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DTSTART;TZID=America/Detroit:20251111T114500
DTEND;TZID=America/Detroit:20251111T124500
DTSTAMP:20251105T194338Z
CREATED:20250926T143952Z
LAST-MODIFIED:20251105T194338Z
UID:10000839-1762861500-1762865100@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nPy-Conformational-Sampling: Towards Predicting Stereoselectivity\nStereoselective reactions are an integral part of organic synthesis due to the abundance of chiral centers in natural products and drug molecules. The design of these reactions remains challenging due to specific substrate requirements\, delicate reaction conditions and more importantly\, multiple competing product-forming transition states (TSs). These TSs often arise from a range of conformers present within the reactant complex. Thus\, predicting stereoselectivity requires detailed insights into favorable interactions amidst the conformational ensemble. This work introduces Py-Conformational-Sampling (PyCoSa) as a methodical approach to sample transition-metal-catalyzed stereoselective reactions. This technique\, when devoted to atroposelective Suzuki-Miyaura coupling to generate axially chiral biaryl products\, shows a variety of mechanistic possibilities through which C(sp2)–C(sp2) bond formation takes place. \nSoumik Das (Chemistry and Scientific Computing)\nSoumik is currently pursuing Ph.D. in Chemistry and Scientific Computing under the supervision of Dr. Paul Zimmerman. His research interests involve developing and applying automated and predictive computational tools using quantum chemistry for reaction design and discovery. Among other things\, he’s also a recipient of MICDE Graduate Fellowship for the academic year 2023-2024 and presented his research in MICDE conference SciFM ’24. \n\nDensity Functional Theory Simulations of Icosahedral Quasicrystals\nQuasicrystals (QCs) are fascinating materials with their long-range aperiodicity and forbidden rotational symmetry\, which opened a new type of classification in crystallography and attracted much attention to its potential applications to condensed matter\, statistical and solid-state physics. The characterization and identification of QCs after the first discovery is widely undertaken\, but thermodynamic stability and kinetics of nucleation are ongoing questions to answer the synthesizability and design novel structures. The quantum mechanical simulation including the density functional theory (DFT) is a widely used method for atomic-scale simulation\, however\, aperiodicity of QC structure makes it challenging to apply a computational model for periodic boundary frameworks. In this present work\, atomistic simulation of Tsai-type ScZn and YbCd icosahedral quasicrystals (iQCs)\, which is one of recently discovered iQCs types\, were performed using density functional theory – finite element (DFT-FE) method to study the thermodynamic stability\, role of surface energy to the stability\, and driving force of QC formation. The size-dependent and mixed-thermodynamic-and-kinetic phase diagram from quantitative theoretical calculations can provide fundamental insights into the origin of QC formation. \nWoohyeon Baek (Materials Science and Engineering and Scientific Computing)\nWoohyeon Baek is a PhD student in Materials Science and Engineering and Scientific Computing under the supervision of Dr. Wenhao Sun. He is working on the thermodynamics and kinetics of non-traditional materials formation from computational simulations including quasicrystals\, minerals\, functional materials\, and organic crystals. \n\nData-Driven Development of Constitutive Equations for Thixotropic Waxy Oil Rheology for Flow Assurance Using Symbolic Regression and PINNs\nWaxy crude oils crystallize below the wax appearance temperature\, forming networks that make rheology strongly dependent on temperature and prior shear history\, complicating pipeline restart operations. We develop a compact\, predictive modeling framework that combines data-driven and mechanistic approaches\, with all methods using differential scanning calorimetry crystallinity measurements to encode temperature effects. Symbolic regression (PySR) trained on two temperatures accurately predicts steady-state flow curves at remaining temperatures. A Fractal Isotropic-Kinematic Hardening (FIKH) model\, fitted at two temperatures for steady response\, predicts steady behavior at other temperatures; for transients\, parameters identified at 5°C reproduce rejuvenation and recovery dynamics at additional temperatures. We introduce LFP-IKH (Liquid Free-Path IKH)\, a novel approach that defines the structural state as liquid-network connectivity bounded by crystallinity. When calibrated only on steady-state data\, LFP-IKH predicts both steady and transient responses across all temperatures without refitting. This yields a mechanism-based framework that requires no parameter adjustment across temperature ranges\, making it suitable for flow-assurance prediction and restart design applications. \nSamuel Ogunwale (Chemical Engineering and Scientific Computing)\nSamuel Ogunwale is a sixth-year PhD student in Chemical Engineering working in the Larson group. His research focuses on developing predictive models for complex fluid systems\, combining mechanistic understanding with experimental validation to address industrial flow assurance challenges.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-5/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-11-11-Das-Baek-Ogunwale.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251104T114500
DTEND;TZID=America/Detroit:20251104T124500
DTSTAMP:20251009T184957Z
CREATED:20250926T143951Z
LAST-MODIFIED:20251009T184957Z
UID:10000838-1762256700-1762260300@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nEmbodying mechano-intelligence in mechanical metastructures for in-memory phononic learning\nMechano-intelligence (MI)—intelligence embodied within the mechanical domain of materials and structures—promises autonomous systems with higher effectiveness\, efficiency\, and resilience. Rather than outsourcing information processing entirely to electronics\, MI envisions materials that store\, process\, and adapt to environmental inputs through intrinsic mechanical responses\, reducing latency and energy while improving robustness in extreme and cyber-contested conditions. Realizing MI requires three elements: a memory module to retain knowledge from inputs\, a computing module to interpret and act on information\, and a physical communication interface linking storage and computation. In this talk\, I will introduce a new approach to realizing MI in and through a reconfigurable phononic metastructures via the concept of in-memory phononic learning\, where mechanical states are programmed to encode and store information and the elastic-wave physics is harnessed to carry out computation and decision—a framework that unifies the full information chain in the mechanical domain and provides efficient\, physically interpretable processing by using elastic waves as the natural communication and processing medium.  \nYuning Zhang (Mechanical Engineering and Scientific Computing)\nYuning is a Ph.D. candidate in Mechanical Engineering under Prof. Kon-Well Wang. His research focuses on wave propagation in phononic metastructures\, and the development of physical computing and mechanical intelligence.  \n\nGlobal Probabilistic Geomagnetic Perturbation Forecasting \nAccurately predicting the horizontal component of the ground magnetic field perturbation (dBH)\, as a proxy for Geomagnetically Induced Currents (GICs)\, is crucial for estimating the impact of geomagnetic storms and remains a topic under active investigation. The current operational Geospace model is computationally expensive for fine-grid global simulations\, while existing machine learning methods consistently tend to underestimate dBH. Additionally\, these models either lack uncertainty quantification (UQ)\, which is either overlooked or treated as secondary. In this work\, as part of the NextGen SWMF project funded by NSF\, we develop a data-driven\, grid-free global model using deep Gaussian process (DGP)\, a Bayesian non-parametric approach that forecasts the dBH for the full surface of Earth with calibrated uncertainty. The model uses solar wind measurements and the Dst index as input\, and it is trained based on ground magnetometer station data provided by SuperMAG over the period 1995-2022. The model’s predictions are evaluated based on the Heidke skill score (HSS) for a total of 23 storms in 2015. We further test the model on the 2024 Gannon superstorm. The results demonstrate that our model outperforms the state-of-the-art model\, with predictions exhibiting high accuracy in mid-latitudes and high-latitude regions in the northern hemisphere. \nHongfan Chen (Mechanical Engineering and Scientific Computing)\nHongfan Chen is a fourth-year PhD student in Mechanical Engineering and the Michigan Institute for Computational Discovery and Engineering (MICDE) Scientific Computing program. His research develops computational methods for uncertainty quantification (UQ) and machine learning (ML) in complex scientific and engineering systems\, with emphases on data assimilation (DA)\, knowledge-guided machine learning\, and optimal experimental design (OED).  \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-4/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-11-4-Zhang-Chen.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251028T114500
DTEND;TZID=America/Detroit:20251028T124500
DTSTAMP:20251027T214532Z
CREATED:20250926T143950Z
LAST-MODIFIED:20251027T214532Z
UID:10000837-1761651900-1761655500@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nAutomated removal of artifactual false positive High Frequency Oscillations in intracranial EEG\nHigh frequency oscillations (HFOs) are a promising biomarker of the epileptogenic zone. Automated HFO detectors alleviate manual labeling but false positives\, artifacts\, remain. Clinicians recognize artifacts readily while viewing the EEG at standard resolution across channels\, and observing artifacts at the times of HFO events leads to a loss of trust in the detections. In this work\, we collect a new gold standard of HFO labeling using clinician expertise\, train several machine learning algorithms\, and develop an artifact filter compatible with any HFO detector to distinguish between true and false positives. \nAshley Tan (Mechanical Engineering and Scientific Computing)\nHer research involves developing engineering tools to control epilepsy. She is currently developing machine learning methods for artifact detection of a potential biomarker and investigating the effects of electrical brain stimulation on pathological activity. \n\nEmergence of three-dimensional structures from vortex pair instabilities in shocked interfacial flows\nThe Crow instability is a vortex-line instability that leads to the three-dimensional growth of perturbations in counter-rotating vortices\, with pinch-off leading to the generation of vortex rings at late time. Classically\, two incompressible\, inviscid vortices are studied in this context; in the present work\, we use numerical simulations to demonstrate that the cores which are generated from the compressible multi-material Richtmyer-Meshkov instability are subject to the Crow instability. Thus\, the onset of the Crow instability from the Richtmyer-Meshkov-induced cores can act as a mechanism for transitioning a nominally two-dimensional Richtmyer-Meshkov flow to three dimensions. \nWilliam White (Mechanical Engineering and Scientific Computing)\nWilliam is a PhD student in the Scientific Computing and Flow Physics Lab working on high-order numerical methods for compressible interfacial flows\, as well as interfacial and vortex-line hydrodynamic instabilities. \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-3/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-10-28-Tan-White.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251007T114500
DTEND;TZID=America/Detroit:20251007T124500
DTSTAMP:20251008T041229Z
CREATED:20250926T143945Z
LAST-MODIFIED:20251008T041229Z
UID:10000833-1759837500-1759841100@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Seminar Series
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. Lunch will be served. These events are open to the public\, but we request that all who plan to attend register in advance. Planned sessions will be canceled if no one signs up to present\, and registered attendees will be notified. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nBridging Wavefunctions and Density Functionals: Unlocking Accurate Data for Functional Development\nDensity Functional Theory (DFT) is one of the most widely used electronic structure methods in chemistry\, physics\, and materials science\, striking a balance between accuracy and computational efficiency. However\, its accuracy is fundamentally limited by the choice of the exchange-correlation (XC) functional\, which remains an approximation in all practical applications. A key shortcoming of existing functionals is their failure to reproduce critical features of the exact XC potential\, such as the asymptotic -1/r decay and the step at integer electron transitions—features essential for correctly describing ionization energies\, band gaps\, and dissociation limits. In this work\, we take a data-driven approach to improving DFT by generating XC potentials from full configuration interaction (FCI) calculations. Using a large Slater basis\, we systematically recover key features of the exact XC potential across atomic systems and analyze their behavior. Additionally\, we compute exchange-correlation energy densities via an aufbau path integral\, ensuring consistency with total XC energy values from FCI. These highly accurate DFT quantities establish a benchmark for diagnosing errors in existing functionals and guiding the development of new approximations that incorporate wavefunction-level accuracy while retaining DFT’s efficiency. \nVaibhav Khanna (Chemistry and Scientific Computing)\nVaibhav Khanna is a Ph.D. candidate in Chemistry and Scientific Computing at the University of Michigan\, where he works under the supervision of Prof. Paul Zimmerman. His research focuses on developing improved density functionals that bridge the gap between highly accurate but computationally expensive wavefunction methods and the efficiency of the popular Density Functional Theory (DFT). By incorporating wavefunction-level accuracy\, his work aims to significantly improve the predictive power of DFT\, a widely used computational method in chemistry\, physics\, and materials science. \n\nTurbulence transport and size segregation of shock-driven multiphase flows\nThe phenomena of a shock-wave interacting with a particle suspension is observed in applications such as pulse detonation engines\, volcanic eruptions\, coal dust explosions and plume-surface interactions during spacecraft landings. Compressibility effects during these interactions give rise to complicated dynamics in the suspensions. While there has been a lot of effort and progress in modeling incompressible flows\, much less work has been done in modeling the microscale physics in turbulent flows at finite Mach numbers. Particle-resolved numerical simulations of shock passing through monodisperse suspensions are used to guide the development of subgrid-scale models for turbulence transport. Turbulent kinetic energy (TKE) is found to contribute to a significant portion of the resolved kinetic energy. A two-equation model is proposed and implemented within a hyperbolic Eulerian-based two-fluid model. The model is found to be accurate across a wide range of volume fractions and Mach numbers. Additionally\, to analyse particle dispersion and segregation in bidisperse suspensions with extreme diameter size ratios\, a hybrid numerical framework is developed\, combining an immersed boundary method for large particles with Lagrangian particle tracking of small particles.  \nArchana Sridhar (Aerospace Engineering and Scientific Computing)\nArchana is a 5th year PhD student in the Aerospace Engineering department. She is a MICDE Fellow working with Dr. Jesse Capecelatro. Her focus is on computational fluid dynamics of multiphase compressible flows. \n\n 
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series/
LOCATION:North Quad – 2185
CATEGORIES:Astronomy,Chemical Engineering,Chemistry,College Of Engineering,Computational Science,computing,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Mechanical Engineering,Micde,Michigan Engineering,Networking,Phd Seminar,Political Science,Prospective Graduate Students,Rackham,Research,Science,Scientific Computing,Seminar,Talk
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-10-07-Khanna-Sridhar.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250711T120000
DTEND;TZID=America/Detroit:20250711T130000
DTSTAMP:20260522T152604Z
CREATED:20250709T192007Z
LAST-MODIFIED:20260522T152604Z
UID:10000827-1752235200-1752238800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nRegister to attend\n\nBridging Bonds and Bands: A Toolkit for Interpreting the Crystal Chemistry of Electronic Structure\nThis talk explores how we can better understand chemical bonding and electronic structure in materials using quantum mechanical calculations. I first show how specific atomic bonds shape the electronic bands of materials like silicon\, using simplified models built from density functional theory (DFT). Then\, I introduce a new method called COGITO\, which creates a clear and flexible atomic picture of the wavefunctions in DFT. COGITO builds a set of atomic orbitals that accurately capture the full electronic structure and reveal where and how electrons are shared between atoms. This makes it possible to see and measure covalent bonds\, estimate bond energies\, and even understand magnetic interactions. I demonstrate how COGITO can explain why some crystal structures are more stable than others and how different DFT functionals change bonding—giving us a powerful new tool for interpreting and designing materials. \nEmily Oliphant\, Materials Science & Engineering and Scientific Computing\nEmily Oliphant is a 5th year PhD student working with Professor Wenhao Sun and Professor Emmanouil Kioupakis. She is working to obtain atom and bonding insight in density functional theory. \n\nAn immersed boundary method formulation for aortic dissection simulation\nAortic dissection is characterized by a disruption of the intima\, leading to delamination of the aortic wall and formation of a true lumen (TL) and a false lumen (FL)\, separated by an intimal flap or septum which moves cyclically due to pressure gradients between TL and FL. Aortic dissection can lead to complications\, including end-organ malperfusion and aortic rupture. The scarcity of clinical hemodynamic data\, such as pressure and flow in the TL and FL\, complicates aortic dissection research\, driving the use of computational simulations to study its flow dynamics and flap motion. Computational simulations can be used to study the aortic dissection dynamics and their relation to pressure gradient across TL and FL. Fluid–structure-interaction (FSI) methods have been used in aortic dissection simulations to investigate the impact of the intimal flap motion on hemodynamic parameters. While the Arbitrary Lagrangian–Eulerian (ALE) approach is widely used for the aortic dissection problems\, it faces challenges: frequent fluid mesh updates increase computational costs\, and mesh quality can degrade when the flap nears the aortic wall. Immersed Boundary Methods (IBM) offer an attractive alternative\, avoiding fluid remeshing and effectively capturing the dynamics of thin structures\, as demonstrated in heart valve simulations among other applications. In this work\, we developed an IBM algorithm within a Finite Element flow solver framework using unstructured grids and computationally efficient rotation-free shell formulation to simulate aortic dissection\, providing a practical approach to study its complex flow and structural behavior in patient-specific cases \nTaeouk Kim\, Biomedical Engineering and Scientific Computing\nTaeouk is a 5th year PhD student in the Biomedical Engineering department. He is working with Dr. Alberto Figueroa at the computational vascular biomechanics lab.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-20250711/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250422T120000
DTEND;TZID=America/Detroit:20250422T130000
DTSTAMP:20260522T152527Z
CREATED:20250114T140812Z
LAST-MODIFIED:20260522T152527Z
UID:10000798-1745323200-1745326800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nRegister to attend\n\nApplications of the phase-field method to polycrystalline materials\nPhase-field modeling is a common diffuse interface method for simulating microstructure evolution due to its ability to capture complex morphologies without the need for explicitly tracking phase interfaces. A typical application of the phase-field method is polycrystalline grain growth during annealing\, where grain boundaries migrate toward their centers of curvature. Recent studies have shown abnormally large grains can be grown in shape memory alloys during cyclic annealing due to additional driving forces generated during the growth and dissolution of second-phase precipitates. In this work\, we model grain growth via a phase-field model that considers stored energy generated during the cyclic heat treatments. Applications of the phase-field method to experimentally acquired grain microstructures will also be discussed. \nZach Croft\, Applied Physics\nZach is a PhD student in the Applied Physics program. He works in the field of computational materials science with an emphasis on phase-field modeling of polycrystalline evolution and solidification of alloys under Professor Katsuyo Thornton. \n\nUsing causal inference to estimate counterfactual disparity measures for access to weight management treatments\nType 2 Diabetes (T2D) is a prevalent condition with significant variation in outcomes based on race and ethnicity\, underscoring the need for more improved prevention practices. Because effective weight management is a key component of T2D prevention\, increasing access to evidence-based treatments for those most at-risk for developing T2D is imperative. Yet\, existing population health management approaches do not typically measure disparities in access to treatments or do so in ways that do not account for the increased risk experienced by certain patient populations. This talk will (1) describe how causal inference was used to calculate counterfactual estimates of disparities in referral to weight management treatments among a population of adults with obesity\, (2) compare counterfactual estimates generating from the standard approach vs. a risk-based approach \, and (3) share UM research\, computing\, and other resources that supports this research. \nCassie Turner\, Health Infrastructures and Learning Systems\nCassie has a joint appointment at Michigan Medicine and the Ann Arbor Veteran Affairs Health System\, where she contributes to health research and practice focused on improving metabolic health through leveraging analytics\, novel care models\, and learning health systems approaches.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-4-22-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250415T120000
DTEND;TZID=America/Detroit:20250415T133000
DTSTAMP:20260522T152446Z
CREATED:20250114T141442Z
LAST-MODIFIED:20260522T152446Z
UID:10000797-1744718400-1744723800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nRegister to attend\n\nTemporal relationship between acute noise exposure and heart rate variability change\nExcessive noise in daily activities and during sleep is disturbing and causes annoyance and stress over time. Noise\, among numerous environmental pollutants\, also independently contributes to the risk of cardiovascular diseases potentially through stress responses. Heart rate variability (HRV) change\, which reflects the neurohormonal and automatic neural responses to stress\, has been evaluted as an outcome to air pollution (PM 2.5\, ozone)\, smoking\, and other exposures. This analysis explored feasibility of using time series analysis to examine the noise and HRV association in a large longitudinal cohort. Alternative modeling approaches were also explored to accommodate the complex structure of this time series data. \nXin Zhang\, EHS and Scientific Computing\nXin Zhang is a 3rd year PhD candidate in the Department of Environmental Health Sciences at the University of Michigan. Her research focuses on evaluating the effects of environmental noise exposure on auditory and cardiovascular health outcomes using integrated data from personal devices with wearable sensors. \n\nEngineering The Immune Response To Improve Muscle Regeneration\nJesus Castor\, Biomedical Engineering\n 
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-4-15-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-04-22-Zhang-Castor-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250408T113000
DTEND;TZID=America/Detroit:20250408T130000
DTSTAMP:20260413T190501Z
CREATED:20250114T141754Z
LAST-MODIFIED:20260413T190501Z
UID:10000796-1744111800-1744117200@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nRegister to attend\n  \n  \n\nProbabilistic Rounding Uncertainty Analysis for Floating-Point Statistical Models\nAdvancements in computer hardware now allow low- and mixed-precision arithmetic to improve efficiency\, especially on new architectures. It is thus critical that the rounding uncertainty be rigorously quantified alongside traditional sources of uncertainty including those from observations\, sampling\, and numerical discretization. Traditional deterministic rounding uncertainty analysis (DBEA) assumes that the absolute rounding errors equal the unit roundoff u\, considering the worst-case scenario. This work presents a novel probabilistic rounding uncertainty analysis called VIBEA. By treating rounding errors as i.i.d. random variables and leveraging concentration inequalities\, VIBEA provides high-confidence estimates for rounding uncertainty using higher-order rounding error statistics. The presented framework is valid for all problem sizes n\, unlike DBEA\, which requires nu<1. Further\, it can account for the potential cancellation of rounding errors\, resulting in rounding uncertainty estimates that grow slowly with n. We demonstrate that quantifying rounding uncertainty alongside traditional sources allows for a more efficient allocation of computational resources\, balancing efficiency with accuracy. This study takes a step towards a comprehensive mixed-precision approach to enhance model reliability and optimize resource allocation in predictive modeling. The talk will conclude with a vision for end-to-end\, formally verified numerics for scientific computing. \nSahil Bhola\, Aerospace Engineering and Scientific Computing\nSahil Bhola is a 4th-year Ph.D. candidate in Aerospace Engineering and Scientific Computing at the University of Michigan. He is a MICDE Fellow and a J.N. Tata Scholar\, advised by Prof. Karthik Duraisamy. He holds a master’s degree in Aerospace Engineering from the University of Michigan and a bachelor’s degree in Mechanical Engineering from Thapar University\, India. His research focuses on adaptive mixed-precision methods\, experimental design for potential energy surfaces\, and flow-based generative models for Bayesian inference. \n\nHomogenous Cities? How Conflict and Politics Shape the Urban Topography\nThe relationship between armed conflict\, politics\, and the urban built environment \nMartin Macias Medellin\, Political Science\nMartin Macias Medellin is interested in the dynamics of mass political dissent\, political and criminal violence\, and state-building processes. In his doctoral dissertation he studies how conflict affects the way in which cities are built and how the physical structures of urban areas affect the dynamics of armed conflict. \n\nMinimally Orthogonal Causal Effect Estimation\nCausal Machine Learning \nYiman Ren\, Business Economics\nYiman Ren is a final year PhD student in Business Economics and Scientific Computing at Ross School of Business. Her research focuses on financial economics and causal machine learning.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-4-8-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-04-08-Bhola-Macias-Medellin-Ren-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250401T120000
DTEND;TZID=America/Detroit:20250401T130000
DTSTAMP:20260522T154208Z
CREATED:20250114T141907Z
LAST-MODIFIED:20260522T154208Z
UID:10000795-1743508800-1743512400@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nRegister to attend\n\nMonitoring the fidelity of the LIGO detectors\nThe detection of gravitational waves depends on LIGO’s ability to discriminate authentic signals from instrumental noise. To improve this capability\, the LIGO Scientific Collaboration employs hardware injections\, controlled\, simulated signals introduced directly into the detectors. These injections validate the analysis pipelines and refine the calibration of the detector. This study focuses on continuous- wave signals from the initial phase of the fourth observing run (O4a)\, using simulated emissions from rapidly rotating neutron stars as benchmarks to assess sensitivity and data-processing efficiency. The analysis employs a template generation approach that uses complex conjugates to align observational data with theoretical signal templates and offers probabilistic validation of detected signals. An investigation explores the role of hardware injections in the refinement of software models and the maintenance of the timing and amplitude. By utilizing daily diagnostic plots for a diverse array of synthetic neutron star signals\, including both binary and isolated systems\, the detector’s responsiveness is evaluated over a broad frequency spectrum. The results emphasize the importance of hardware injections in sustaining calibration standards and affirming LIGO’s reliability in gravitational wave detection \nPreet Baxi\, Physics and Scientific Computing\nPreet Baxi is an innovative Data Scientist and Algorithm Developer with experience in scientific computing\, data pipeline optimization\, and business data analysis. Specializing in developing advanced algorithms and has worked extensively in gravitational wave data analysis\, contributing to cutting-edge research in astrophysics. Currently working in large language models (LLMs)\, focusing on their development and optimization. \n\nFast Summation for Geophysical Fluid Dynamics\nFast Summation refers to a family of techniques for the fast approximation of N-body sums. While traditionally fast summation has been applied to problems coming from astrophysics or electrodynamics\, many problems in geophysical fluid dynamics can be rewritten as the computation of a spherical convolution\, and when these integrals are discretized\, the resulting problem is a N-body problem. In this talk\, I discuss a novel spherical tree code/fast multipole method based on barycentric Lagrange interpolation\, as well as applications to problems coming from geophysical fluid dynamics\, including tidal modeling and the problem of computing Self Attraction and Loading in the ocean model MOM6. \nAnthony Chen\, Applied and Interdisciplinary Mathematics and Scientific Computing\nAnthony Chen is a 4th year in Applied and Interdisciplinary Mathematics working on fast summation for problems in geophysics.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-4-1-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-04-01-Baxi-Chen.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250318T120000
DTEND;TZID=America/Detroit:20250318T130000
DTSTAMP:20250228T184043Z
CREATED:20250114T142206Z
LAST-MODIFIED:20250228T184043Z
UID:10000794-1742299200-1742302800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. If you have any questions\, please email micde-phd@umich.edu. \nRegister to attend\n  \n  \n\nSolving High Reynolds Number Flows on Cartesian Cut-cell Meshes using a Jacobian-Free Newton–Krylov Method\nIn this work\, we developed a Newton–Krylov method for a second-order Cartesian cut cell Reynolds-averaged Navier–Stokes (RANS) solver\, Viscous Aerodynamic Cartesian Cut cells (VACC)\, with the one equation Spalart–Allmaras (SA) turbulence model. The Newton–Krylov method uses pseudo-transient continuation and a point Jacobi preconditioner to accelerate convergence. Then various wall functions were compared on a finite flat plate and 2D bump cases. The SA analytical wall function was used as a baseline. An ordinary differential equation (ODE) wall function and wall-modeled RANS (WMRANS) approach were also implemented. Although these methods all showed promise\, the interior viscous fluxes resulted in oscillatory pressures. These oscillations degraded the accuracy of all of the solutions. \nAlex Kleb\, Aerospace Engineering\nAlex Kleb is a fifth year PhD candidate in the CFD Group and MDO lab in the Aerospace Engineering department. \n\nGeometrically Nonlinear Methods for High-Fidelity MDO of Very-Flexible Aircraft\nOver the past decade\, advances in Multidisciplinary Design Optimization (MDO) have enabled the optimization of aircraft wings using high-fidelity simulations of their coupled aerodynamic and structural behavior. Using RANS CFD and detailed structural finite element wingbox models\, the aerodynamic shape and internal structural sizing of a wing can be optimized concurrently to tailor the wing’s aeroelastic behavior and optimally trade-off drag and structural mass. This capability makes MDO a key enabling technology for the next generation of efficient high-aspect-ratio transport aircraft. However\, as their aspect-ratios increase\, these wings increasingly exhibit geometrically nonlinear behavior that cannot be correctly modeled by typical linear structural analysis methods. This work demonstrates the first simultaneous optimization of a wing’s aerodynamic shape and structural sizing using high-fidelity geometrically nonlinear models. Our methods are implemented in the open-source finite element library\, TACS\, and include a geometrically nonlinear shell element formulation\, an efficient and robust nonlinear solver\, and a constitutive model for stiffened shells. We demonstrate the ability to couple these nonlinear structural analysis tools to a high-fidelity RANS CFD solver using a geometrically nonlinear load and displacement transfer scheme. Finally\, we use this capability to optimize a single-aisle commercial transport aircraft wing featuring 547 design variables and 1277 constraints. \nAlasdair Christison Gray\, Aerospace Engineering\nAlasdair Christison Gray is a 5th year PhD student in the Aerospace Engineering department’s MDO Lab. His research focuses on applying high performance computing to the large scale design optimization of aircraft wings.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-3-18-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-03-18-Kleb-Christison-Gray.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250311T120000
DTEND;TZID=America/Detroit:20250311T130000
DTSTAMP:20250225T214448Z
CREATED:20250225T214118Z
LAST-MODIFIED:20250225T214448Z
UID:10000810-1741694400-1741698000@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:  \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. If you have any questions\, please email micde-phd@umich.edu. \nRegister to attend\n  \n\nUnraveling Rotator Cuff Tendon Tear Growth Mechanisms with Full-Volume Strains and Data-Driven Modeling\nIn this talk\, I will show how full-volume methods\, which can probe internal locations of a material\, enable the detection of regions with high shear strain concentration in intact and torn rotator cuff tendons. I will also explain my approach to use these full-volume datasets to develop a finite element model of this tendon using variational system identification\, and future work to obtain validated computational models that can predict tear growth. \nNathaly Villacis\, Mechanical Engineering and Scientific Computing\nNathaly is a fifth year Ph.D. candidate in Mechanical Engineering\, who works at the Soft Tissue Mechanics Lab\, supervised by Dr. Ellen Arruda. Her research involves the characterization of rotator cuff tendon tear growth with experimental and computational methods. She will work on machine learning models of the rotator cuff once she finishes her Ph.D. \n\nIncremental Tensor Decompositions for Machine Learning and Bayesian Inference\nWith recent advancements in large-scale parallel computing\, there is an increased interest in constructing high-fidelity digital twins of complex systems. Especially for systems that have limited physical experimentation possibilities\, high-fidelity simulations may provide the main source of information for constructing digital twins. However\, performing such simulations is computationally intensive and generates extreme amounts of data. The size of the generated simulation data makes it challenging to use the data in further analysis. As the spatial and temporal resolution of these simulations grow\, even storing the data may become a serious bottleneck. This talk proposes a solution to this multi-faceted problem through the use of low-rank tensor decompositions. Specifically\, we present incremental algorithms that provide computationally efficient ways of compressing data with accuracy guarantees. We showcase a diverse array of applications\, from 3D turbulent Navier-Stokes simulations to Minecraft gameplay videos\, demonstrating the versatility and power of these techniques. \nDoruk Aksoy\, Aerospace Engineering and Scientific Computing\nDoruk is a 5th year Ph.D. candidate in the Department of Aerospace Engineering in the Computational Autonomy group. His research focuses on developing incremental low-rank tensor decomposition algorithms to compress large-scale data for downstream machine learning applications.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-20250311/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/02/2025-03-11-Villacis-Aksoy.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250225T120000
DTEND;TZID=America/Detroit:20250225T130000
DTSTAMP:20250221T144301Z
CREATED:20250114T142545Z
LAST-MODIFIED:20250221T144301Z
UID:10000793-1740484800-1740488400@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:  \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. If you have any questions\, please email micde-phd@umich.edu. \nRegister to attend\n  \n\nNumerical simulation of the collapse of a cavitation bubble near a deformable solid surface\nThe exact mechanisms leading to the permanent deformation of solid surfaces\, following a cavitation event\, are still unclear. Specifically\, the relationship between the characteristics of a given cavitation bubble and the shape of the resulting pit is unknown. In this study\, we numerically investigate the collapse of a single cavitation bubble near a solid surface\, with the objective of characterizing how the pit shape (height and depth) changes with the bubble initial radius\, its distance from the solid and the initial pressure difference at the bubble interface. To this end\, we implement a diffuse interface method for the interaction of multiple compressible fluids and hyperelastic solids in an Eulerian frame of reference. This method numerically solves the evolution equations of mass\, momentum\, energy as well as volume fractions of each material and of the mixture. The model is closed by splitting the internal energy of each material into hydrodynamic and elastic contributions\, with appropriate equations of state. A set of evolution equations of local cobasis\, with a plastic source term\, are used to compute the elastic Finger tensor\, which is needed to obtain the elastic energy and the deviatoric stress. We additionally provide improvements to the numerical method to preserve interface conditions. The proposed method allows to elucidate some of the mechanisms of cavitation pitting.  \nBaudouin Fonkwa Kamga\, Mechanical Engineering and Scientific Computing\nBaudouin is a 4th year PhD student in the department of Mechanical Engineering\, under the supervision of Eric Johnsen. His research combines the theoretical study of cavitation in viscoelastic medium and the development of numerical methods for multimaterial compressible flows. \n\nScalable foundation model training for computational pathology\nScalable and efficient foundation model training is critical for advancing computational pathology. In this talk\, we present a two-stage self-supervised pipeline for whole slide image (WSI) analysis. First\, HiDisc leverages the inherent patient–slide–patch hierarchy to learn robust visual representations efficiently without relying on heavy data augmentation\, outperforming existing methods in cancer diagnosis and genetic mutation prediction. Building on these high-quality patch-level features\, our second stage\, Slide Pre-trained Transformers (SPT)\, treats WSI patches as tokens and integrates data transformation strategies from both language and vision models to capture the rich morphological diversity of gigapixel images. Together\, these methods offer a scalable\, efficient framework for training foundation models that drive robust performance across a range of diagnostic tasks. \nXinhai Hou\, Bioinformatics and Scientific Computing\nXinhai Hou is a PhD candidate in the department of computational medicine and bioinformatics. His research focuses on self-supervised learning\, computer vision\, and multimodal machine learning\, with a particular emphasis on real-world applications such as AI in healthcare and medicine.
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-2-25-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-02-25-Fonkwa-Kamga-Hou-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250211T120000
DTEND;TZID=America/Detroit:20250211T130000
DTSTAMP:20260522T152322Z
CREATED:20250114T150617Z
LAST-MODIFIED:20260522T152322Z
UID:10000792-1739275200-1739278800@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nAdaptive Deep Learning-Powered Multi-fidelity Stratified Sampling for Efficient Failure Analysis of Nonlinear Dynamic Systems\nCurrent stochastic simulation-based frameworks that leverage variance reduction techniques still require a substantial number of model evaluations to estimate small failure probabilities associated with rare events. In the context of high-fidelity modeling environments\, these frameworks can become computationally challenging\, especially when dealing with complex nonlinear systems. Despite the potential of providing remarkable computational efficiency\, low-fidelity models may yield bias if used directly. To address this challenge\, this work introduces a multi-fidelity framework within the setting of stratified sampling\, termed Multi-Fidelity Stratified Sampling (MFSS)\, for efficient estimation of failure probabilities given various limit states of interest. In this approach\, the strata-wise failure probabilities\, associated with a carefully selected stratification variable\, are estimated by multi-fidelity Monte Carlo. To minimize the computational budget\, the high-fidelity data used in the stratified multi-fidelity estimator is also employed as training data for developing a deep learning-based metamodel\, which then serves as a low-fidelity model. To derive the trade-off between the approximation quality and computational demand associated with the metamodel\, an adaptive strategy is proposed to seek the minimal training data that ensures a desired correlation between the high- and low-fidelity models. Through application to a full-scale high-rise steel building subject to stochastic wind excitation\, the proposed scheme is demonstrated to be capable of accurately reproducing exceedance probability curves of nonlinear responses of interest with significant computational gains\, compared to variance reduction techniques relying solely on high-fidelity models. \nLiuyun Xu (Civil Engineering and Scientific Computing)\nLiuyun Xu is a fourth-year Ph.D. candidate in Civil Engineering and Scientific Computing at the University of Michigan. Her research lies in enhancing the resilience and adaptation of civil infrastructures against climate-related hazards by leveraging AI/ML\, scientific computing and data science.  \n\nA Hybrid Surrogate Modeling Framework for Digital Twins of Nuclear Energy Systems\nNuclear Power Plants (NPPs) are complex systems that can benefit from Digital Twin (DT) technologies to reduce operational costs and increase plant reliability. A system surrogate model is developed to predict quantities and responses associated with diverse physical and computational assets. The proposed hybrid surrogate modeling framework is applied to a Pebble-Bed Fluoride-salt-cooled High-temperature Reactor (PB-FHR)\, with a two-loop reactor configuration. The surrogate’s hybrid design combines the accuracy of physical models and computational efficiency of data-driven models to achieve speed and predictive robustness. This surrogate model is adaptable through assimilation with online measurements\, which is highlighted in a proposed DT framework design. \nJasmin Lim (Aerospace Engineering and Scientific Computing)\nJasmin is a 5th PhD student in the department of aerospace engineering in the Computational Aerosciences Laboratory under the advisement of Karthik Duraisamy. Her research is focused on developing data-driven methods for digital twin applications; which includes surrogate modeling\, data assimilation\, and system framework design.  \n\nRegister to attend
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-2-11-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-02-11-Xu-Lim.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250204T120000
DTEND;TZID=America/Detroit:20250204T130000
DTSTAMP:20260522T154253Z
CREATED:20250114T145459Z
LAST-MODIFIED:20260522T154253Z
UID:10000791-1738670400-1738674000@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu. \nRegister to attend \n\nAerodynamic Shape Optimization with Curved Mesh Adaptation\nIn this talk we present a method for performing curved mesh adaptation during aerodynamic shape optimization with high-order computational fluid dynamics (CFD). High-order methods are promising because they offer increased accuracy for a given mesh. Mesh adaptation further improves the efficiency of high-order methods. These high-order methods require curved meshes to properly capture the simulated geometry and a mesh adaptation process that can generate curved meshes. Adapting these curved meshes needs to be robust as any failures will require human intervention inside the automated optimization loop. We first will present HOEP\, a novel and highly robust method for adapting highly-anisotropic curved meshes. Then we will present our adaptation strategy that balances computational cost with accuracy and show results for transonic airfoil optimization. \nAlexander Coppeans\, Aerospace Engineering and Scientific Computing\nAlexander Coppeans is a 5th year PhD Student in Aerospace Engineering and Scientific Computing. His research focuses on high-order adaptive methods for CFD based aerodynamic shape optimization. \nRegister to attend
URL:https://micde.umich.edu/event/ph-d-in-scientific-computing-student-seminars-02-04-2025/
LOCATION:4th floor conference room\, Green Ct.\, 3520 Green Ct.\, Ann Arbor\, MI\, 48105\, United States
CATEGORIES:Micde,MICDE PhD Seminar Series,Phd Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241209T121500
DTEND;TZID=America/Detroit:20241209T131500
DTSTAMP:20241115T183858Z
CREATED:20240924T215159Z
LAST-MODIFIED:20241115T183858Z
UID:10000767-1733746500-1733750100@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:Mahmoud Komaiha (Biomedical Engineering) will give a talk on BME and Scientific Computing. \nZhucong Xi (Materials Science & Engineering) will give a talk on Multiscale Simulations of Solute Clustering in Aluminum Alloys. \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-8/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241202T121500
DTEND;TZID=America/Detroit:20241202T131500
DTSTAMP:20241115T184037Z
CREATED:20240924T215200Z
LAST-MODIFIED:20241115T184037Z
UID:10000768-1733141700-1733145300@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:Shuai Che from the Nuclear Engineering & Radiological Sciences department will be giving a talk on Thermal-sturctural analysis of printed circuit heat exchangers and supporting structures for molten salt test facility. \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-10/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/09/2024-12-2-Updated.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241118T121500
DTEND;TZID=America/Detroit:20241118T131500
DTSTAMP:20241101T183341Z
CREATED:20240924T215200Z
LAST-MODIFIED:20241101T183341Z
UID:10000770-1731932100-1731935700@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-12/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241111T121500
DTEND;TZID=America/Detroit:20241111T131500
DTSTAMP:20250107T180016Z
CREATED:20240924T215158Z
LAST-MODIFIED:20250107T180016Z
UID:10000764-1731327300-1731330900@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars: Vishal Subramanian / Heting Fu
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu. \n\nAccelerating Fock exact exchange calculations using Tucker Tensor techniques \nDensity Functional Theory (DFT) is widely used to predict the electronic structure and properties of a broad range of materials. Although exact in theory\, DFT simulations rely on exchange-correlation (Exc) functionals that are approximated in practice. The accuracy of DFT calculations is solely dependent on the accuracy of the Exc functionals. Hybrid exchange-correlation functionals are a class of functionals that have been shown to match experimental observations more closely compared to other Exc functionals. However\, the use of hybrid Exc functionals necessitates the computation of Fock exact exchange\, significantly increasing the computational cost. Furthermore\, the nature of Fock exact exchange demands a substantial increase in memory requirements and communication across processors. The latter is a serious issue as it affects the scalability of the code\, restricting routine simulations to a few tens of atoms. In this work\, we have developed a Tucker Tensor-based approach that significantly reduces the computational cost of Fock exact exchange calculations. We have incorporated an innovative communication pattern that reduces communication without significantly increasing peak memory usage. Consequently\, we have developed a robust\, efficient\, and scalable algorithm that achieves an order-of-magnitude speedup over the current state of the art. \nVishal Subramanian (Materials Science & Engineering and Scientific Computing) \nVishal Subramanian is a PhD candidate in the Materials Science and Engineering department. He is interested in harnessing the power of linear algebra and high-performance computing to develop robust\, and efficient algorithms that can compute material properties accurately. His work with Prof. Gavini’s group developing algorithms and scalable implementations for fast density functional theory (DFT) calculations on large-scale systems earned him the 2023 Gordon Bell Prize – the highest honor given in high-performance computing. \n\nTopology Optimization for Die Casting with Nonplanar Parting Surfaces \nThis talk presents a density-based topology optimization method for the simultaneous design of die-castable geometry\, die drawing directions\, and arbitrarily nonplanar parting surface. Viewing a die casted part as a two-component system consisting of the cavities of die halves\, an arbitrarily nonplanar parting surface is represented as the boundaries between adjacent partitioned domains similar to the joints in multi-component topology optimization (MTO). The draw direction of each die half is represented as a probability distribution to avoid premature convergence\, and the undercut of a part geometry in the draw direction is evaluated using the gradient of the density field. Several numerical examples are presented to demonstrate the advantages of the inclusion of nonplanar parting surfaces as optimization variables. \nHeting Fu (Mechanical Engineering and Scientific Computing) \nHeting Fu is a Ph.D. candidate under the guidance of Professor Kazuhiro Saitou in Mechanical Engineering. His research involves multi-component\, multi-material\, and multi-process topology optimization.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-6/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2024/09/Vishal-Subramanian-Heting-Fu.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241028T121500
DTEND;TZID=America/Detroit:20241028T131500
DTSTAMP:20240926T204946Z
CREATED:20240924T215158Z
LAST-MODIFIED:20240926T204946Z
UID:10000762-1730117700-1730121300@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-4/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241021T121500
DTEND;TZID=America/Detroit:20241021T131500
DTSTAMP:20240926T204936Z
CREATED:20240924T215157Z
LAST-MODIFIED:20240926T204936Z
UID:10000760-1729512900-1729516500@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-2/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20241014T121500
DTEND;TZID=America/Detroit:20241014T131500
DTSTAMP:20240926T204844Z
CREATED:20240924T215157Z
LAST-MODIFIED:20240926T204844Z
UID:10000758-1728908100-1728911700@micde.umich.edu
SUMMARY:Ph.D. in Scientific Computing Student Seminars
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we request that all who plan to attend register in advance. \nIf you have any questions\, please email micde-phd@umich.edu.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-student-seminars-14/
LOCATION:Undergraduate Science Building – 1250
CATEGORIES:Micde,Phd Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240416T120000
DTEND;TZID=America/Detroit:20240416T130000
DTSTAMP:20240414T192856Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240414T192856Z
UID:10000676-1713268800-1713272400@micde.umich.edu
SUMMARY:Workshop / Seminar:MICDE Ph.D. Student Seminar: Anna Halstenbach and Katie Nissen
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public but we ask that all attendees register so that we can prepare properly. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \n  \nAnna Halstenbach: “Uncovering the network of political parties’ event sponsors in Germany”\nGray money in politics – those contributions that don’t fall under transparency regulations but cannot be made completely anonymous either\, for example sponsorships of political parties’ events – could change our understanding of money as a signal. However\, the fact that neither political parties nor firms are obliged to disclose such transactions makes studying them difficult. In the talk\, I will present one approach to measure gray money on the basis of tweets from party conferences.\n\nAnna Halstenbach\, Ph.D. candidate in Political Science and Scientific Computing\nAnna earned her Bachelor’s degree from the University of Mannheim and her Master’s degree from Heinrich Heine University Düsseldorf. Her current research analyzes the distinct incentives within the regulatory frameworks governing political party finances in Germany and the United States. Additionally\, she explores the impact of consumer behavior on firms’ decisions to be vocal about their political donations and take controversial political stances.\n\n\n\nRegister to attend this seminar\n\n\n\nKatie Nissen: “Climate Change Protests and Gender: The Influence of Role Incongruence on Support for Social Movements”\nIn recent years\, we have seen an increase in the incidences of radical protests about climate change in response to lackluster mitigation efforts worldwide. Historically\, the environmental movement as a whole has long been an issue space where women have held prominent leadership positions. However\, role congruity theory posits that women – due to being perceived as more passive and docile than men – may not be regarded as “proper” leaders of social movements\, especially when such movements use radical tactics. How does the interaction of protest tactics and leadership gendering affect support for the current climate movement? In this paper\, we report the results of a pilot survey experiment to address this question. Respondents were exposed to mock news stories about climate protests where they received one of four treatment conditions that varied the protest characteristics between combinations of radical/traditional tactics and women leadership/gender of leadership not specified. Respondents were then asked to report on their level of support for the movement\, level of support for the protest\, and the likelihood of the movement’s success. We also asked respondents to write in their most important reason for supporting the movement or not\, to which we applied basic topic modelling to extract key themes. Ultimately\, our pilot results show support for notion that radical protest tactics harm both support and perceptions of the movement\, but that gender of the protest leadership does not make a significant difference. We believe that the latter result is most likely due to weakness of the gender treatment in the survey experiment\, so future iterations of this work will seek to develop a stronger prime for this component of our analysis.\n\nKatie Nissen\, Ph.D. candidate in Political Science and Scientific Computing\nKatie is a current fourth year Joint PhD Candidate in Political Science and Scientific Computing. Her research is primarily about factors that influence climate change discourse and public opinion\, and her dissertation will focus on the effects of optimism and pessimism on climate attitudes.\n  \nRegister to attend this seminar
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-anna-halstenbach-and-katie-nissen/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240409T120000
DTEND;TZID=America/Detroit:20240409T130000
DTSTAMP:20240405T124240Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240405T124240Z
UID:10000675-1712664000-1712667600@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Jeffrey Hatch and Jiadong Chen
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public but we ask that all attendees register so that we can prepare properly. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \n  \nJeffrey Hatch: An introduction to the many-body basis set amelioration method\nModeling the interaction of subatomic particles in chemical species has become a routine part of modern chemical research as this analysis can be used to find a system’s energy\, thermodynamic properties and more. The algorithms that can accomplish this vary in their accuracy and computational cost\, with more accurate methods generally incurring more cost. Additionally\, the more subatomic particles present\, the more costly the calculation will be. A computationally intensive family of methods known as select configuration interaction methods are generally thought of as the most accurate and most computationally expensive family of methods. However\, due to their high cost\, it is requisite that we investigate mechanisms of diminishing the cost while maintaining accuracy. The nature of one such method\, incremental full configuration interaction (iFCI) lends itself to accurate extrapolations based on much cheaper levels of theory in smaller basis sets. This is known as the many-body basis set amelioration (MBBSA) method. The MBSSA method has be shown to reduce the cost of a given calculation by as much as 80% without loss in the accuracy of the calculation.\n\nJeffrey Hatch\, Ph.D. candidate in Chemistry and Scientific Computing\nJeffrey is in the Zimmerman group in the chemistry department. He is interested in using HPC methods to improve quantum chemical calculations especially in the configuration interaction realm of electronic structure calculations.\n\n\n\nRegister to attend this seminar\n\n\n\nJiadong Chen: High dimensional phase diagrams: Engineering relative stability in 4-dimensions\nSequential learning algorithms based on Bayesian optimization are routinely being deployed for materials stability optimization in high-parameter spaces. We anticipate these optimization methods would perform better if they were built upon stronger priors\, for example\, as derived from the fundamental thermodynamics underlying the equilibrium behavior of materials. Here\, we present a thermodynamics-based technique to optimize the relative stability of a materials in high-dimensional thermodynamic space\, based on a new derivation of a generalized high-dimensional Clausius Clapeyron relation. Using this thermodynamic infrastructure\, we design several pathways to enhance the relative acid stability of Mn-oxides versus its dissolved states for potential electrochemical catalyst application. We construct a 4-D Pourbaix diagram with pH\, redox potential E\, particle radius 1/R and a chemical potential μK as axis. By exploring the gradients of the high-dimensional phase boundaries\, we derive first-principles insights that nano-sizing (1/R) and certain doping ions (μK) can stabilize some metastable Mn-oxides polymorphs\, where 1/R decreases acid stability and μK increases it. Our high-dimensional thermodynamic framework is a general method to engineer relative stability in parameter spaces that leverage multiple forms of thermodynamic work.\n\nJiadong Chen\, Ph.D. candidate in Materials Science and Engineering and Scientific Computing\nJiadong Chen is a 5th year PhD in materials science and engineering department\, Wenhao Sun group\, focusing on use computational and data-driven methods to predict materials stability and synthesis recipes.\n  \nRegister to attend this seminar
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-jeffrey-hatch-and-jiadong-chen/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240312T120000
DTEND;TZID=America/Detroit:20240312T130000
DTSTAMP:20240220T232015Z
CREATED:20240220T232015Z
LAST-MODIFIED:20240220T232015Z
UID:10000674-1710244800-1710248400@micde.umich.edu
SUMMARY:Workshop / Seminar:MICDE Ph.D. Student Seminar: Hannah Van Wyk and Musawer Ahmad Saqif
DESCRIPTION:Hannah Van Wyk will present her talk: Using a hidden markov model to pinpoint the date of the primary case in a dengue outbreak in rural Ecuador.\nAn infectious disease outbreak investigation typically consists of retrospectively determining information regarding the outbreak such as the timing of the primary case (the first case of the outbreak\, whether detected or not) and transmission dynamics that occurred prior to the outbreak. However\, information on the primary case is often hard to obtain\, especially in scenarios where the disease has a high asymptomatic ratio. Using a hidden Markov model\, we estimate the most likely date of the primary case of a dengue outbreak in a small community in northern coastal Ecuador.\n*Bio*:\nHannah is a doctoral student in the Department of Epidemiology. Her research involves using mathematical models of infectious diseases to understand transmission dynamics. She has a background in mathematics and computer science at her undergraduate institution and a Master of Public Health in Epidemiology.\nMusawer Ahmad Saqif will present his talk: Fracture and Collapse Simulation of UHPC Structures.\nThis presentation delves into the advanced simulation techniques for understanding the fracture and collapse behaviors of ultra-high performance concrete (UHPC) structures. Leveraging finite element modeling and experimental validation\, the study elucidates the critical mechanical properties and failure mechanisms of UHPC under various conditions. Through a detailed investigation of microstructural characteristics and their impact on macroscopic performance\, the research provides valuable insights into optimizing the design and resilience of UHPC structures against extreme loading scenarios. The findings contribute significantly to the field of civil engineering by enhancing the predictive capabilities for the structural integrity and durability of UHPC infrastructures.\n*Bio*:\nM. A. Saqif is a fifth year PhD student in Civil Engineering and Scientific Computing at the Computational Structural Simulation Lab. His research interest lies in fracture and collapse simulation of concrete structures.\n*The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public.\nIf you have any questions\, please email micde-events@umich.edu.*
URL:https://micde.umich.edu/event/workshop-seminarmicde-ph-d-student-seminar-hannah-van-wyk-and-musawer-ahmad-saqif/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Phd Seminar,Scientific Computing,Seminar,Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240305T120000
DTEND;TZID=America/Detroit:20240305T123000
DTSTAMP:20240223T215755Z
CREATED:20240220T232014Z
LAST-MODIFIED:20240223T215755Z
UID:10000673-1709640000-1709641800@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Lingfeng Luo
DESCRIPTION:Please register to attend \nLingfeng Luo will present: Gradient Boosting-Based Discrete Failure Time Model for Selecting Time-Varying Effects and Interactions as a part of the MICDE PhD Student Seminar Series. \nThe MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that all attendees register in advance so that we can be prepared with lunch for all attendees. \nIf you have any questions\, please email micde-events@umich.edu. \nPlease register to attend
URL:https://micde.umich.edu/event/micde-ph-d-student-seminar-lingfeng-luo/
LOCATION:Duderstadt Center – 1180
CATEGORIES:Biostatistics,Phd Seminar,Scientific Computing,Seminar,Workshops
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231205T120000
DTEND;TZID=America/Detroit:20231205T130000
DTSTAMP:20231204T192114Z
CREATED:20230926T191303Z
LAST-MODIFIED:20231204T192114Z
UID:10000654-1701777600-1701781200@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Jeffrey Hatch
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nComputational Methods in Chemistry\nAbstract coming soon… \nJeffrey Hatch\, Ph.D. candidate in Chemistry and Scientific Computing \nBio coming soon… \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-jeffrey-hatch/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231128T120000
DTEND;TZID=America/Detroit:20231128T130000
DTSTAMP:20260522T152930Z
CREATED:20230914T150100Z
LAST-MODIFIED:20260522T152930Z
UID:10000641-1701172800-1701176400@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars 2023-2024: Guoer Liu
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nWhen Is Big Data Biased?\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nGuoer Liu\, Ph.D. candidate in Political Science and Scientific Computing\nGuoer Liu is a Ph.D. candidate in Political Science. Her dissertation project\, ‘‘From Oversight to Overlook’’ investigates how political determinants distort the technology infrastructure and create seemingly credible but inaccurate information to the public. \nAdvisors: Mary Gallagher\, Charles Shipan \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-guoer-liu/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231114T123000
DTEND;TZID=America/Detroit:20231114T130000
DTSTAMP:20231103T200940Z
CREATED:20230914T150100Z
LAST-MODIFIED:20231103T200940Z
UID:10000640-1699965000-1699966800@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars: Jamie Holber
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nActive Learning for Physics Informed Data Sampling and Construction of Free Energy Representations\nUsing automation technology to gather and disseminate information to the public is commonly viewed as a government-led effort to enhance oversight and address the principal-agent problem in bureaucracy. However\, focusing on the expansion of China’s automatic ambient air quality monitoring network in the last decade (2012-2022)\, I argue that technology is being utilized as a tool to emphasize optics but overlook the substantive problems. I illustrate the idea with multiple original georeferenced data sets on the automatic monitoring network\, pollution sources\, and satellite-derived vegetation density across time and space. I show that\, while the automation initiative has improved the data quality in some ways\, the undersupply of automatic monitoring stations\, over-represented clean locations\, and non-random missing pollution records continue to contribute to inaccurate air pollution information. As long as political incentives to manipulate information persist\, actors can mold technology that operates without human intervention to serve their own interests. \nJamie Holber\, Ph.D. candidate in Applied Physics and Scientific Computing \nJamie Holber is a PhD Candidate in Applied Physics and Scientific Computing working in the Computational Physics Group in the Mechanical Engineering Department. \nAdvisor: Krishna Garikipati \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-jamie-holber/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20231107T120000
DTEND;TZID=America/Detroit:20231107T130000
DTSTAMP:20231019T200916Z
CREATED:20230914T150100Z
LAST-MODIFIED:20231019T200916Z
UID:10000639-1699358400-1699362000@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminars: Bernardo Pacini & Srinivasan Arunachalam
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nGradient-Based Multidisciplinary Design Optimization for Propeller Design\nUrban air mobility (UAM) vehicles have taken form as advanced rotorcraft with sets of wings\, rotors\, canards\, and other appendages. Noise generation is an important technical barrier that must be addressed to prevent these vehicles from causing excessive disturbance to the communities they are intended to service. To understand the noise these vehicles generate\, and to develop designs that can minimize disturbance\, there is a need for analysis and optimization tools specifically for the conceptual design and sizing phase of urban air mobility vehicle development. Such tools must be computationally efficient to allow for the repeated analyses needed for design optimization. This presentation will review the work being carried out at the University of Michigan\, coupling aerodynamic\, structural\, and aeroacoustic disciplines within the multidisciplinary gradient-based design optimization framework OpenMDAO. While aerostructural optimization has been performed previously\, coupling with aeroacoustics is challenging given the requirement for time accurate simulations and the associated computational cost of such analyses. By leveraging multiple model fidelities and utilizing efficient gradient calculation techniques\, such as the adjoint method and algorithmic differentiation\, these disciplines can be formulated into an optimization framework that can be applied to UAM vehicle designs. This presentation will review the work completed to date\, including preliminary results\, and expand on the future goals of the project\, working towards a broader optimization framework for rotorcraft vehicle design optimization. \nBernardo Pacini\, Ph.D. candidate in Mechanical Engineering and Scientific Computing \nBernardo Pacini is a Ph.D. Candidate at the University of Michigan focusing his research on aerodynamic\, structural\, and aeroacoustic modeling for multidisciplinary design optimization of urban air mobility vehicles. He is a member of the Multidisciplinary Design Optimization Laboratory led by Professor Joaquim R. R. A. Martins and of the Computational Aerosciences Laboratory led by Professor Karthik Duraisamy. Bernardo’s work to date is on developing an aero-structural-acoustic analysis framework that can be implemented within the multidisciplinary design optimization process for rotorcraft and urban air mobility vehicle design. \nRegister to attend this seminar \nValidation of a multivariate non-Gaussian\, non-stationary wind pressure simulation model for performance-based wind engineering\nWith a growing interest in probabilistic performance assessments of building systems subjected to wind loads\, there is a demand for accurately representing building-specific wind loads\, considering their non-Gaussian and non-stationary features. While typical wind tunnel data collected for a set of discrete wind directions provide a single realization of stationary pressures\, there is currently no experimentally validated model for the stochastic simulation of non-Gaussian and non-stationary wind pressures that can be calibrated to wind tunnel datasets. Such a model is essential for simulating building aerodynamics\, especially the stochastic\, path-dependent responses associated with time-varying wind speed and direction experienced by a building during hurricane wind events. This talk will review a recently developed theoretical formulation for generating these stochastic pressures. Through carefully designed tests conducted at the University of Florida wind tunnel facility\, the formulation was extensively validated with respect to its ability to capture trends over time\, occurrences of peaks\, and time-varying frequency content. \nSrinivasan Arunachalam\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nSrinivasan Arunachalam is a PhD candidate in Civil and Environmental Engineering. His research interests lie in uncertainty quantification and understanding the inelastic behavior of wind-excited structures. He is excited about the algorithmic developments that enable efficient reliability assessments\, as well as the evolving insights into the physics of extreme responses and their implications for structural design. \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-bernardo-pacini-srinivasan-arunachalam/
LOCATION:2022 South Thayer Building
CATEGORIES:Computation,Computational Modeling,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Sessions,Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20230926T123000
DTEND;TZID=America/Detroit:20230926T130000
DTSTAMP:20230921T195259Z
CREATED:20230913T145952Z
LAST-MODIFIED:20230921T195259Z
UID:10000631-1695731400-1695733200@micde.umich.edu
SUMMARY:MICDE Ph.D. Student Seminar: Haowei Sun
DESCRIPTION:The MICDE PhD Student Seminar Series showcases the research of students in the Ph.D. in Scientific Computing. These events are open to the public\, but we ask that you register to attend the seminar. If you have any questions\, please email micde-events@umich.edu. \nRegister to attend this seminar \nTera City: Accurate and Efficient AV Safety Performance Evaluation\nThis talk is aiming at mitigating current simulation-based AV safety performance evaluation approaches. Tera City is composed of naturalistic driving environment construction and intelligent testing environment construction\, which provided accuracy and efficiency\, respectively. \nHaowei Sun\, Ph.D. candidate in Civil and Environmental Engineering and Scientific Computing \nHaowei Sun is a Ph.D. candidate at Civil Engineering\, Next Generation Transportation System Program. His research focus is mainly on the safety validation and verification of autonomous vehicles. \nRegister to attend this seminar
URL:https://micde.umich.edu/event/phd-seminar-haowei-sun/
LOCATION:2022 South Thayer Building
CATEGORIES:Civil and Environmental Engineering,Computation,Computational Science,Engineering,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,In Person,Interdisciplinary,Michigan Engineering,Phd Seminar,Prospective Graduate Students,Rackham,Science,Scientific Computing,Seminar,Talk
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END:VEVENT
END:VCALENDAR