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DTSTART;TZID=America/Detroit:20250318T120000
DTEND;TZID=America/Detroit:20250318T130000
DTSTAMP:20260618T185623
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:20250401T120000
DTEND;TZID=America/Detroit:20250401T130000
DTSTAMP:20260618T185623
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:20250408T113000
DTEND;TZID=America/Detroit:20250408T130000
DTSTAMP:20260618T185623
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:20250415T120000
DTEND;TZID=America/Detroit:20250415T133000
DTSTAMP:20260618T185623
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:20250422T120000
DTEND;TZID=America/Detroit:20250422T130000
DTSTAMP:20260618T185624
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/01/2025-04-22-Croft-Turner.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20250711T120000
DTEND;TZID=America/Detroit:20250711T130000
DTSTAMP:20260618T185624
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
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/07/2025-07-11.png
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