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SUMMARY:MICDE - Mechanical Engineering seminar: Phani Motamarri\, Indian Institute of Science\, Bangalore
DESCRIPTION:Bio: Phani Motamarri is an Assistant Professor in the Department of Computational and Data Sciences at the Indian Institute of Science\, Bengaluru\, where he leads the MATRIX Lab. He is an alumnus of the University of Michigan–Ann Arbor\, where he earned his PhD in Mechanical Engineering.\nHis research lies at the intersection of computational mechanics\, materials science\, numerical analysis\, and high-performance computing. His work focuses on developing mathematical techniques and hardware-aware algorithms for quantum modeling of materials\, with applications to structural and functional materials and multiscale modeling methodologies. He is also interested in machine learning frameworks for accelerating materials discovery and quantum computing\, particularly in the context of quantum-centric supercomputing. \nProf. Motamarri’s research contributions include advances in finite-element methods\, numerical analysis\, and large-scale scientific software development. He is one of the lead developers of DFT-FE\, an open-source\, massively parallel finite-element code for density functional theory calculations. He received the ACM Gordon Bell Prize in 2023 and was a finalist for the ACM Gordon Bell Prize in 2019. \nInexact yet Accurate: Unlocking Quantum Modeling of Materials at Scale through Approximation-Tolerant Algorithms\nAbstract:  Modern computing architectures increasingly rely on iterative solvers that employ reduced-precision computation and communication-reduction techniques to lower time-to-solution and improve scalability. However\, eigensolvers in scientific simulations have struggled to exploit such approximations without compromising accuracy. We present an eigensolver R-ChFSI\, a residual-based reformulation of Chebyshev Filtered Subspace Iteration (ChFSI) provably tolerant to inexact matrix–vector products. By expressing the Chebyshev recurrence in terms of residuals rather than eigenvector estimates\, R-ChFSI naturally accommodates multiple sources of approximation\, including reduced-precision arithmetic (FP32 and TF32) in the filtering step\, lossy compression with compression ratios exceeding 4x for inter-process communication\, and approximate inverses for generalized eigenproblems\, while preserving eigensolver robustness. Large-scale experiments on GPU accelerators are conducted using finite-element discretized generalized eigenproblems arising in Kohn–Sham density functional theory for quantum modeling of materials. The results demonstrate that R-ChFSI achieves eigen-residual norms orders of magnitude smaller than standard ChFSI under comparable inexactness\, while delivering substantial performance gains. This work provides a practical pathway toward approximation-tolerant eigensolvers enabling accurate and scalable simulations on modern computing architectures. \n\nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-phani-motamarri-iisc/
LOCATION:1311 EECS\, 1301 Beal Ave.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:College Of Engineering,Computational Science,Featured Events,Graduate Students,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/05/Phani-Motamarri.png
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260317T160000
DTEND;TZID=America/Detroit:20260317T170000
DTSTAMP:20260306T144640Z
CREATED:20260306T144640Z
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SUMMARY:Mathematics - MICDE - MCAIM joint colloquium: Peter Bosler\, Sandia National Laboratories
DESCRIPTION:Bio:  Dr. Bosler received his B.S. degree with Honors in Oceanography from the U.S. Naval Academy in 2002. In 2002-2007\, he served as an officer in the U.S. Navy with active duty service that included both surface warfare and meteorology/oceanography operational support. Upon completing his service\, he started graduate studies at the University of Michigan and received a Ph.D. degree in Applied and Interdisciplinary Mathematics in 2013. In 2014\, he received the John von Neumann Postdoctoral Fellowship at Sandia National Laboratories\, and thereafter\, he became a staff member in the Center for Computing Research at Sandia. His projects involve close coupling between numerical methods development\, data collection\, application science\, and high-performance computing. Recent projects focus on climate modeling and plasma physics. Dr. Bosler received the Department of Energy Early Career Award for Advanced Scientific Computing in 2022 and the Presidential Early Career Award for Science and Engineering in 2025. \nAccelerating Earth System Simulation\nAbstract: Providing high-quality “actionable information” for strategic risk analysis is amongst the primary goals of the U.S. Department of Energy’s Exascale Earth System Model (E3SM). The simulation speed required to generate high-quality localized predictions at seasonal-to-decadal time scales is very high. In this talk\, we highlight some algorithmic design decisions that combine new research with classical numerical methods to enable E3SM’s ultra-high resolution configuration to achieve exascale performance and win the inaugural Gordon Bell Prize for Climate in 2023. Our design strategies tailor mathematical methods to both the unique features of the application space and to the heterogeneous computing architectures of exascale supercomputers. Ultimately\, these efforts doubled the speed of the most computationally demanding component of E3SM\, its atmosphere model. We will also discuss new and ongoing research associated with opportunities afforded by these performance gains. \n  \n\n  \nThe MICDE 2025-26 Seminar Series is open to all. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/math-micde-mcaim-peter-bosler-sandia/
LOCATION:1360 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Climate and Space Sciences and Engineering,College Of Engineering,Featured Events,Mathematics,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20260129T140000
DTEND;TZID=America/Detroit:20260129T150000
DTSTAMP:20260522T151806Z
CREATED:20251125T210910Z
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UID:10000844-1769695200-1769698800@micde.umich.edu
SUMMARY:MICDE - Mechanical Engineering Seminar - Elif Ertekin\, University of Illinois Urbana-Champaign
DESCRIPTION:Bio: Elif Ertekin is an Andersen Faculty Scholar\, Associate Professor\, and Associate Head for Graduate Programs in the Mechanical Science and Engineering Department at the University of Illinois at Urbana-Champaign. She is a faculty affiliate of the National Center for Supercomputing Applications (NCSA) and the Materials Research Laboratory (MRL). Her research interests center on the theory and modeling of materials\, with an emphasis on probabilistic and stochastic methods. She focuses on developing a microscopic understanding of atomic and electronic scale processes in materials\, with applications areas in thermal transport\, energy conversion\, and defect chemistry. She received BS degrees in Mathematics and in Engineering Science and Mechanics from Penn State\, a PhD in Materials Science and Engineering from UC Berkeley\, and she carried out post-doctoral work at the Berkeley Nanoscience and Nanoengineering Institute and the Massachusetts Institute of Technology. She is an Associate Editor for the Journal of Applied Physics and a Divisional Associate Editor for\nPhysical Review Letters. \nPhysical Mechanisms or Learned Patterns? Reconciling First-Principles Models with Machine Learning for Predictive Materials\nPredictive materials simulation has long been rooted in first-principles descriptions of physical mechanisms\, grounded in quantum mechanics but limited by tractable length scales\, sampling challenges\, and the accuracy-cost tradeoff. Today\, machine-learning methods seek to transform materials science by revealing patterns in data extending beyond conventional modeling. My talk will explore how these two paradigms\, mechanistic simulation and data-driven learning\, can act synergistically to accelerate materials discovery and understanding. I will begin by outlining what first-principles simulations can currently achieve and where their limitations arise\, using examples from our work in thermoelectrics\, wide-band-gap semiconductors\, ion-transport materials\, and structural alloys. Building on this foundation\, I will show how machine-learning approaches\, when designed with materials-specific considerations such as symmetries and invariances\, can enhance traditional methods. Examples include symmetry-aware generative models for inorganic crystalline solids and machine-learning solutions to the many-body electronic-structure problem that rival high-accuracy quantum methods. Together\, these examples highlight how integrating mechanisms and patterns can help advance predictive materials simulations.\ \n\nThe MICDE 2025-26 Seminar Series is open to all. \nThis seminar is organized by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering. Prof. Ertekin will be hosted by Prof. Chenhui Shao\, Associate Professor of Mechanical Engineering. \nThis is an in-person event. This seminar will not be recorded! \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-seminar-elif-ertekin-uiuc/
LOCATION:Lurie Robert H. Engin. Ctr – Johnson Rooms (LEC 3213)
CATEGORIES:College Of Engineering,Featured Events,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/11/Elif-Ertekin.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20251209T114500
DTEND;TZID=America/Detroit:20251209T124500
DTSTAMP:20251208T171351Z
CREATED:20250926T143954Z
LAST-MODIFIED:20251208T171351Z
UID:10000841-1765280700-1765284300@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  \n\nImproving Slater Orbital Integration Accuracy through Prolate Spheroidal Coordinates\nThe core of electronic structure calculations is the integration of forces exerted on and by\nelectrons and nuclei in a system. Some of these interactions have forms which manifest in such a way that makes integration challenging depending on the choice of basis (specifically Slater Type Orbitals (STOs)). This difficulty lies in the fact that not all integrals have a known analytically integrable form when Slater functions are used as a basis. The Prolate Spheroidal coordinate system has only been applied to diatomic systems\, but offers an advantage in numerical integration accuracy over more generally applicable schemes. A third center is added in the PS coordinate grid in this work\, where we will note the challenges and steps taken to handle a third center. It is important to note that the addition of a third center is sufficient to solve all integrals required by the Hamiltonian under the Resolution of the Identity(RI) approximation. Analysis was performed using metrics which test the scheme directly (error values for integral matrix elements) and indirectly(applying integrals to Hartree-Fock(HF) and post-HF methods to get observables). The methods ability to accurately calculate 2-center properties allows for the use of larger basis sets which were previously unserviceable. \nAlexander Stark (Chemistry and Scientific Computing)\nThis is Alexander Stark\, he is in the Zimmerman group in the chemistry department\, his research involves refining different levels of wave-function theory as to improve the accuracy of predictions. \n\nMultiscale Modeling of Radical and Vibrational Pathways in Plasma-Assisted Ammonia Synthesis on Fe(110) and Ni(111)\nLow-temperature plasma (LTP)-assisted ammonia synthesis is a promising alternative to the Haber-Bosch process for decentralized\, renewable energy-driven production. Progress has been limited by an incomplete mechanistic understanding\, particularly the debated roles of vibrationally excited N2(g)\,ν and plasma-generated N · /H · radicals\, which may explain the unexpected insensitivity of catalyst performance across metals. We apply first-principles multiscale modeling—combining density functional theory (DFT) calculations and a packed-bed reactor microkinetic model—to disentangle these contributions to LTP-assisted NH3(g) synthesis over Fe(110) and Ni(111) catalysts. The model incorporates an experimentally derived vibrationally excited N2(g)\,ν distribution from a radiofrequency (RF) plasma source and accounts for their vibrational surface quenching. The model predicts that vibrational excitation enhances the dissociation of N2(g)\,ν on Ni but its impact on Fe is limited. Quenching of vibrationally excited N2(g)\,ν\ndue to collisions with the reactor walls and the catalyst surface does not significantly affect ammonia yields on either catalyst\, with less an an order of magnitude increase. In contrast\, Eley-Rideal reactions involving N · and H · radicals dominate ammonia formation\, bypassing the conventional rate-controlling steps of thermal catalysis on Fe and Ni materials. This mechanistic picture explains the experimentally observed insensitivity of ammonia production rates to metal catalyst identity and highlights the central role of radical chemistry in plasma-assisted ammonia synthesis. \nOluwatosin Ohiro (Chemical Engineering and Scientific Computing)\nOluwatosin earned his primary degree in petroleum and gas engineering and worked for several years as a reservoir engineer and oil asset planner. He is currently pursuing his PhD in the Chemical Engineering Department under the supervision of Prof. Bryan Goldsmith. His research focuses on the interface of computational materials science and heterogeneous catalysis. \n\nQuantifying the state of inflammation in invasive lobular breast cancer using a one-class logistic regression algorithm\nAfter invasive ductal cancer (IDC)\, invasive lobular cancer (ILC) is the second most diagnosed type of breast cancer. Given complexities with detection\, patients with ILC may be diagnosed at an advanced stage of disease\, presenting larger tumors and a higher metastasis incidence when compared to IDC. It is increasingly appreciated that the immune system plays a crucial role in both primary tumor and metastatic progression and is a complex balance of both innate and adaptive immune interactions. Critically\, the success of modern immunotherapies\, such as immune checkpoint blockade\, depends not only on the T cells on which they directly act\, but also the complicated and often contradictory influence of innate myeloid cells on the lymphoid compartment. Innate myeloid cells in the tumor microenvironment (TME) have the potential to be both pro- and anti-cancer and often present in a spectrum within the TME. The dynamic nature of these immune components makes understanding and interpreting the state of the immune system in the TME very difficult. Simple methods\, like quantifying tumor infiltrating lymphocytes (TILs) or tumor-associated macrophages (TAMs) do not account for the function of these cells\, which may be pro- or anti-tumor. We investigated the role of the immune system in the tumor microenvironment (TME) of ILC by developing a machine learning-based inflammation score (IS) that can quantify the complex state of the immune system within a primary tumor on a numerical scale from pro- to anti-inflammatory. We correlate the IS with overall survival and disease-free survival to set prognostic thresholds for immune dysregulation. \nKate Griffin (Biomedical Engineering and Scientific Computing)\nKate is a PhD Candidate in Biomedical Engineering in the Shea Lab. Her research involves engineering nanoparticles to reverse immunosuppression in metastatic breast cancer\, and using computational methods to understand immune dysregulation in the metastatic niche.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-7/
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
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DTSTART;TZID=America/Detroit:20251118T114500
DTEND;TZID=America/Detroit:20251118T124500
DTSTAMP:20251023T021817Z
CREATED:20250926T143953Z
LAST-MODIFIED:20251023T021817Z
UID:10000840-1763466300-1763469900@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\nTailored Ultrashort Pulse Bursts in a Gain-Managed Nonlinear Fiber Amplifier for Coherent 50fs Pulse Stacking at mJ Energies\nWe show a method of scaling gain-managed nonlinear amplifiers (GMNA) to mJ energies using feedback-driven scaling of pulse bursts that can be time-combined into a single 50fs output pulse using coherent pulse stacking.  \nLauren Cooper (Electrical Engineering and Scientific Computing)\nLauren Cooper is working on coherent pulse stacking of gain-managed nonlinear amplified pulse bursts for high power applications. She is being advised by Professor Almantas Galvanauskas in the Electrical Engineering department at the University of Michigan. \n\nLeveraging multipole models to measure rotation in time-dependent potentials\nMultipole expansion models are efficient and flexible methods by which to encode aspherical and time-dependent fluctuations in 3D functions of galactic densities and potentials. Historically these techniques have been used primary to perform orbit integration and N-body simulations. However\, it is becoming increasingly clear that the expansion series coefficients encode useful physical information that may be used to discover novel dynamics. In this talk\, I will outline my recent work using multipole expansion coefficient series\, including methods I have developed for measuring rotation in the quadrupole component and the discoveries multipole expansion has facilitated. \nNeil Ash (Astronomy and Scientific Computing)\nNeil is a 5th year graduate student in the Astronomy Department working with Professor Monica Valluri. His research interests include hydrodynamical simulations of cosmic structure formation and galactic dynamics\, with a special focus on the dark matter haloes and their interactions with the baryonic (stellar) galactic component. \n\nTracing Refractory Material in the Inner 10 AU of Protoplanetary Disks\nPlanets form in protoplanetary disks by building their cores from rocky/refractory material that drifts inward toward the central star\, establishing this material as the fundamental building blocks of all planets. Identifying the physical processes that regulate rocky material within the inner 10 AU during disk evolution is essential for understanding the formation of the observed diversity of planetary systems\, particularly for all rocky planets. In my PhD dissertation\, I study the content of rocky material in the inner regions of protoplanetary disks. I utilize spectroscopic observations across the entire electromagnetic spectrum\, using both ground-based and space telescopes\, to disclose how much rocky material reaches the inner disk and what its composition is. I have found (1) evidence for refractory depletion in the inner gas disk\, 2) connections between age and dust-trapping/planet-forming mechanisms with higher depletion values\, and 3) estimates of the impact of sublimation temperature and dust drifts on the composition of rocky material in the inner disk. Overall\, my work probes dust trapping and dust drift theories. \nMarbely Micolta (Astronomy and Scientific Computing)\nI’m a fifth-year Ph.D. student in Astronomy\, working with Prof. Nuria Calvet. I’m from Venezuela. My research aims to constrain the physical and chemical processes that regulate rocky (refractory) material\, the building blocks of planets\, in the inner 10AU of protoplanetary disks. I have developed a broad expertise in disk characterization\, using observations across the electromagnetic spectrum\, both from the ground and space telescopes.
URL:https://micde.umich.edu/event/workshop-seminarph-d-in-scientific-computing-seminar-series-6/
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/2025/09/2025-11-18-Cooper-Ash-Micolta.png
END:VEVENT
BEGIN:VEVENT
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
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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
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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
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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
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DTSTART;TZID=America/Detroit:20241107T180000
DTEND;TZID=America/Detroit:20241107T190000
DTSTAMP:20241030T170447Z
CREATED:20241029T230120Z
LAST-MODIFIED:20241030T170447Z
UID:10000787-1731002400-1731006000@micde.umich.edu
SUMMARY:Taking the Next Step: Graduate Studies in Computation/AI for Science and Engineering at U-M
DESCRIPTION:PhD in Scientific Computing director Eric Johnsen will speak about opportunities for undergraduate or master’s students seeking a graduate education in Computation and Artificial Intelligence for Science and Engineering at the University of Michigan. Food will be provided. Please register to attend. \nPlease register via the link: https://sessions.studentlife.umich.edu/p/track/12857 \nZoom option available after registering.
URL:https://micde.umich.edu/event/taking-the-next-step-2024/
LOCATION:GG Brown Laboratory – 2147
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Artificial Intelligence,Astronomy,Biology,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Science,Computational Social Science,computer science,computing,Earth And Environmental Sciences,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Epidemiology,Free,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Michigan Engineering,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scientific Computing,Statistics,Talk,Undergraduate,Undergraduate Students,Virtual,Workshop
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DTSTART;TZID=America/Detroit:20241001T150000
DTEND;TZID=America/Detroit:20241001T160000
DTSTAMP:20241011T124325Z
CREATED:20240925T142215Z
LAST-MODIFIED:20241011T124325Z
UID:10000772-1727794800-1727798400@micde.umich.edu
SUMMARY:MICDE/ME Seminar: Krishnan Mahesh\, Professor\, University of Michigan NAME
DESCRIPTION:Bio:  Krishnan Mahesh is a Richard B. Couch Professor of Naval Architecture and Marine Engineering at the University of Michigan. His research focuses on the simulation of complex\, multi-physics turbulent flows. Mahesh received his Bachelor’s degree in Mechanical Engineering from the Indian Institute of Technology (Mumbai)\, and in 1996 obtained his Ph.D. degree in Mechanical Engineering from Stanford University. He is a 2018 Fulbright-Nehru Specialist\, a Fellow of the American Physical Society\, an Associate Fellow of the American Institute of Aeronautics and Astronautics\, and a Fellow of the Minnesota Supercomputing Institute. Mahesh is a recipient of the CAREER Award from the National Science Foundation and the Francois N. Frenkiel Award from the American Physical Society. He has received the Taylor Award for Distinguished Research\, McKnight Presidential Fellowship\, Guillermo E. Borja Award\, and McKnight Land-Grant Professorship from the University of Minnesota. \nLarge Eddy Simulation of Turbulent Cavitating Flows\nCavitation is a complex multi-scale phenomenon that has implications from intense sound production to erosion in engineering applications. This talk will discuss our efforts at developing the large-eddy simulation capability for the simulation of turbulent cavitating flows. LES of cavitation is challenged by phase change modeling\, acoustic stiffness\, sharp multiphase fronts\, strong compressibility effects\, consistent accounting of nuclei\, broadband turbulence and subgrid effects. \nLES of partial cavitation will be discussed under the same conditions as experiments in a sharp wedge configuration.  Physical mechanisms of cavity transition observed in the experiments\, i.e.\, re-entrant jet and bubbly shock waves\, are both captured in the LES over their respective regimes. Vapor volume fraction data obtained from the LES will be quantitatively compared to X-ray densitometry\, and the results will be discussed. Cavitation nuclei are likely to be introduced through the free-stream as well as at solid surfaces. We will present a novel approach based on Gibbs free energy minimization to predict nuclei concentrations. The results from the proposed work will be applied to account for dissolved gas content in CSM measurements and predict several decades of experimentally observed trends in nuclei concentrations. Cavitating flows possess a range of vapor length scales ranging from tiny vapor bubbles to large vapor pockets. We will discuss a compressible hybrid model to capture both sub-grid vapor nuclei and massive sheet cavity dynamics. Finally\, physical aspects of inception due to the interaction of a counter–rotating vortex pair generated behind a pair of hydrofoils will be presented. \n\n  \nThe MICDE Fall 2025 Seminar Series is open to all. University of Michigan faculty and students. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/micde-me-seminar-krishnan-mahesh-professor-university-of-michigan-name/
LOCATION:2150 H.H. Dow\, 2300 Hayward St\, Ann Arbor\, 48109\, United States
CATEGORIES:Computational Science,Engineering,Featured Events,Free,Mechanical Engineering,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Naval Architecture and Marine Engineering
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X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=2150 H.H. Dow 2300 Hayward St Ann Arbor 48109 United States;X-APPLE-RADIUS=500;X-TITLE=2300 Hayward St:geo:-83.7154247,42.2929214
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20240419T110000
DTEND;TZID=America/Detroit:20240419T120000
DTSTAMP:20240412T140752Z
CREATED:20240412T011911Z
LAST-MODIFIED:20240412T140752Z
UID:10000680-1713524400-1713528000@micde.umich.edu
SUMMARY:MICDE Fellowships Information Session
DESCRIPTION:Applications for the $4\,500 2024-2025 MICDE Graduate Fellowships will open May 1\, 2024. Please join this Zoom session to learn more about the fellowships and how to submit a great application! \nThese fellowships are sponsored by the Michigan Institute for Computational Discovery & Engineering. For more information\, see https://live-umor-micde.pantheonsite.io/academic-programs/fellowships/.
URL:https://micde.umich.edu/event/livestream-virtualmicde-fellowships-information-session/
LOCATION:Zoom Event
CATEGORIES:Aerospace Engineering,Ai In Science And Engineering,Astronomy,big data,Biomedical Engineering,Biosciences,Biostatistics,Chemical Engineering,Chemistry,Civil and Environmental Engineering,Climate and Space Sciences and Engineering,College Of Engineering,Complex Systems,Computation,Computational Modeling,Computational Science,Computational Social Science,computer science,Data Science,Earth And Environmental Sciences,Ecology,Ecology And Evolutionary Biology,Economics,Education,Electrical And Computer Engineering,Electrical Engineering and Computer Science,Engineering,Engineering Academic Calendar,Epidemiology,Evolutionary Biology,Fellowship,Free,Funding,Generative Ai,Graduate,Graduate and Professional Students,Graduate School,Graduate Students,Health Data,High Performance Computing,Industrial and Operations Engineering,Interdisciplinary,Kinesiology,Life Science,Lsaresearch,Machine Learning,Materials Science,Mathematics,Mechanical Engineering,Medicine,Micde,Natural Language Processing,Natural Sciences,Naval Architecture and Marine Engineering,Neuroscience,Nuclear Engineering and Radiological Sciences,parallel computing,Pharmacy,Physics,Politics,Prospective Graduate Students,Psychology,Public Health,Public Policy,Rackham,Research,Robotics,Scholarship,Science,Scientific Computing,Sciml,Sociology,Statistics,Virtual,Webcast,Workshops
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DTSTART;TZID=America/Detroit:20231002T160000
DTEND;TZID=America/Detroit:20231002T170000
DTSTAMP:20231013T144409Z
CREATED:20230913T145953Z
LAST-MODIFIED:20231013T144409Z
UID:10000632-1696262400-1696266000@micde.umich.edu
SUMMARY:MICDE / ME Seminar:  Olivier Desjardins\, Professor of Mechanical and Aerospace Engineering at Cornell University
DESCRIPTION:Bio: Olivier Desjardins is a Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University. He joined the Cornell MAE faculty in July 2011. Prior to that\, he was on the Mechanical Engineering faculty at the University of Colorado at Boulder. He received a Master of Science in Aeronautics and Astronautics from ENSAE (Supaero) in Toulouse\, France\, in 2004. The same year\, he received a Master of Science in Mechanical Engineering from Stanford University\, then in 2008 he obtained a Ph.D. in Mechanical Engineering from Stanford University. He received an NSF CAREER award in 2014 to work on turbulence modeling around liquid-gas interfaces\, and he was presented with the Junior Award from the International Conference on Multiphase Flow in 2016. \nResearch Interests: Prof. Desjardins’ research focuses on large-scale numerical modeling of turbulent reacting multiphase flows with industrial application. Using world-class parallel computers\, his group develops numerical methods and models to investigate the multi-scale and multi-physics fluid mechanics problems that arise in a range of engineering devices\, such as combustors or biomass reactors. \nHigh-fidelity computational techniques such as large-eddy simulations and direct numerical simulations are at the heart of Dr. Desjardins’ research. By enabling the exploration of complex non-linear flow physics from first principles\, these techniques have the potential to guide the development of highly optimized energy and propulsion systems. \nMulti-scale modeling of topology change in multiphase flow simulations\nLiquid atomization and spray formation are ubiquitous processes in nature as well as engineered system. Predicting droplet size distributions from first principle simulations presents a fantastic challenge due to the wide range of scales involved in topology change. In this talk\, we present new developments to the geometric volume of fluid method that enable the tracking of sub-grid scale interfacial features. By reconstructing the interface with multiple planar surfaces or with paraboloid surfaces\, we show that ligaments and sheets can be represented accurately independently of mesh resolution while preserving exact conservation\, good computational efficiency\, and easy integration with finite-volume-based flow solvers. A consequence of such strategies is that lack of mesh resolution no longer induces topology change\, which then needs to be reintroduced explicitly using physics-based models. We discuss various flavors of such models in the context of the break-up of thin liquid films\, a common feature in aerodynamic liquid atomization. \n  \n\n  \nThe MICDE Fall 2023 Seminar Series is open to all. University of Michigan faculty and students interested in predicting and explaining the properties of materials using computer simulation are encouraged to attend. \nThis seminar is cohosted by the Michigan Institute for Computational Discovery & Engineering (MICDE) and the Department of Mechanical Engineering (ME). Prof. Desjardins will be hosted by Dr. Jesse Capecelatro\, Associate Professor of Mechanical and Aerospace Engineering. \nThis is an in-person event. \nGraduate Certificate in Computational Discovery and Engineering\, and MICDE fellows\, please use this form to record your attendance. \nQuestions? Email MICDE-events@umich.edu
URL:https://micde.umich.edu/event/workshop-seminarmicde-me-seminar-olivier-desjardins/
LOCATION:1109 FXB\, 1320 Beal Ave.\, Ann Arbor\, MI\, United States
CATEGORIES:Aerospace Engineering,College Of Engineering,Mechanical Engineering,Micde Seminar,MICDE Seminar Series
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