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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
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DTSTART;TZID=America/Detroit:20260317T160000
DTEND;TZID=America/Detroit:20260317T170000
DTSTAMP:20260306T144640Z
CREATED:20260306T144640Z
LAST-MODIFIED: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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DTSTART;TZID=America/Detroit:20260529T110000
DTEND;TZID=America/Detroit:20260529T120000
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CREATED:20260514T175620Z
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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
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DTSTART;TZID=America/Detroit:20260902T090000
DTEND;TZID=America/Detroit:20260902T100000
DTSTAMP:20260828T150121Z
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SUMMARY:MICDE - LANL Michigan SPARC Seminar: Building AI Systems for Scientific Discovery
DESCRIPTION:Mike Grosskopf\nBio: Mike Grosskopf is a scientist in the Statistical Sciences Group (CAI-4) at Los Alamos National Laboratory (LANL). He holds a Ph.D. in Statistics from Simon Fraser University. Prior to his Ph.D. he worked as a research assistant at the University of Michigan with R. Paul Drake and Carolyn Kuranz in the AOSS (now CLASP) Department. His current research combines statistical machine learning\, scientific computing\, and artificial intelligence\, with a recent focus on developing reliable AI agents that accelerate scientific research. \nURSA – Using agentic AI to accelerate science\nAbstract: Agentic AI and coding agents are everywhere in life and the URSA team at LANL are adding to that in the scientific discovery domain. Our approach to agentic AI is designed around the idea that humans are at their best when thinking\, generating creative ideas\, asking questions\, suggesting solutions\, vetoing bad ideas and understanding results. We also want to develop agents that can take advantage of increasingly powerful AI to answer increasingly abstract questions and quickly implement prototypes of big ideas. The core elements of URSA will be presented which include agents for hypothesizing\, planning\, execution\, simulation management\, and multi-agent coordinated systems. Results of doing so on complex scientific discovery and R&D tasks will be discussed to demonstrate the capabilities of these tools. \n  \nAlex Wadell\nBio: Alex Wadell is an AI-for-science postdoctoral researcher at LANL. He holds a Ph.D. in Mechanical Engineering from the University of Michigan. His research focuses on foundation models and AI agents for scientific discovery. \nAugmenting AI Agents with SciFMs for Design & Discovery\nAbstract: Scientific Foundation Models (SciFMs) are powerful tools for prediction\, simulation\, and design\, but their impact depends on whether scientists and AI agents can use them effectively in real-world workflows. The talk will explore how SciFMs can be connected to AI agents through tool-based interfaces\, with a focus on programmatic tool calling and the practical challenges of incorporating SciFMs into agentic design loops. Two examples will be presented: molecular discovery with MIST and perturbed-layer interface design with JANUS. In both cases\, agents used SciFM predictions to construct task-specific optimization workflows and propose candidate designs. Along with this Nomad\, the underlying framework used to integrate both SciFMs into an agentic harness\, will be introduced and the steps required to connect additional models will be described.
URL:https://micde.umich.edu/event/lanl-michigan-sparc-building-ai-systems-for-scientific-discovery/
LOCATION:McDivitt Conference Room\, FXB 1044\, 1320 Beal Ave\, Annn Arbor\, MI\, 48109
CATEGORIES:Aerospace,Aerospace Engineering,College Of Engineering,Computational Science,Featured Events,Graduate Students,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Seminar
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DTSTART;TZID=America/Detroit:20260903T153000
DTEND;TZID=America/Detroit:20260903T170000
DTSTAMP:20260827T203006Z
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SUMMARY:LANL Michigan SPARC - MICDE Joint Seminar: Christopher Lane\, Los Alamos National Laboratory
DESCRIPTION:Bio: Christopher Lane received his Ph.D. in Physics from Northeastern University in 2019. In the same year\, he joined Los Alamos National Laboratory as a Postdoctoral Research Associate in the Quantum and Condensed Matter Physics Group (T-4) of the Theoretical Division. In 2020\, he became a Director’s Postdoctoral Fellow\, and in 2021 he was converted to staff. Lane is a recipient of the LDRD Early Career Research Award. His expertise includes first-principle quantum simulations and ab initio-based many-body perturbation theory calculations with a focus on modeling the electronic structure and spectroscopy of correlated d- and f-electron materials\, 2D thin films\, and their heterostructures. \nIdentifying Topological Superconductivity for Qubit Platforms \nAbstract: With our entrance into the noisy intermediate-scale quantum (NISQ) era in just the last few years\, greater focus has been placed on quantum error mitigation to enable sustainable quantum supremacy. This ever-growing issue stems from the short coherence times plaguing current qubit platforms\, requiring ever more overhead generated by error correction. To remedy this\, Majorana fermion modes have been proposed as a class of topologically protected qubits that are immune to conventional decoherence sources. Topological superconductors are believed to host such exotic quasiparticles. So far\, very few material realizations have been theoretically predicted\, let alone experimentally verified. In this talk\, I will present some of our recent efforts developing a first-principles-based methodology [1\,2] to identify topological superconductivity across a broad class of quantum materials. Specifically\, I will discuss results in the two-dimensional transition metal dichalcogenide family of materials that reveal a variety of topologically trivial and non-trivial superconducting states [1]. \n[1] Christopher Lane and Jian-Xin Zhu. Phys. Rev. Materials 6\, 094001 (2022).\n[2] Christopher Lane. Phys. Rev. B 113\, 144508 (2026) \n 
URL:https://micde.umich.edu/event/christopher-lane-lanl-seminar/
LOCATION:GC 4425\, 3520 Green Court\, Ann Arbor\, 48105\, United States
CATEGORIES:Aerospace,Aerospace Engineering,College Of Engineering,Computational Science,Featured Events,Graduate Students,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Seminar
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2026/08/Chris-Lane.png
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DTSTART;TZID=America/Detroit:20261002T150000
DTEND;TZID=America/Detroit:20261002T160000
DTSTAMP:20260817T165002Z
CREATED:20260817T165002Z
LAST-MODIFIED:20260817T165002Z
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SUMMARY:MICDE - AIM Joint Seminar: Mitchell Luskin\, University of Minnesota
DESCRIPTION:Bio: Mitchell Luskin is a Mathematics professor at the University of Minnesota’s School of Mathematics. He develops mathematical models and computational methods with applications to physics and mechanics. His current research focuses on quantum materials\, machine learning\, and data-enabled modeling. \nLuskin’s early work proposed and analyzed finite-difference and finite-element methods for fluid dynamics\, normal modes of the oceans\, neutron transport\, and viscoelasticity. Later work developed methods for liquid crystal defects and for materials with microstructure. More recent work formulated atomistic-to-continuum coupling and accelerated molecular dynamics methods \n  \nResearch Interests: \n\nNumerical analysis\nScientific computing\nApplied mathematics\nComputational physics\n\n\nTitle and abstract will be published soon. \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/mitchell-luskin-uminnesota/
LOCATION:1084 East Hall\, 530 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:College Of Engineering,Computational Science,Featured Events,Graduate Students,Mathematics,Mechanical Engineering,Micde,Micde Seminar,MICDE Seminar Series,Michigan Engineering,Seminar
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