I am broadly interested in computational methods and numerical analysis for control, optimization, design and uncertainty quantification of complex and large-scale systems . I work on using reduced-order models in the context of multifidelity and data-driven modeling, optimization and control, uncertainty quantification, reliability-based design, and design under uncertainty. More information on my CV.
Department of Mechanical and Aerospace Engineering
at the University of California San Diego
Jacobs Hall (EBU1) | Room 3313
9500 Gilman Drive | La Jolla | CA 92093-0411
AffiliationsCenter for Extreme Events Research (CEER)
Center for Computational Mathematics (CCoM)
Graduate Program in Computational Science, Mathematics and Engineering
09/30 - 10/04/2019: At the ENUMATH 2019 conference, I will present recent work on Lifting transformations and model reduction in MS31 on Monday September 30 at 1:30PM. I will also present Reduced order models for risk measure estimation in robust design at 11:05AM on Thursday October 3rd in MS18.
08/13/2019: Our paper "Learning physics-based reduced-order models for a single-injector combustion process" (with Renee Swischuk, Cheng Huang, and Karen Willcox) is now posted at arXiv:1908.03620 and Oden Institute Report 19-13.
07/29/2019: Our paper Balanced truncation model reduction for lifted nonlinear systems (with Karen Willcox) is now posted on arxiv, see arXiv:1907.12084.
07/28 - 08/01/2019: I'll attend the 15th U.S. National Congress on Computational Mechanics in Austin, TX and will be presenting Multifidelity Estimation of Risk Measures in Robust Design on July 31 from 3:40pm-4:00pm in MS#205 Multilevel/Multifidelity Strategies for Uncertainty Quantification.
Two papers that I co-authored are on the most-cited list of SIAM Journal of Uncertainty Quantification (accessed 06/17/2019), see Conditional-Value-at-Risk Estimation via Reduced-Order Models (with Matthias Heinkenschloss, Timur Takhtaganov, Karen Willcox) and Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation (with Benjamin Peherstorfer, Karen Willcox).
06/17/2019: Our conference paper Transform & Learn: A data-driven approach to nonlinear model reduction. (with Elizabeth Qian, Alexandre Marques and Karen Willcox) appeared in the proceedings of the AIAA Aviation 2019 Forum. Software for this publication available under https://github.com/elizqian/transform-and-learn and we have also made a more general operator inference code available at https://github.com/elizqian/operator-inference .
05/06/2019: Our paper Multifidelity probability estimation via fusion of estimators (with Alexandre Marques, Umberto Villa, Benjamin Peherstorfer and Karen Willcox) is now published at the Journal of Computational Physics, link.
04/23/2019: We posted a paper on Adaptive reduced-order model construction for conditional value-at-risk estimation (with Matthias Heinkenschloss and Timur Takhtaganov).
04/22/2019: Our paper Nonlinear Model Order Reduction via Lifting Transformations and Proper Orthogonal Decomposition (with Karen Willcox) appeared online at AIAA Journal, link.
01/29/2019: We posted a paper on Information reuse for importance sampling in reliability-based design optimization (with Anirban Chaudhuri and Karen Willcox).
12/04/2018: After 3.5 years of review, our patent finally got granted: US10145576B2: System and method for controlling operations of air-conditioning system.
04/04 - 04/05/2019: I attended the East Coast Optimization Meeting 2019 at George Mason University and presenting recent results on conditional-value-at-risk estimation via reduced models.
02/25 - 03/01/2019: I attended the SIAM CSE 2019 conference. There, together with Dr. Kevin Carlberg, we are organized the minisymposium MS343: Data-augmented Reduced-order Modeling: Operator Learning and Closure/error Modeling. I also gave a talk about Lifting Nonlinear Systems: More Structure, More Opportunities for ROM? at MS60 organized by Troy Butler and Steve Matthis.
11/16/2018: I presented work on "Lifting transformations for dynamical systems and model reduction" as part of the Kolchin seminar at the City University of New York (CUNY)".
11/06/2018: I gave a talk about "Nonlinear model reduction for complex systems" at the University of Washington Mechanical Engineering Graduate seminar.
10/23/2018: Our paper Conditional-Value-at-Risk Estimation via Reduced-Order Models (with Matthias Heinkenschloss, Timur Takhtaganov, Karen Willcox) just appeared online at SIAM/ASA Journal of Uncertainty Quantification.
07/27/2018: I presented at WCCM 2018 conference about "Stabilization of reduced-order flow models through learning-based closure modeling".
After three years, our patent finally got granted on May 22, 2018: US9976765B2: System and method for controlling operations of air-conditioning system.
05/30 – 06/01: Karen Willcox organized a workshop on Data to Decisions: Computational Methods for Design of Next-Generation Engineered Systems Workshop. where I presented recent work.
04/23/2018: I gave a talk at the Tufts Computational and Applied Math Seminar about "Conditional-Value-at-Risk Estimation with Reduced-Order Models".
04/10-13/2018: I presented at the MoRePaS IV conference (Model Reduction of Paramatrized Systems) in Nantes, France.
03/15/2018: Our paper System identification via CUR-factored Hankel approximation (with Alex A. Gorodetsky) appeared online in SIAM Journal of Scientific Computing.
03/6-9/2018: The workshop Reducing Dimensions and Cost for UQ in Complex Systems was a great opportunity to connect with other researchers, and I am happy that I could present recent results on Conditional-Value-at-Risk estimation there.
03/02/2018: I presented work on "Conditional-Value-at-Risk Estimation with Reduced-Order Models" at our in-house Aerospace Computational Design Lab (ACDL) seminar series.
02/03/2018: I gave a colloquium talk on "Reduced-order models for data-driven modeling and uncertainty quantification" at the Department of Mathematics at Dartmouth College, Hanover, NH.
11/21/2017: I gave a presentation about "Model reduction for uncertainty quantification of high-dimensional systems" at the Department of Mathematics at the Johannes Gutenberg University Mainz.
10/9-13/2017, I visited Professor Matthias Heinkenschloss at Rice University to work on efficient computation of risk measures in optimization.
07/10/2017: During the SIAM Conference on Control and its Applications in Pittsburgh I presented work on "Data-Driven Reduced-Order Models for Control of PDEs with Uncertain Parameters".
06/26/2017: I presented work on "Stabilization of reduced-order flow models through learning-based closure modeling" at the Conference on Classical and Geophysical Fluid Dynamics: Modeling, Reduction and Simulation at Virginia Tech.
05/23/17: At the SIAM Optimization conference in Vancouver, I presented our work on "Data-Driven Model Reduction via CUR-Factored Hankel Approximation".
04/18/2017: I gave a talk at the Sibley School of Mechanical and Aerospace Engineering at Cornell about "Exploiting Low-Dimensional Structures for Sensing and Control of Fluids via Data-Driven Reduced-Order Modeling".
04/03/17: We organized a minisymposium on "Uncertainty Quantification and Model Inadequacy in Combustion Simulations" at the 2017 SIAM International Conference on Numerical Combustion (with Todd Oliver). There, I presented "Multifidelity Failure Probability Estimation in Combustion Modeling".
03/30-31/17: I visited Professor Karthik Duraisamy at the University of Michigan.
03/17/17: I gave a presentation at the Department of Mathematics Colloquium at Virginia Tech.
03/15/17: I gave a talk on "Data-driven low-dimensional modeling for analysis and decision-making" at Sandia National Laboratories in Livermore, CA.
03/02/2017 I presented our work on "Multifidelity Computation of Failure Probabilities" at the SIAM CSE 2017 in Atlanta, GA.
02/28/2017 We co-organized a minisymposium on "Model Order Reduction: Perspectives from Junior Researchers" at SIAM CSE 2017 (with Alessandro Alla ).
02/15/2017: I gave a presentation about "Exploiting low-dimensional structures for sensing and control of fluids via data-driven reduced-order modeling at the "Computational Science Seminar", Department of Mathematics, University of Massachusetts Dartmouth, February 15, 2017.
02/02/2017: I presented our work on "Data-driven modeling for control of systems with time-varying and uncertain parameters" at the workshop on "Data-Driven Methods for Reduced-Order Modeling and Stochastic Partial Differential Equations" at the Banff International Research Station in Canada.
Jan 16-20,2017: I visited Professor Matthias Heinkenschloss at Rice University to work on risk measure estimation and computation.