I am a Postdoctoral Research Associate at the Aerospace Computational Design Lab (ACDL), where I work under the supervision of Professor Karen Willcox. My research program is focused on computational methods and numerical analysis for control, optimization, design and uncertainty quantification of large-scale dynamical systems. To enable—or speed-up—these computationally expensive tasks, I am interested in developing new methods and algorithms that use reduced-order surrogate models. With an increased availablilty of data available, I am interested in integrating information from data into decades-old, accurate, first-principles computational models.

You can find papers and citations here, and on Google Scholar and ResearchGate. My professional profile is at LinkedIn. I have a persistent digital identifier as my ORCiD profile and my peer-reviewing service profile is at Publons.

- Reduced-order modeling: data-driven and physics-based
- Optimizaton, control, design for large-scale systems (under uncertainty)
- Uncertainty quantification
- System Identification
- Partial differential equations (e.g., thermal and reactive flows)

July 22-27: I will present 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.

02/13/2018: Our paper Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation (with B. Peherstorfer and K. Willcox) got accepted in SIAM/ASA Journal of Uncertainty Quantification.

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.

12/05/2017: A preprint of the paper Conditional-Value-at-Risk estimation via Reduced-Order Models with Timur Takhtaganov (Rice), Matthias Heinkenschloss (Rice) and Karen Willcox (MIT) is now posted.

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.

10/30/2017: A preprint of the paper Multifidelity probability estimation via fusion of estimators with Alexandre Marques (MIT), Benjamin Peherstorfer (Wisconsin), Umberto Villa (UT Austin) and Karen Willcox (MIT) is now posted.

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.