I am a Research Assistant Professor of Electrical and Systems Engeneering (ESE) at Washington University in St. Louis, and a member of the Computational Imaging Science Laboratory led by Professor Anastasio.
Prior to joining Washington University, I was a Research Associate at The Institute for Computational Engineering and Sciences (ICES) of The University of Texas at Austin (March 2015-July 2018), working with Prof. Omar Ghattas on scalable numerical methods for the solution of Bayesian inverse problems, uncertainty quantification and propagation, optimal experimental design, and optimization under uncertainty.
I completed my postdoctoral training at the Center for Applied Scientific Computing (CASC) of Lawrence Livermore National Laboratory (LLNL) (February 2013 - February 2015), working with Dr. Panayot Vassilevski on algebraic multigrid and numerical upscaling techniques with applications to flow in porous media.
In December 2012, I obtained my Ph.D. in Mathematics with specialization in Computational Mathematics (high performance computing, computational fluid dynamics, image processing, inverse problems, and numerical analysis) from Emory University, with Prof. Alessandro Veneziani (Dept. of Mathematics and Computer Science) serving as my principal advisor.
- Feb 28: I’ll present my work on scalable algorithms for Bayesian Optimal Experimental Design at the 2019 SIAM CSE Conference in Spokane, WA.
- Feb 28: I’m chairing a minisymposium on Bayesian Optimal Experimental Design at the 2019 SIAM CSE Conference in Spokane, WA.
- Jan 28: O. Ghattas, Y. Marzouk, M. Parno, N. Petra, G. Stadler, and I share our gratifying experience in organizing and teaching the 2018 Gene Golub Summer School as a SIAM news article.
- Jan 28: I’m giving a seminar in the Math Department at WAshU on Learning from data through the lens of mathematical models
- Jan 24: I’m giving a seminar in my department on Large Scale Inverse Problems and Uncertainty Quantification: Computational Tools and Imaging Applications
- Jan 14: I’ll be teaching Computational Methods for Imaging Science, one of the core curriculum courses in the Imaging Science Ph.D. program at WashU.
- Dec 12: hIPPYlib 2.2.0 has been released! It is now available as a pip package.
- Oct 23: The hIPPYlib project has been published in the Journal of Open Source Software [DOI].
- Aug 1: I joined the School of Engineering and Applied Sciences at Washington University as Research Assistant Professor
- July 18: hIPPYlib 2.1.0 has been released!
- June 30: The 2018 G2S3 was a blast! It was a pleasure and an honor teaching inverse problems to 44 talented students from all over the world. Thank you!
- June 17: I’ll be teaching inverse problems at the 2018 Gene Golub Summer School G2S3
- June 15: hIPPYlib 2.0.0 has been released!
- May 16: hIPPYlib 1.6.0 has been released!
- Apr 13: New paper uploaded: Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty
- Jan 25: Application deadline for the 2018 Gene Golub SIAM Summer School on Inverse Problems: Systematic Integration of Data with Models under Uncertainty is approaching (Feb 1).
- Jan 24: hIPPYlib 1.5.0 has been released!
- Jan 9: I was invited to join the editorial board of Numerical Linear Algebra with Applications.
- Jan 9: I am organing a minisymposium on Model Inadequacy at SIAM UQ 18.
- Jan 9: I will be presenting my work on Optimal Experimental Design at SIAM UQ 18.
- Nov 11: Applications are now open for the 2018 Gene Golub SIAM Summer School on Inverse Problems: Systematic Integration of Data with Models under Uncertainty.
- Nov 11: hIPPYlib 1.4.0 has been released!
- Oct 30: New paper submitted: Multifidelity probability estimation via fusion of estimators.
- July 20: I’m co-organizing the 2018 Gene Golub SIAM Summer School; early announcement flier.
- June 28: hIPPYlib 1.3.0 was released!