email@example.com Assistant Computational Scientist
Mathematics and Computer Science Division
Argonne National Laboratory.
Research Assistant Professor
Department of Applied Mathematics
Illinois Institute of Technology, Chicago.
I am an Assistant Computational Scientist at the Mathematics and Computer Science division (MCS) at Argonne National Laboratory. Previously, I was the 2019 Margaret Butler Postdoctoral Fellow at Argonne National Laboratory and obtained my Ph.D. in Mechanical & Aerospace Engineering from Oklahoma State University. My interests are scientific machine learning, stochastic processes, high performance computing with applications to engineering, geoscience, plasma physics. An updated list of publications can be found on my Google Scholar profile and some of my software contributions can be found on Github.
If you're interested in a high-level overview of some of my research, check out these recordings of recent talks , , , . If you are a student interested in an internship at Argonne along the lines of my research interests - please email me.
Starting July 2023, I will be an Assistant Professor in the Department of Information Science and Technology (IST) at Pennsylvania State University. I will also be jointly appointed at Argonne National Laboratory (Argonne) as a faculty scientist. I have several fully funded PhD positions in the Interdisciplinary Scientific Computing Laboratory, starting Fall 2023. Please contact me if you are interested. Note - applicants must apply online (deadline December 15) to the IST graduate program here.
In addition to the team at Penn State, the group will also be composed of postdoctoral fellows, graduate, and undergraduate students at Argonne and allow for research at the intersection of academia and National Labs. Successful applicants will have a unique PhD experience with access to Argonne's state-of-the-art supercomputing resources and the ability to work on large-scale research projects of strategic importance.
Alec's paper on building stable neural ordinary differential equations for chaotic dynamical systems is accepted in the Journal of Computational Physics! Congratulations to Alec and our co-authors. An arxiv preprint is available here.
Our work on deep-learning based surrogate modeling for internal combustion engine simulations is awarded the best paper in ASME Internal Combustion Engine Fall Conference, 2021. This was work in collaboration with Sudeepta Mondal, Gina Magnotti, Bethany Lusch, and Roberto Torelli.
Our minisymposium proposal titled "MS 423 - Recent Advances in Data-Intensive Physics-Informed Machine Learning for Accelerating Computational Science", jointly chaired by Qi Tang, Joshua Burby, and Romit Maulik, was accepted by USNCCM 2023 at Albuquerque New Mexico. Please consider submitting an abstract here.
Our large multi-institute collaborative project for Community Research on Climate and Urban Science (CROCUS) has been accepted! We will be working on developing novel parameterizations and surrogates for assessing the impact of tree canopies on street level simulations in collaboration with Drs. Kotamarthi, Fytanidis, and Fernando.