Adjunct Assistant Professor
University of Michigan
PhD Nuclear Engineering & Radiological Sciences 2016
BSE Nuclear Engineering & Radiological Sciences, Minor: Math/Physics 2010
- Scientific Machine Learning, Kinetic Plasma Physics, Computational Mathematics
- Reviewer: JOSS, Phys Rev E, New Journal of Physics
- Open Source Contributor: tensorflow, jax, torchdyn, aws, jupyter
In addition to being an Adjunct Assistant Professor at NERS, Dr. Joglekar is also a Founding Research Engineer at Syntensor, a drug-discovery software startup focused on modeling multi-scale biological systems. He also founded Ergodic LLC to provide expertise in machine learning, fusion physics, and scientific computing on the cloud.
His current research is at the intersection of machine learning, non-linear dynamical systems, multi-scale modeling, kinetic plasma physics, and fusion. He is also interested in building software systems that can enable new paradigms of research and applied science using public cloud infrastructure.
Archis has previously served at Amazon Web Services where he worked alongside some of the premier Machine Learning companies and architected and built ML + scientific software on public cloud infrastructure. He has also served as a Research Scientist and as Head of Artificial Intelligence for an R&D focused software startup. Prior to the transition into industry, he was a Postdoctoral Scholar with the Kinetic Simulation Center at the Department of Physics and Astronomy and EECS at the University of California – Los Angeles and a Research Fellow at Los Alamos National Laboratory.
He has given numerous invited talks and posters, has several publications and citations in theoretical, computational, and experimental plasma physics and has active collaborations with researchers from the National Laboratories as well as universities worldwide. He also contributes to open-source software such as tensorflow, jax, torchdyn as well as open-source software journals such as JOSS.