معرفی
Somdatta Goswami serves as Assistant Professor in Civil and Systems Engineering and Applied Mathematics and Statistics at Johns Hopkins University, with dual affiliations at the Institute for Data Intensive Engineering and Science (IDIES) and Hopkins Extreme Materials Institute (HEMI). She leads the Centrum IntelliPhysics research group developing AI-driven methodologies for scientific discovery.
Her educational trajectory includes:
- Bachelor's in Civil Engineering from Birla Institute of Technology, Mesra (2011)
- Master's in Structural Engineering from Indian Institute of Engineering Science and Technology (2013)
- PhD in Civil Engineering and Structural Mechanics from Bauhaus University-Weimar, Germany (2020) funded by DAAD
Dr. Goswami's research pioneers Scientific Machine Learning at the intersection of computational mechanics and AI, focusing on neural operator architectures that accelerate physics-based simulations. Her group develops methods for long-time horizon prediction, multiscale multiphysics modeling, and real-time inference in complex systems through latent space representations and physics-informed learning. Current emphases include cardiac digital twins, structural response under natural hazards, and RNA electrophoresis modeling.
Analysis of her 2024-2025 publications reveals dominant trends in latent operator learning, physics-informed neural networks, and hybrid solvers combining traditional numerical methods with deep learning. These innovations enable breakthroughs in computational efficiency across engineering and biological domains, particularly in multiscale modeling and uncertainty-aware simulation.
Her scientific recognition includes:
- National Science Foundation’s National Artificial Intelligence Research Resource (NAIRR) Pilot
- Johns Hopkins University Discovery Award 2024
Dr. Goswami mentors PhD candidates including Dibakar Roy Sarkar (Creel Family Engineering Fellow), Sharmila, and Maryam. Major research funding comprises:
- NSF grant for "Cardiac Digital Twins" with Kevrekidis, Trayanova, and Maggioni
- NSF grant for exascale AI-integrated simulations with UT Austin
- DOE grant for uncertainty-informed latent operators with Shields, Graham-Brady, and Kevrekidis
- Johns Hopkins Discovery Award for biological systems modeling
The Centrum IntelliPhysics group operates within JHU's Latrobe Hall, collaborating with IDIES and HEMI on interdisciplinary projects spanning computational mechanics, materials science, and biological systems. Their work integrates high-performance computing with novel neural architectures to solve previously intractable scientific problems.
