201 Latrobe Hall
Research Areas Scientific machine learning algorithm development with applications to various physical and biological systems

As an assistant professor in the Department of Civil and Systems Engineering, Somdatta Goswami is keen to advance the modeling and simulation of physical and biological systems. Her research, at the intersection of modeling, simulation, and machine learning, aims to provide real-time solution strategies for system learning, prediction, optimization, and decision-making. Goswami’s specific focus lies in Scientific Machine Learning (SciML) and Artificial Intelligence for Science (AI4Science), where she contributes to the development of algorithms and architectures tailored to address challenges in engineering, physical, and biological systems through the application of deep learning methodologies.

Her academic journey includes obtaining a bachelor’s degree in civil engineering from Birla Institute of Technology, a master’s degree in structural engineering from the Indian Institute of Engineering Sciences and Technology, and a PhD in structural engineering from Bauhaus University Weimar. She was a recipient of the Deutscher Akademischer Austauschdienst (DAAD) scholarship for her PhD pursuits in 2017 and subsequently carried out her postdoctoral research in the Division of Applied Mathematics at Brown University.