People

Principle Investigator (PI)

Dr. Ameya D. Jagtap

Assistant Professor (Tenure Track),

Aerospace Engineering Department,

Worcester Polytechnic Institute, USA.

Email: ajagtap@wpi.edu, ameyadjagtap@gmail.com

Website: Personal,  WPI

Before joining WPI, Dr. Jagtap served for three and a half years as an Assistant Professor of Applied Mathematics (Research) at Brown University. His academic path includes both a PhD and a Master’s degree in Aerospace Engineering from the prestigious Indian Institute of Science (IISc) in India, followed by postdoctoral research at the Tata Institute of Fundamental Research - Center for Applicable Mathematics (TIFR-CAM). He later continued his postdoctoral work at Brown University's Division of Applied Mathematics. Dr. Jagtap is particularly focused on advancing scientific machine learning algorithms that seamlessly blend data and physics, with wide-ranging applications in computational physics. His areas of expertise include scientific machine learning, deep learning, data- and physics-driven methods, uncertainty quantification, and multi-scale/multi-physics simulations covering solids, fluids, and acoustics. He is well-versed in spectral and finite element methods, WENO/DG schemes, and domain decomposition techniques, as well as traditional machine learning techniques, including deep generative models and innovative neural network architectures such as quantum and graph neural networks. His interests extend into cutting-edge domains, such as spiking neural networks and bio-inspired computing approaches, pushing the boundaries of scientific and machine learning applications.

Editorial Board Member: He serves on the editorial board of the following international journals.

• Neural Networks, Elsevier (IF: 7.8) 

• Neurocomputing, Elsevier (IF: 6.0) 

• Journal of Machine Learning Research (IF: 5.177)

• Frontiers in Neuroinformatics (IF:  3.5)

• Frontiers in Computational Neuroscience (IF:  3.2) 

Moreover, he has reviewed more than 500 manuscripts for over 100 international journals and has served as a proposal reviewer on panels for several prestigious institutions, including the U.S. Department of Energy, the Swiss National Science Foundation, and A*STAR (Singapore), among others.

Ph.D. Student

Sidharth S. Menon

Aerospace Engineering Department

Worcester Polytechnic Institute, USA.

Sidharth has a strong interest in research at the intersection of scientific computing, engineering, and machine learning, particularly in solving complex problems. His background includes experience gained in both academic research and industry, with projects spanning materials, fluids, and dynamical systems. Before joining WPI for his Ph.D., Sidharth completed a research-focused Master’s degree at the University of Washington, Seattle.

Ph.D. Student 

Trishit Mondal

Aerospace Engineering Department

Worcester Polytechnic Institute, USA.

Trishit's research interests include scientific machine learning, data-driven modeling of dynamical systems, and high-performance computing. His past projects have focused on modeling landslides using particle-based hydrodynamicsand solving inverse problems in functional spaces related to solid and fluid mechanics. He also has experience in robotics development, particularly in path planning and navigation. Before joining WPI for his Ph.D., Trishit completed Integrated M.Tech (Earth Science) degree from IIT Roorkee.