Numerical simulations are essential when real-world experiments are too costly, dangerous, or plain impossible. Using computational physics we create a "digital laboratory" where we can test theories and understand complex systems without the real-world risks. For example, simulating space events helps us understand astrophysical phenomena without actually leaving Earth. At its foundation, numerical simulation converts physical events into mathematical models. Using computational fluid dynamics (CFD) as our primary tool, we manipulate these models to replicate and predict real-world behaviors.

Our research groups work on a variety of challenges related to aerospace, machine learning, high-performance computing (HPC), and simulations. We focus on two main areas: Numerical Simulation and Physics-Informed Machine Learning. In numerical simulation, we work on the mathematics and physics that is used in the design of these simulations as well as the computer science ideas for developing codes to run on HPC clusters. In Physics-Informed Machine Learning we investigate how ML/AI can enhance and accelerate simulation processes. 

2025 Research Highlights

MIT Undergraduate Research Technology Conference (URTC)

October 10–12, 2025 · Massachusetts Institute of Technology
https://urtc.mit.edu

• (Paper + Oral) Physics-Informed Neural Networks for Aerodynamic Shape Optimization:
  A Machine Learning Approach to Accelerating Aircraft Design
  Akshay Lakkur, Benjamin Schmidt, Linus Feng, Aarav Dixit, Chloe Lui

• (Paper + Oral) Airfoil Trailing-Edge Noise Prediction Using Physics-Informed Neural Networks
  Kaining Yuan, Sathvik Malla, Varun Ramachandran, Vinamra Singhal

• (Paper + Oral) Challenges in 2D Hybrid Non-Quasi-Neutral Hall Thruster Simulation
  Matthew Fang, Weiping Li, Aditya Kaul, Efthimios Gkatzimas, Ashita Pant, Rhea Haridas

AIAA Young Professionals, Students, and Educators (YPSE) Conference

November 21, 2025 · Johns Hopkins University
https://www.aiaaypse.com

• (Oral) Challenges in 2D Hybrid Non-Quasi-Neutral Hall Thruster Simulation:
  Development and Validation of the ASCFD Code
  Vunal Jinasundera, Naga Chintalapati, Matthew Fang, Weiping Li, Aditya Kaul,
  Efthimios Gkatzimas, Ashita Pant, Rhea Haridas

Southern California Conference for Undergraduate Research (SCCUR)

November 22, 2025 · California State University Channel Islands
https://www.sccur.org

• (Oral) Challenges in 2D Non-Quasineutral Hall Thruster Simulation
  Weiping Li, Aditya Kaul

• (Poster) Airfoil Trailing-Edge Noise Prediction Using Physics-Informed Neural Networks
  Kaining Yuan, Varun Ramachandran

Preprint Submitted

December 24, 2025 · Link 

• (Paper) Physics-Informed Gradient Boosted Decision Trees for Simulating Mathematical and Physical Systems
  Ishita Bhadra, Shriya Bhadra, Aveesh Agrawal

Publications

PDFs attatched via google drive for convenience