Summary
Sangeetha Grama Srinivasan is a research scientist specializing in differentiable simulation, 3D geometry, and high-performance computing, with over a decade of experience bridging academic research and industry. During her PhD at UW–Madison she integrated deep learning with physics-based modeling, producing practical tools for realistic fluid and digital-human simulation. She has driven GPU-accelerated solvers and real-time, super-resolved fluid previews at NVIDIA, and previously built cross-platform C++ libraries for cloud asset syncing at Adobe. Based in the United States, she combines strong numerical methods and systems skills with hands-on implementation in frameworks like NVIDIA Warp and fVDB, and has a proven track record of turning research prototypes into high-performance, production-ready components.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Wisconsin-Madison
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at National Institute of Technology Karnataka