A little bit about me :

Profile Picture

I am a final-year PhD candidate at the Department of Computer Sciences, University of Wisconsin-Madison. I am fortunate to be advised by Prof. Eftychios Sifakis. My interests lie in the intersection of Differentiable Simulation and High-performance computing. My PhD research is focused on synergistic integration of deep learning in physics-based modeling and simulation. Specifically, I have experience in designing fast and efficient solutions for problems in 3D vision, physics-based deep learning and scientific computing.

I am currently seeking full-time industry positions where I can apply my skills in designing scalable and differentiable pipelines. I'm open to opportunities that will both utilize my current skills and help me learn more. If you're looking for a simple example to understand what differentiable pipelines might be, you can take a look at this one: Learning edge detection operators

Before coming to the US, I graduated with a B.Tech in Computer Science from National Institute of Technology Karnataka (NITK), India. I also worked for a year at Adobe, India.

In my free time, I like hiking & biking. I also make it a point to try out new baking recipes. Feel free to contact me if you want some nice trail suggestions in Madison or some yummy recipes!

For a copy of my CV, please send me an email :)

Work Experience

[May 2024 - Jan 2025] Research Scientist Intern @ NVIDIA

Spent 8 months working with amazing people at NVResearch working on deep learning for particle-based fluid simulations (SPH and more).


[Summer 2022] Internship @ NVIDIA

Spent the summer designing an anatomy transfer tool for internal anatomy transfer across digital human models. Our work was featured in the NVIDIA Special Address at SIGGRAPH 2022: Youtube Link.


[Summer 2021] Internship @ NVIDIA

Spent the summer exploring an efficient numerical solver design for sparse symmetric definite matrices for applications in physics-based facial animation.


Graduate Research Assistant

Secured a Research Assistantship to support my PhD research in Synergistic Integration of Deep Learning in physics-based modeling and simulation


Graduate Teaching Assistant

Worked as a Teaching Assistant for Parallel and Throughput computing (CS639), Computer Graphics (CS559) - taught by Prof. Eftychios Sifakis and Programming III course (CS400) - taught by Prof. Debra Deppeler.


[Jun 2018 - Aug 2019] Software Development Engineer

Worked on ACPLocal (Adobe Content Platform) to sync files across devices (desktop and mobile) in the Cloud Technology team at Adobe, India. Developed a platform agnostic asset upload-download C++ library that can be used by all Adobe products for syncing files on cloud.


Projects & Publications

4. Near-realtime Facial Animation by Deep 3D Simulation Super-Resolution

Hyojoon Park, Sangeetha Grama Srinivasan, Matthew Cong, Doyub Kim, Byungsoo Kim, Jonathan Swartz, Ken Museth, Eftychios Sifakis
Accepted to Transactions On Graphics 2024 - Presented at SIGGRAPH Asia 2024


3. Fluidic Topology Optimization with an Anisotropic Mixture Model

Yifei Li, Tao Du, Sangeetha Grama Srinivasan, Kui Wu, Bo Zhu, Eftychios Sifakis, Wojciech Matusik
Accepted at SIGGRAPH ASIA 2022.


2. Learning active quasistatic physics-based models from data

Sangeetha Grama Srinivasan, Qisi Wang, Junior Rojas, Gergely Klár, Ladislav Kavan, Eftychios Sifakis
Accepted at SIGGRAPH 2021.


1. Trace-Driven Simulation and Design Space Exploration of Network-on-Chip Topologies on FPGA

Sangeetha Grama Srinivasan, Vignesh Radhakrishnan, Prabhu Prasad, Khyamling Parane, Basavaraj Talawar
Accepted at International Symposium on Electronic System Design (ISED) 2018.