Utkarsh

Utkarsh

Fourth-year Ph.D. Student in Computational Science and Engineering

Massachusetts Institute of Technology

Biography

I am a $4^{th}$ year Ph.D. student in the Dept of Computational Science and Engineering at MIT, co-advised by Prof. Alan Edelman and Dr. Chris Rackauckas at the Julia Lab, MIT CSAIL. My research lies at the intersection of artificial intelligence, probabilistic modeling, and scientific computing, with a focus on building scalable, performance-engineered, and physics-consistent AI systems.

In the past internships I have worked closely with Danielle Robinson, Bernie Wang, and Michael W. Mahoney at AWS AI Labs, and collaborated with Akshay Subramaniam and Noah Brenowitz at NVIDIA.

I completed my undergraduate studies double majoring in Electrical and Chemical Engineering from IIT Kanpur, India.

Interests
  • Artificial Intelligence & Machine Learning
  • Probabilistic Modeling
  • Scientific Computing
  • Physics-Informed AI
Education
  • Ph.D. in Computational Science and Engineering, 2024-Present

    Massachusetts Institute of Technology

  • Master's in Computational Science and Engineering, 2024

    Massachusetts Institute of Technology

  • Bachelor of Technology in Electrical Engineering, Chemical Engineering, 2022

    Indian Institute of Technology Kanpur

Experience

 
 
 
 
 
Research Intern
May 2025 – Present Remote
Performance improvements for cBottle project and multiscale diffusion models for climate modeling. Mentors: Akshay Subramaniam, Noah Brenowitz.
 
 
 
 
 
Applied Scientist Intern
June 2024 – August 2024 Remote
Probabilistic learning framework with hard constraints and time series forecasting with LLMs. Mentors: Danielle Robinson, Bernie Wang, Michael W. Mahoney.
 
 
 
 
 
Julia Lab, MIT CSAIL
Research Assistant
September 2022 – Present Cambridge, MA
GPU-based differential equation solvers, neural SDEs, and parallel optimization methods. Co-advised by Alan Edelman and Chris Rackauckas.
 
 
 
 
 
Julia Computing Inc.
Research Intern/Consultant
January 2021 – August 2022 Remote
Pseudo-transient methods for differential equations with CUDA support and automatic differentiation. Mentor: Chris Rackauckas.
 
 
 
 
 
Voice Intelligence Team, Samsung Research
Research Intern
January 2021 – December 2021 Remote
Slot identification algorithms and BERT models for conversational AI.

Publications

Loading publications...

Loading publications...