Rahul Chalamala Resume


California Institute of Technology

September 2022 – June 2026

Bachelor of Science in Computer Science

Graduate-level technical coursework:

  • Machine Learning and Data Mining (CS 155)
  • Large Language and Vision Models (EE 148)
  • Learning Systems (CS 156a)
  • Probability Models (ACM 116)
  • Game Theory (PS 172)
  • Econometrics (Ec 122)

Undergraduate-level technical coursework:

  • Algorithms (CS 38)
  • Linear Algebra (Ma 1b)
  • Data Structures (CS 2)
  • Discrete Mathematics (Ma 6a)
  • Probability and Statistics (Ma 3)
  • Functional Programming (CS 4)
  • Models of Computation (CS 21)
  • Group Theory (Ma 5a)

Professional Experience

AI/ML Researcher at Together AI

August 2023 – Current San Francisco, CA advised by Prof. Ce Zhang

  • Reducing inference latency in large language models by researching and implementing efficient model hot-swapping algorithms in C++ and CUDA.
  • Conducting experiments with knowledge distillation techniques to enable longer context windows in large multimodal models in PyTorch.

    Undergraduate Researcher at Caltech Anima AI + Science Laboratory

    February 2023 – October 2023 Pasadena, CA advised by Dr. Kaiyu Yang Prof. Anima Anandkumar

    • Explored the use of Code Large Language Models, GPT-4 and ChatGPT Plugins in Python to enhance Lean-based automated theorem provers.
    • Leveraged retrieval-augmented generation to result in a 39% increase in proof success rate compared to a retrieval-free baseline model.
    • Accepted for a poster presentation at the ICML 2023 Workshop on Knowledge and Logical Reasoning in the Era of Data-driven Learning.

      Undergraduate Researcher at Caltech Autonomous Robotics and Controls Laboratory

      October 2022 – March 2023 Pasadena, CA advised by Joshua Cho Prof. Soon-Jo Chung

      • Extended ArduPilot for compatibility with custom 6DOF drones to support testing and simulation for the Neural-Fly autonomous vehicle project.
      • Utilized MATLAB to precisely calculate the physical dynamics of any n-motor drone, enabling it to maneuver in all six degrees of freedom.

        Phillips Space Scholar at Air Force Research Laboratory

        June 2021 – July 2022 Kirtland AFB, NM advised by Dr. Joanna Hinks

        • Modeled the Air Force NTS-3 satellite's signal interference in Python and validated accuracy via field tests with the Joint Navigation Warfare Center.
        • Designed a sieve-based algorithm to generate navigation ranging sequences 26.15x faster than existing GPS satellite implementations.


          • International Collegiate Programming Contest (ICPC) North American Championship Qualifier (2023)
          • USA Computing Olympiad (USACO) Platinum Qualifier (2021)
          • Air Force Research Laboratory Outstanding Scholar Award (2021)
          • Stanford ACM Programming Competition Advanced Division Top 3 Award (2022)