Shreyas Waghe

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Bio

I’m a student at the University of Massachusetts Amherst, studying Computer Science and Applied Mathematics. I study and research mathematics – Fair Machine Learning, Statistical Physics, and Biophysics. I describe more of my coursework here.

My mathematical interests are interdisciplinary – 1) the extension and application of mathematical theory to model and explain physical and statistical phenomena; and 2) the development of computational tools enhanced with domain-specific knowledge of the problems I work on. Programmatically, I do:

  1. Scientific Computing - C++, Python, Julia (with Eigen, Boost, Numpy, Scipy etc.)
  2. Optimization - Gurobi, CVX, CVXPY
  3. Quantum Computing - Qiskit, CUDAQ

I’ve contributed to projects at:

  1. Pfizer Inc. - Quantum Optimization Algorithms for Drug Development
  2. Fair and Explainable Decision-Making Lab, UMass CS - Convex Optimization Methods for Fair ML
  3. PALM Research Lab, Brown University CS (with an NSF Undergraduate Fellowship!) - Generative Models
  4. Machta Research Group, UMass Physics - Annealing Algorithms

Additionally, I’ve TA-ed the following courses at UMass:

  1. Pre-Calculus (Math 100, 101)
  2. Computational Physics (Physics 281)
  3. Artificial Intelligence (CS 383)
  4. Introduction to the Theory of Computation (CS 250)

Reaching out

I’m active on LinkedIn, and I’m always available on e-mail.

Updates

  • Jul 2024 - I spent a week visiting the University of Utah’s Math-Bio Group for a Graduate School Preview. Here, I worked with Samantha Linn on exact mean cover times for a run-and-tumble particle. Take a look at our slide deck.
  • May 2024 - I began my internship at Pfizer! I’m a Scientific Computing & HPC intern, and I’m working on developing Quantum Algorithms for Combinatorial Optimization problems arising in Drug Development, in addition to improving classical algorithms for statistical analysis.
  • Apr 2024 - I presented my work with Dr Cyrus Cousins on Convex Optimization for Fair ML at the 30th Massachusetts Undergraduate Research Conference.
  • Mar 2024 - I spent a weekend participating in Columbia University Engineering’s EngAGE program for students interested in pursuing Doctoral studies in Applied Mathematics & other quantitative sciences!
  • Feb 2024 - I started work on my undergraduate thesis in Applied Math advised by Dr Andreas Buttenschoen. It’s on modeling collective cell migration using biophysical principles. Read my proposal here.
  • Aug 2023 - I concluded my summer program at Brown University, and presented posters at the Leadership Alliance National Syposium and the Brown Summer Research Symposium.
  • Jun 2023 - I joined Brown University’s REU - ‘Artificial Intelligence for Computational Creativity’ - working with the PALM Research Lab (PI: Dr Chen Sun) on Generative Modeling techniques.