About Me

A driven and curious biochemist turned software engineer, interested in the applications of technology in answering biological questions

I love exploring and engaging in different new diverse projects. While I enjoy building machine learning models, I also love to hike, meet new people and reinvent the ways we enjoy and consume food.

Check out my projects here & my cv.


  • Open Source PyTorch Contribution : Implemented conditional GAN


  • 2019-Present: Research Assistant @ Stanford University
    Principle Investigator: Dr. Anshul Kundaje, Department of Genetics & Computer Science
    • ENCODE Working Group Lead: Leads data analysis and pipeline generation in key working group of 41 participants in ENCODE Consortium4.Robust testing of validation pipeline across multiple celltypes to be used by Consortium.
    • Involved in problem formulation and hypothesis testing based on different data input types.
    • Frequent Presentations to non-technical audience.
    • Data Analytics and Deep Learning: Implemented and interpreted statistical and deep learning modelson multi-model biological data inputs.
    • Curated and combined datasets for exploration and downstream prediction tasks.Improved ease of use and validation practices of relevant code and packages
  • 2018-2019: Research Assistant @ McGill University
    Supervisor: Professor Jerome Waldispuhl
    • Implemented CNNs to solve multiple sequence alignment problem via utilizing crowd-sourced human-computing platforms - Phylo
    • Performed feature selection on known sequence alignments that allow for automatic adjustments of puzzle difficulty based on skill level
  • 2016-2018: Research Assistant @ McGill University
    Supervisor: Professor Kalle Gehring
    • Resolved N15 spectrum of linker protein involed in autophagy, Crystallized transmembrane domain of CNNM Transmembrane protein
    • Involved in protein growth and purification


  • B.Sc. in Biochemistry, Computer Science, McGill University, Dec 2018
    • BL21 research scholar:
    • Yale hackathon sponsor award: Highest social good and scalability in machine learning
  • Diploma in Culinary Arts, International Culinary Centre, 2015

Skills & Relevant Courses

  • Python, Java, C, BASH Scripting
  • Applied Machine Learning
  • Computational Biology Research and Applications
  • Software Systems
  • Algorithms & Data Structures I, II
  • Probability, Statistics, Linear Algebra