The Synopsis

I am a Machine Learning Engineer at PhysicsX. I have a Masters in Business Analytics at MIT, focusing on Machine Learning and Optimization where I also served as Class President. I have a BSc in Statistics and Computer Science from McGill, with research work at Mila.

MIT Sloan x Operations Research Center

• Masters of Business Analytics - 2023
• Class President & Graduation Speaker
• Research Assistant (Operations Research Center)
• Sloan Senate and Health & Wellness committee
• Course experience includes:
• Analytics Tools
• Advanced Analytics Edge
• Optimization Methods
• Machine Learning Under a Modern Optimization Lens
• Analytics Lab
• From Analytics to Action
• Poker Bots
• Power and Negotiation
• Integer Optimization
• Sensorimotor Learning

McGill

• BSc Double Major Statistics and Computer Science - 2022
• J W McConnell Scholar
• Research Assistant (Mila)
• Course experience includes:
• Applied Machine Learning
• Algorithm Design
• Artificial Intelligence
• Reinforcement Learning
• Probabilistic Programming
• Statistical Learning
• Numerical Computing
• Theory of Machine Learning
• Network Science
• Advanced Calculus
• Statistics
• Probability
• Real Analysis
• Abstract Algebra
• Linear Algebra
• Sampling Methods
• Stochastic Processes

Experience

Languages

• Python
• Julia
• Java
• R
• SQL
• Web Dev
• OCaml
• Matlab

Technical

• AWS
• Docker
• Git
• Linux

Machine Learning Engineer @ PhysicsX (Mar 2025 - present)

• Building ML models and optimization algorithms for complex physics-based simulations across industries
• Working face-to-face with customers, helping them to achieve accelerated development and optimized engineering designs

Data Scientist @ ENODA (Nov 2023 - Dec 2024)

• Designed and developed signal control algorithms combining ML and optimization to enable self-balancing grids
• Built data science standards, codebases, documentation and roadmaps preparing for team expansion

@ Invenia Labs — Research Intern (May 2021 - Aug 2021) & Software Engineer Intern (May 2020 - Dec 2020)

• Created an open source Julia package, LinearMixingModels.jl, that implements a specific class of multi-output Gaussian Process.
• Developed and analyzed the performance of cloud-computing infrastructure to enable better use of AWS tools

Extracurriculars

Community

• REES Youth Advisory Board member
• Hak4Impact McGill software developer
• Coffee House organizer & performer

Athletic & Artistic

• Ultimate Frisbee
• Rock Climbing
• Golf
• Running
• Piano
• Guitar
• Song Writing
• Theatre

Writing

Papers

• The effect of weather data on probabilistic electricity load forecasts
• Ice lead network analysis
• Student schedule generation via mixed integer optimization
• Prediction methods for numerical weather model uncertainty
• Interpretable end-to-end player prescription via machine learning and robust optimization
• Robust Guided Forest Search for Unit Commitment

Blog Posts and misc.

• Navigating Your First Technical Internship
• Building a Gaussian Process from Scratch
• A Day in the Life of an MBAn Student

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