Parth Jaggi
Graduate Research Assistant
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolParth Jaggi is a research-driven software engineer with 8 years of experience bridging applied machine learning, simulation, and full-stack development. As a Graduate Research Assistant at the University of Toronto’s D3M Lab he develops symbolic dynamic programming methods and MonteCarloLights—a traffic-signal control system that combines learned microscopic traffic dynamics with tree-search and is patent-pending. He has production experience building scalable backend APIs and recommendation services using Node.js, MongoDB, and PyTorch from roles at myPAT.in and DataMonk. Parth’s background in mechanical engineering and hands-on numerical work (MatLab, CFD tools) informs his ability to translate physical models into data-driven algorithms. Colleagues describe him as an explorer of ideas—equally comfortable prototyping DRL trading bots as implementing closed-form solutions for continuous-state MDPs. Based in Toronto, he blends rigorous academic research with practical engineering to deliver systems that generalize beyond pure model-free approaches.
8 years of coding experience
2 years of employment as a software developer
Practical Deep Learning For Coders, Practical Deep Learning For Coders at fast.aiMachine Learning Advanced Nanodegree Program, Machine Learning Advanced Nanodegree Program at UdacityHigh School, High School at Manav Sthali School, Rajinder Nagar, DelhiMaster of Applied Science, Mechanical and Industrial Engineering, Master of Applied Science, Mechanical and Industrial Engineering at University of TorontoEngineer’s Degree, Mechanical Engineering (Hons), 8.53, Engineer’s Degree, Mechanical Engineering (Hons), 8.53 at Indian Institute of Technology, Ropar
Stackoverflow
3reputation
1kreached
0answers
1question
Github Skills (79)
parallel10
python10
ray10
optimization10
java10
reinforcement-learning10
programming-tools10
pytorch10
llm-inference9
deep-learning9
hyperparameter-optimization9
automl9
traffic9
transport9
simulation9
Programming languages (6)
Github contributions (5)
RaptorMai/flow
Jun 2020 - Nov 2020
Computational framework for reinforcement learning in traffic control
Contributions:28 commits, 10 PRs, 5 pushes in 5 months
reinforcement-learningdeep-reinforcement-learningtrafficreinforcementcomputational
jihwan-jeong/xadd-inference
Sep 2020 - May 2021
Automatically exported from code.google.com/p/xadd-inference
Contributions:3 PRs, 13 pushes, 1 branch in 8 months
pytorchnlpdeep-learninginferencemachine-learning
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