Hamza Attarwala

// PhD Researcher · Software Engineer

Hamza
Attarwala

Building intelligent systems at the intersection of software engineering and machine learning. PhD student at Polytechnique Montréal, working on scalable AI applications.

Researcher & Builder

I'm a PhD student in Computer Engineering at Polytechnique Montréal, at the Software Emerging Technologies (SæT) Lab under the supervison of Dr. Mohammed Hamdaqa. I completed my MSc. in Applied Modeling & Quantitative Methods at Trent University, under the supervision of Dr. Quazi Rahman.

My research sits at the intersection of Artificial Intelligence and Software Engineering (AI4SE), with a focus on harnessing Large Language Models (LLMs) to augment and automate core SE tasks. Currently, I'm investigating how LLMs can improve areas such as requirements engineering, code generation, and formal specification — with the broader goal of making software development more reliable, efficient, and accessible.

My work bridges rigorous research and practical engineering — from building EV charging platforms to designing AI-powered course recommenders!

Previously at EasyFits and EVDrop, I led backend development, optimized APIs, and deployed scalable cloud services. I also spent four years as a Teaching Assistant at Trent University, helping students in learning Python, Java, and Linux workflows.

Languages

Python Java JavaScript C SQL

Technologies

AWS React Django NestJS Linux TensorFlow PyTorch Scikit-Learn PostgreSQL Docker

Academic Background

Doctor of Philosophy
Computer Engineering
Polytechnique Montréal
Jan 2026 — Dec 2029 · Montréal, QC
Master of Science
Applied Modeling & Quantitative Methods
Trent University
Sept 2023 — Aug 2025 · Peterborough, ON
📄 Master's Thesis ↗
Bachelor of Science
Computer Science
Trent University
Sept 2019 — Sept 2023 · Peterborough, ON

Publications

Master's Thesis · 2025

A Two-Stage Hybrid Deep Learning Framework With Reinforce-Learned Temporal Dilated Convolutions for Predicting Vehicle Left-Turn Speed at Pedestrian Crossings ↗

Hamza Attarwala · Trent University · 2025

Predicting vehicle speed at critical road segments, such as pedestrian crossings during left-turn maneuvers at signalized intersections, is essential for improving traffic safety and supporting autonomous driving systems. This thesis presents a novel two-stage hybrid deep learning framework enhanced with reinforcement learning to forecast vehicle left-turn speed at pedestrian crossings.

Where I've Worked

Feb 2025 — Present

Backend Developer

EVDrop ↗ · Remote

  • Built an EV charger reservation platform (Django, Clojure, OCPP), reducing driver wait times with 91% positive pre-launch feedback.
  • Deployed automated email notifications via Django + AWS SES with 100% delivery success across 81 reservations in 10 days.
  • Developed a feedback module (Django, PostgreSQL, AWS S3) enabling peer reviews, improving user decision-making.
  • Built a unified analytics dashboard eliminating manual data collection for EV operators.

May 2023 — Feb 2025

Software Developer

EasyFits ↗ · Remote

  • Led development of a virtual try-on platform with personalized 3D avatars, significantly boosting user engagement.
  • Optimized NestJS + PostgreSQL API via Prisma ORM — reduced query time from 200ms to under 100ms.
  • Built web and mobile frontends in React and React Native, integrating D3.js for advanced data visualization.
  • Automated CI/CD pipelines using Docker; deployed Blender-based Python avatar service on AWS S3 and EC2.

Jan 2021 — May 2025

Teaching Assistant

Trent University · Peterborough, ON

  • Assisted 30+ students with lab assignments across Python, Java, HTML, and CSS coursework.
  • Delivered coding tutorials and lectures to 90+ students covering Linux CLI and GitHub workflows.

Selected Work

Let's Connect

Whether it's research collaboration, a project idea, or just a conversation — my inbox is open.