Experience

Developing AuditMate, an AI-driven web and mobile platform that automates building energy audits by guiding users through assessments and analyzing results with object detection, OCR, and LLMs.

Performing data analysis and image preprocessing. Building and integrating machine learning and deep learning pipelines that support both professional auditors and individual clients, enabling self-serve and guided audit experiences.

Deploying the full cloud-based architecture using AWS EC2 and integrating AI services with Next.js and Flutter frontends to deliver scalable, accessible applications.

Full-stack developer for GenAI Genesis 2026, Canada's largest AI hackathon, with 600+ hackers in 2025.

Developing, revamping, and maintaining the event website and platforms for participants and judges.

Designing and developing database schemas, secure REST APIs with role-based access control, user interfaces, as well as Discord bots, chatbots, and Chrome extensions to streamline workflows. Developing hiring and application review systems for organizers.

Collaborating with cross-functional teams to ensure smooth event operations.

Leading the development of the SceneClarity ML project, an interpretable reliability scoring pipeline for autonomous vehicles, delivering an end-to-end system that quantifies and attributes perception failures under adverse visual conditions.

Managing and collaborating with developers using Jira to track progress, assign tasks, and manage workflows within 3 subteams in performing dataset preparation and analysis, object detection (YOLOv11, RT-DETRv2, etc.), lane detection (LaneNet), glare, weather and time-of-day classification (MobileNetV3, ResNet-50, etc.), unsupervised failure mode attribution (KMeans, GMM, etc.), reliability score aggregation, as well as final deliverables which include containerized REST APIs and a React web application.

Presented SceneClarity to stakeholders at different events and conferences, including the EigenAI Conference.

Developing ML pipelines for the Functional Gene Expression Analysis project for identifying disease biomarkers and developing predictive models for autoimmune diseases such as Rheumatoid Arthritis.

Researching and analyzing gene data from various datasets, evaluating and fine-tuning classification models including Random Forest, Logistic Regression, SVM, and Ridge Classifier for data-driven feature discovery and providing insights into disease mechanisms and treatment strategies.

Official contributor and modder of the starblast.io game. Developed the official “Capture the Flag” mod, which has been played around 2 million times, improving performance, balance, and engagement. Developed multiple mods using the Starblast.io API, implementing real-time game logic in JavaScript with WebSockets, and designing custom 3D ships using CoffeeScript for Three.js rendering.

FTC Team 16488 - Rams Robotics Team | Mentor (2025-Present), Senior Programmer (2023-2025), Builder & Designer (2021-2022)

FTC Team 22101 - Lambs Robotics Team | Mentor (2025-Present), Senior Advisor (2023-2024), Programming Lead (2022-2023)

Mentored, led, and advised FTC teams 16488 and 22101, developing advanced autonomous systems, TensorFlow and OpenCV vision, and PID-controlled motion. Designed robot components using Fusion 360 and OnShape. Engineered robot simulations and parallel state machines for complex behavior modeling. Helped teams win many awards, including top placements at Ontario Provincial Championships and Innovate/Design Awards.

Led, trained, and supervised a team of tutors to teach students in programming, STEM, and languages. Adjusted course trajectory based on student feedback. Developed marketing initiatives to expand the organization’s reach, positively impacting 300+ students across 50+ schools in Ontario.

Designed and developed the web platform using the SvelteKit framework. Engineered intuitive database schemas and relationships in the Firestore cloud database to support core app functionality such as user management and course enrollment. Continuously improved the user experience based on user feedback.

Worked as a part-time tutor at Upper Markham Learning Centre, teaching coding, robotics, competitive programming, and high school STEM subjects including math and physics. Delivered personalized lessons, managed multi-level classrooms, and provided detailed progress feedback to parents while adapting strategies to support individual learning needs.

Led the coding section at the non-profit organization FutureEd 4 Kids, managing mentors and organizing team meetings. Designed new programming courses to expand the coding section in the organization. Taught students in engaging and interactive classes.

Researched technical foundations of deep learning neural networks and their applications in self-driving technologies.

Designed and conducted a primary survey to collect and analyze data on public perceptions of autonomous vehicles.

Synthesized primary and secondary sources into structured arguments addressing technical, ethical, and societal impacts.

Developed predictions on the future of AV regulation and adoption based on current technological and legal trends.

Strengthened skills in research design, data analysis, and scientific writing through a 4000-word paper.

Conducted in-depth theoretical and experimental research on open-ended physics problems, winning a gold medal in 2023, and a bronze medal in 2024 as part of team Schwarzschild. Designed and executed hands-on experiments to collect and validate data. Applied MATLAB and Python (with Matplotlib) for simulations, data analysis, visualization, and communication. Presented and defended solutions in competitive debates, demonstrating strong problem-solving and scientific communication skills.