About Me
Who I Am
I'm a software engineer and Master of Applied Computing graduate from the University of Windsor, with a strong focus on backend development, ML systems, and computer vision.
My work spans GPU-accelerated AI inference at JLR, FastAPI backends for industry-academic projects, Spring Boot recommendation APIs, and ML-powered prediction apps — I love building things end to end.
I bring CS fundamentals to production systems, whether that's optimizing Linux concurrency or building digital twins for sustainability research.
JLR & UWindsor AI Innovation Challenge — Winner
Selected for a two-week paid internship at Jaguar Land Rover based on outstanding performance in an industry-sponsored automotive AI competition.
14
GitHub
Repositories
Repositories
4
Internships
Completed
Completed
5+
Languages
& Frameworks
& Frameworks
MAC
UWindsor
Graduate 2026
Graduate 2026
Experience
Where I've Worked
Sep – Dec 2025
JLR / UWindsor
Windsor, ON
Software Developer Intern AI Systems
- Designed asynchronous multi-agent task execution and GPU data-parallel processing for large-scale model inference workloads on Linux.
- Applied system-level optimization across CPU, memory, and GPU to improve runtime efficiency and execution stability.
- Conducted performance benchmarking evaluating latency, throughput, and resource utilization; presented findings to JLR and academic stakeholders.
May – Aug 2025
MealLens
Windsor, ON
Software Developer Intern Backend
- Built SQLite-backed data models and FastAPI REST endpoints for barcode-based product identification, inventory tracking, and cart automation.
- Translated real user requirements into functional backend components across multiple repositories.
Jan – May 2023
Lad Partners Holdings
Toronto, ON
Software Engineer Intern Fullstack
- Built the company's portfolio platform using React.js and Python with responsive UI across desktop, tablet, and mobile.
Jun – Jul 2022
TatvaSoft
Ahmedabad, India
Frontend Developer Intern Frontend
- Developed frontend components for the Book-E-Sell project using React.js within a MERN stack.
Skills
Tech Stack
Languages
Frameworks
ML & Data
Computer Vision
Databases & Cloud
Systems & Tools
Projects
Highlighted Work
01
ML / AI
CryptoSeer
ML-powered cryptocurrency price prediction web app. Applies machine learning models to historical crypto data to forecast price trends — combining data analysis, model training, and interactive visualizations.
JupyterPython
MLData Viz
02
ML / AI · ★1
Battery Recycling Digital Twin
Digital twin simulation for battery recycling operations. Pipelines with Random Forest, Decision Tree, and Isolation Forest detect contaminated samples and predict chemical composition from operational data.
Pythonscikit-learn
PandasMatplotlibSeaborn
03
Systems · ★1
Linux AI Benchmark
AI inference benchmarking for high-concurrency Linux environments built during the JLR/UWindsor AI Challenge. Measures GPU latency, throughput, and resource utilization across asynchronous multi-agent workloads.
PythonLinux
GPUAsyncMulti-Agent
04
Backend · Java
OTT Subscription Recommender
Full-stack OTT plan recommendation system — Spring Boot REST API backend analyzing user preferences to suggest the best streaming plans, paired with a React frontend for plan selection and comparison.
JavaSpring Boot
REST APIReactJavaScript
05
Full-Stack
GreenHabit — Sustainable Living Tracker
Full-stack Django web app promoting eco-friendly habits. Features user authentication, habit and goal tracking, blog-style posts, likes, comments, and media uploads with a responsive Bootstrap UI.
DjangoPython
SQLiteBootstrapHTML/CSS
06
Computer Vision
Camera Calibration & Stereo Vision
Python/OpenCV system for camera calibration, stereo vision, and 3D reconstruction. Estimates intrinsic/extrinsic parameters, generates disparity maps, and reconstructs depth from stereo image pairs.
PythonOpenCV
NumPy3D Reconstruction
07
Computer Vision
Dense Stereo Matching (ZNCC)
Computer vision project implementing dense stereo matching using Zero-mean Normalized Cross-Correlation (ZNCC) on stereo image pairs. Produces accurate disparity maps for depth estimation.
PythonOpenCV
ZNCCImage Processing
08
Systems · C
System Programming Project
Demonstrates core OS-level system programming in C: process management with fork/exec, file I/O, inter-process communication (IPC), and Linux signal handling. A strong showcase of low-level fundamentals.
CLinux
IPCSignalsfork/exec
Contact
Let's Connect
I'm actively looking for software engineering roles in backend, ML systems, or full-stack development. Whether you have an opportunity, want to collaborate, or just want to say hi — reach out!