Building high-performance AI pipelines at the edge and in the cloud.
I am a Master's student at NYU specializing in Machine Learning Systems and Edge AI. My engineering philosophy focuses on bridging the gap between research models and production deployment. I build systems that are latency-sensitive, memory-safe, and scalable.
- π Currently working on: Real-time video analytics using NVIDIA DeepStream & C++.
- πΌ Experience: IT Technology Intern @ NYU, ML Intern @ Novixpert, GSoC Contributor @ NRNB.
- π± Learning: Advanced CUDA optimization and Distributed Systems.
- β‘ Core Stack: C++, Python, PyTorch, AWS, Docker.
| Project | Stack | Description |
|---|---|---|
| Edge-AI Facial Recognition | C++ DeepStream AWS |
30+ FPS pipeline on Jetson Nano using custom GStreamer plugins and Zero-Copy memory transfer. |
| Autonomous Navigation RL | PyTorch PPO CUDA |
Deep Reinforcement Learning agent optimized with vectorized environments for robot navigation. |
| Cloud-Native Automation | AWS Lambda Svelte Python |
Serverless microservices to automate university data workflows, reducing admin overhead by 90%. |
| GSoC 2024 Contribution | Python Open Source |
Modernized genomic data pipelines for the National Resource for Network Biology (NRNB). |


