Undergraduate Computer Science Major at the University at Buffalo graduating in May 2027. Specializing in machine learning pipelines, computer vision systems, human-centric AI tools, and high-performance interactive web interfaces.
Institution: University at Buffalo (B.S. Computer Science, May 2027)
Core Technologies: React, Three.js, Python, OpenCV, XGBoost, MediaPipe, LLaMA-3, YOLOv8, FastAPI, Flask, Node.js, Next.js, GSAP, Tailwind CSS, Docker, GCP.
Multimodal ML pipeline predicting ADHD task abandonment risk in real time. Architecture combines LLaMA-3, YOLOv8 visual attention tracking, XGBoost behavioral classification, and MediaPipe on Google Cloud Platform with FastAPI microservices. Sub-2s end-to-end latency.
Intelligent movie discovery and recommendation platform featuring vector-based semantic search, parametric multi-filter catalog engine, and optimized media compression.
Smart glasses wearable prototype for Alzheimer's patient care. Operates on a Raspberry Pi Zero 2 W streaming camera input to Gemini 2.0 Flash multimodal vision API, delivering I2S audio prompts and proactive wandering detection alerts.
Computer vision hand cricket game detecting webcam hand gestures (1-6 fingers) using MediaPipe landmark detection and NumPy vector mathematics under 500ms latency.
Interactive iOS-inspired desktop web application with window management, dock items, Spotlight search (Cmd+K), and accessible semantic shadow DOM structure.