// portfolio
I build
// about
I am a software engineering student specializing in artificial intelligence, 3D point-cloud processing, and algorithmic optimization. Passionate about building high-performance models and interactive systems that scale.
$ focus: ["3D Vision", "Deep Learning", "Discrete Optimization"]
$ core_stack: ["Python", "PyTorch", "C#", "SQL"]
$ status: Open to Opportunities
// stack
// selected work
Engineered an end-to-end ML pipeline utilizing PointNet autoencoders for 3D point-cloud registration. Implemented PCA and Iterative Closest Point (ICP) algorithms to classify and reconstruct satellite models from spatial LiDAR datasets.
Constructed an interactive 3D virtual environment in Unity. Implemented custom player kinematics, environmental physics, and spatial layouts to provide real-time interactive rendering.
Designed a low-churn discrete-event heuristic engine resolving high-contention scheduling over 35 companies, 800 candidates, and 20 rooms. Features real-time disruption replanning with minimal entity reshuffling via Streamlit.
Built an autonomous research agent on an explicit state-graph pipeline that ingests, parses, and synthesizes arXiv papers into grounded, interactive Q&A. Pairs dense retrieval over an in-memory Chroma vector store with anti-hallucination guardrails and exponential-backoff retries for resilient LLM execution.
// contact
Open to opportunities in AI, 3D vision, and systems engineering. The fastest way to reach me:
neel.m.naik4@gmail.com