Approximate Nearest Neighbor Search
Density-aware quantization, re-ranking, and CPU/SIMD optimization for high-recall vector search.
Open to ML systems work
Ganap Tewary
ML systems researcher building fast vector search, RAG infrastructure, FPGA acceleration, and hardware-aware AI.
Current Focus
FPGA-Accelerated HNSW for sub-us vector search
Thesis Progress
Chapter 2/5
Available From
Summer 2026
Research Direction
Systems that make retrieval and inference feel immediate.
Hardware-Accelerated ML
FPGA datapaths and accelerator-aware design for ultra-low latency graph traversal and retrieval.
RAG and Knowledge Systems
Graph-aware retrieval, autoscaling, and production-minded infrastructure for reliable LLM workflows.
Publications
Active papers and research artifacts.
Opportunities
Summer 2026 ML Engineering Internship
Open to research collaborations in approximate nearest neighbor search and efficient ML systems.
Targets
Conference deadlines.
Contact
Bring a concrete research problem, prototype, or collaboration idea.
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