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NerdyVisky/README.md

πŸ‘‹ Hello devs, I'm Vishvesh (NerdyVisky)

Linkedin Badge Gmail Badge GitHub LeetCode Website


πŸ‘¨β€πŸŽ“ About Me

I’m a Machine Learning Engineer + Researcher currently pursuing my M.S. in Computer Science at NYU Courant (GPA: 4.0).
My work sits at the intersection of:

  • LLM reasoning, retrieval & attention mechanisms
  • Healthcare ML & safety for deployed clinical AI
  • Document intelligence, VLMs, synthetic data generation
  • Production ML systems & model monitoring

πŸ§ͺ Current Roles

πŸ”¬ Graduate Research Assistant β€” NYU CILVR Lab

Working with Prof. Eunsol Choi on multilingual LLM retrieval:

  • Improving in-context fact retrieval across 5 languages
  • Modifying attention mechanisms in LLaMa-3.2-8B, Qwen-2.5-7B, Phi-3.5
  • Achieved 15% retrieval gains with 30% lower KV-cache

πŸ₯ Machine Learning Engineer β€” NYU Langone Health (BioDASH)

Building production-grade safety systems for ML models powering clinical workflows across 23 hospitals.

  • Designed drift detection pipelines (K–S, PSI, DeLong)
  • Real-time monitoring with Prometheus + Grafana
  • Extensive work with HIPAA-compliant datasets (EPIC COSMOS, OMOP CDM, Caboodle, Clarity)
  • Co-authored NIH & PCORi grant proposals

πŸ“„ ML Researcher β€” CVIT, IIIT Hyderabad

Published at ICDAR 2025 (Oral, Top 2%).

  • Generated 18k synthetic slides using novel LLM pipeline
  • Boosted VLM performance by 13% mAP and 10% Recall@K
  • HuggingFace model reached 500+ downloads

πŸ“š Publication

ICDAR 2025 (Oral, Top 2%)

AI-Generated Lecture Slides for Improving Slide Element Detection and Retrieval
Maniyar, Trivedi et al.
πŸ”— Project: https://synslidegen.github.io
πŸ”— DOI: https://doi.org/10.1007/978-3-032-04614-7_11


πŸš€ Featured Projects

⚑ Adaptive & Warp-Cooperative GPU Hash Table

πŸ”— Code: https://github.com/NerdyVisky/adaptive-gpu-hashtable

  • Built a high-performance adaptive GPU hash table in C++/CUDA using cooperative groups and elected-lane atomics
  • Achieved 21Γ— faster inserts and 20Γ— faster lookups, outperforming naΓ―ve GPU hashing at scale
  • Implemented epoch-based dynamic resizing + compaction for non-blocking concurrency
  • Sustains stable throughput on 100M+ operations, even at 0.99 load factor

🎯 Attention-Aware DPO for Multi-Image VQA


πŸ” Open-Source Contribution: Retrieval Heads (ICLR 2025 spotlight)


πŸ’» Tech Stack

Languages

Python Β· C/C++ Β· R Β· SQL (Postgres, MySQL) Β· JavaScript Β· TypeScript Β· Bash/Zsh

Frameworks & Libraries

PyTorch Β· TensorFlow Β· HuggingFace Β· LangChain
NumPy Β· Pandas Β· scikit-learn Β· Matplotlib

DevOps & Tools

AWS Β· GCP Β· Azure Β· Databricks
Docker Β· Git Β· Redis Β· MongoDB
Prometheus Β· Grafana


πŸ“ˆ GitHub Stats

Github Stats Top Langs


Thanks for stopping by! Feel free to reach out if you're working on LLMs, retrieval, ML safety, or healthcare AI. πŸš€

[Nov 2025] - I am looking for fulltime roles related to SDE/MLE and Applied Science based in the US starting Summer 2026. I am a US Permanent Resident (Green Card), and hence require no visa sponsorship. If you're hiring and like my work, feel free to connect on my email : vishvesh106@gmail.com

Pinned Loading

  1. adaptive-gpu-hashtable adaptive-gpu-hashtable Public

    A spelled out, plug-and-play, header-only data structure implementation of GPU-friendly HashTable which works optimally on single-core, multicore, or GPU-accelerated applications

    Cuda 1

  2. multilingual-retrieval-translation-heads multilingual-retrieval-translation-heads Public

    Python

  3. synslidegen/synslidegen.github.io synslidegen/synslidegen.github.io Public

    Official Website repository for SynSlideGen (ICDAR 2025)

    JavaScript