Himanshu Dhurve

AI safety researcher investigating how large language models internally represent safety-critical concepts. I want to understand whether alignment techniques genuinely shape model internals or simply produce surface-level behavior, and how mechanistic interpretability can help us build more robust safeguards.

Completed the Bluedot Impact Technical AI Safety Course (2026) and the project sprint, replicating and extending refusal directionality findings in Llama-3.1-8B-Instruct. Read the write-up.

GitHub · LinkedIn · Email

Experience

AI/ML Research Intern
Vizuara AI Labs · India · Jan 2026 – Mar 2026

Aerodynamics Research Assistant
San Diego State University · USA · Aug 2021 – Dec 2023

Skills

Core ML/AI
Mechanistic Interpretability, LLM Evaluation & Benchmarking, Post-Training Alignment, Machine Learning, Deep Learning, Computer Vision, NLP, Reinforcement Learning, RAG, Object Detection, Image Segmentation

Languages
Python, C++, Bash/Shell, MATLAB

Frameworks & Libraries
PyTorch, TensorFlow, LangChain, FastAPI, OpenCV, Hugging Face, Unsloth, ChromaDB

MLOps & Infrastructure
MLflow, Databricks, Docker, Git, Weights & Biases, HPC/SLURM

Projects

Geometry of Refusal: Mechanistic Interpretability of Safety-Relevant Representations
Replicated and extended Arditi et al. (2024) on Llama-3.1-8B-Instruct. Extracted per-layer DIM refusal directions across 32 layers; layer 12 was the strongest. Both single-direction and per-layer ablation achieved 100% flip rate on training prompts (0/150 random baseline). On JailbreakBench (n=100), true ASR was 100% with coherence intact across all conditions. Applying layer 12's direction across all layers dropped refusal score to -3.67; skipping it matched per-layer (-0.96), confirming refusal is distributed. Activation addition on harmless prompts pushed refusal score 9x (1.48 → 13.46). Bluedot Impact AI Safety project sprint.
Blog

Customer Churn: End-to-End ML Pipeline
Production ML pipeline for customer churn prediction with model versioning, automated retraining, and inference API using MLflow, FastAPI, and Docker.
Repo

OpenFOAM RAG: Citation-Grounded Q&A
Citation-grounded RAG system for OpenFOAM technical documentation using hierarchical chunking, dense retrieval, and cross-encoder reranking. Achieved 4.6/5 generation quality and 5.0/5 citation correctness. Published at RAG4Report Workshop @ ACL 2026.
Repo · Live

PaperDigest: Agentic PDF-to-Digest
Agentic system that ingests academic PDFs, extracts structured content, and generates concise digests using FastAPI and Gemini. Automated pipeline from upload to summary with key-finding extraction.
Profile

SAR Aircraft Detection (RF-DETR)
Fine-tuned RF-DETR on synthetic aperture radar imagery for aircraft detection. Achieved mAP 0.614, competitive with published benchmarks. Diagnosed overfitting and scoped SARDet-100K for data scaling.
Profile

Student Misconception Detection
Fine-tuned Qwen2.5-Math-1.5B-Instruct with Unsloth and a compact MLP classification head to identify student misconceptions in math reasoning. Improved MAP leaderboard from 0.885 to 0.925 (+4.5%).
Repo

Stable Video OCR: License Plate Recognition
Real-time detection using fine-tuned YOLO11 + EasyOCR. Eliminated flickering via a majority-voting algorithm over a 12-frame rolling buffer, producing stable text output across video frames.
Repo

Video Instance Segmentation: Mask R-CNN
Per-frame object detection and pixel-level segmentation pipeline using PyTorch's pre-trained Mask R-CNN. Renders per-instance colored masks and bounding boxes on live video streams.
Repo

Research

Decompose, Retrieve, Cite: A RAG Pipeline for Structured Report Generation from Technical Documentation
RAG4Report Workshop @ ACL 2026 — Accepted
Himanshu C. Dhurve, et al.

Effect of Surface Texture on the Lift and Drag of Small Spinning Balls
AIAA Aviation Forum & Ascend 2025 — Published
Joseph Katz, Himanshu C. Dhurve
Read Paper

Resume

Download PDF · View

Education

M.S. Aerospace Engineering
San Diego State University, USA · GPA 3.52 / 4.0 · 2021 – 2024
Recipient, Master's Research Scholarship · 2022

B.Tech Mechanical Engineering
Dr. Babasaheb Ambedkar Technological University, India · GPA 8.57 / 10.0 · 2014 – 2018