cv
Basics
| Name | Vijayabharathi Murugan |
| Label | Graduate Student at Stony Brook University |
| vmurugan@cs.stonybrook.edu | |
| Phone | +1 (934) 246-0713 |
Work
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2025.01 - 2026.05 Stony Brook, NY
Research Assistant — Master's Thesis
Stony Brook University
Advisor: Prof. Zhaozheng Yin. Developed a training-free pipeline for zero-shot 6DoF object pose estimation by fusing Stable Diffusion (DIFT) and DINOv2 features into 3D point descriptors from multi-view CAD renders, with pose recovered via Kabsch+RANSAC. Outperformed DINOv2-only baseline by +6.8 Mean AR over all 7 BOP benchmark datasets.
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2023.10 - 2024.07 Bengaluru, India
Senior Data Scientist
Anheuser-Busch InBev
D2C Sales Decomposition: Built a deep learning sales attribution model in TensorFlow with custom domain-specific layers and hierarchical parameter sharing across brands; automated retraining pipeline via GitHub Actions with DVC-managed data pulls. Achieved 88.4% R² on sales prediction; measured impact of $49M+ in media spend across 60+ brands.
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2021.09 - 2023.09 Bengaluru, India
Data Scientist
Anheuser-Busch InBev
E-Retail ROI: Developed a Linear Mixed Effects model to measure impact of $1.5M+ promotion spend, achieving 82.5% R²; automated hyperparameter tuning via Bayesian Optimization. Built a RAG pipeline using LangChain and Chroma with chain-of-thought prompting demonstrated to ABI's CTO. Engineered a GPT-4-powered summarization tool for social signals in collaboration with Bain & Company.
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2020.08 - 2021.08 Bengaluru, India
Associate Data Scientist
Anheuser-Busch InBev
Media Effectiveness: Developed an XGBoost model with SHAP-based feature attribution achieving 87.3% R² with top-K features capturing >75% cumulative SHAP attribution. MMM Lead, Canada: Led end-to-end modeling across a $17M+ marketing budget; recommendations drove an estimated $4M in incremental net revenue.
Education
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2024.08 - 2026.05 Stony Brook, US
Master of Science in Computer Science
Stony Brook University
- Vision Language Models
- Intro to Computer Vision
- Natural Language Processing
- Distributed Systems
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2016.08 - 2020.07 Chennai, India
Bachelor of Technology in Chemical Engineering
Indian Institute of Technology Madras
- Multivariate Data Analysis for Process Modeling
- Process Optimization
- Integer Optimization
Publications
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2020.10.28 Prediction of IPL matches using Machine Learning while tackling ambiguity in results
Indian Journal of Science and Technology
Applied machine learning models to predict IPL cricket match outcomes while addressing ambiguity in match results.
Skills
| Programming | |
| Python | |
| SQL | |
| Golang | |
| C |
| Computer Vision | |
| DINOv2 | |
| CLIP | |
| Stable Diffusion | |
| LLaVA | |
| OpenCV | |
| Pose Estimation |
| AI/ML | |
| Hugging Face | |
| Transformers | |
| LLMs | |
| RAG / LangChain | |
| Fine-tuning (LoRA) | |
| Bayesian Optimization | |
| XGBoost |
| Tools & Infrastructure | |
| Docker | |
| Git | |
| FastAPI | |
| CI/CD | |
| pytest | |
| MLflow | |
| Wandb | |
| PowerBI | |
| Excel |
Languages
| English | |
| Native/Bilingual Proficiency |
| Tamil | |
| Native/Bilingual Proficiency |
| Hindi | |
| Native/Bilingual Proficiency |
Interests
| Computer Vision |
| Natural Language Processing |
| Deep Learning |
| 6DoF Pose Estimation |
| Generative AI |
| Machine Learning Systems |