Resume
Download Full Resume (updated Nov 2024)
Summary
Education
- MS, Mechanical Engineering (Artificial Intelligence focus), Carnegie Mellon University, Aug 2023 – May 2025
- GPA: 3.96/4.0
- Concentration: Generative AI, Large Language Models, Deep Learning, and NLP
- TA Role: Teaching Assistant for Mathematical & Computational Foundations for ML
- B.Tech, Mechanical Engineering, Delhi Technological University (DTU), Aug 2017 – Jul 2021
- GPA: 8.75/10
Professional Experience
Graduate Student Researcher, CMU Machine Learning Dept.
- Integrated Geo-FNO into PDE solvers, achieving 2.7x lower error compared to traditional methods.
- Automated dataset generation with OpenFOAM, producing 2,500+ samples for irregular geometries.
Data Science Intern, O-I Glass, Pittsburgh
- Streamlined workflows by converting Excel models to Python scripts, reducing processing time by 90%.
- Built an end-to-end pipeline using Azure ML, SAP HANA, and Databricks, saving 300+ hours annually.
- Created CO2 emission models, aiding executive leadership in sustainability strategies.
Energy Analyst, ICF Consulting
- Contributed to energy models showing pathways to reduce India’s import bill by $20B.
- Specialized in hydrogen adoption studies, receiving the prestigious ‘Bronze Award.’
Key Projects
- Physics-Informed Diffusion Models for Physics-Based Data Generation
- Integrated physical constraints into denoising diffusion models, improving adherence to governing equations by 20%.
- Fine-tuning LLaVA for Scientific Visual Question Answering
- Adapted multimodal models for scientific imagery and charts, achieving 92.5% accuracy on Science QA datasets.
- Retrieval-Augmented Generation (RAG) for Factual Q&A
- Built a factual Q&A pipeline combining document retrieval and LLMs, optimizing for relevance and reducing hallucinations.
- Reinforcement Learning for Portfolio Management
- Developed a time-series forecasting model for financial decision-making using advanced RL techniques.
Skills
| Category | Skills |
|---|---|
| Languages | Python, C++, SQL, LaTeX, Julia |
| Machine Learning | Scikit-learn, TensorFlow, PyTorch, CUDA, Azure ML, OpenFOAM |
| NLP | Hugging Face Transformers, LangChain, Generative AI, Retrieval-Augmented Generation |
| Data Visualization | PowerBI, Streamlit |
| Cloud Platforms | AWS, GCP, Databricks |
| Other Tools | Excel, PowerPoint, wandb |
Publications
Co-authored 8 research papers in journals and conferences on optimization and CFD, achieving 26 citations. Google Scholar
Interests
- Research Areas: Generative AI, Physics-Informed ML, NLP, and Reinforcement Learning.
- Personal Interests: Passionate about AI applications in engineering and beyond, leveraging AI to solve real-world challenges.