CV
Resume pdf
Basics
| Name | Vani Nigam |
| Label | AI & Materials Engineering Graduate Student |
| vnigam@andrew.cmu.edu | |
| Phone | +1 (412) 606-1243 |
| Url | https://www.linkedin.com/in/vani-nigam |
| Summary | Graduate student specializing in Artificial Intelligence for Materials Engineering, with experience in machine learning, polymer informatics, time-series analysis, and AI agent orchestration. |
Work
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2024.05 - 2024.07 Summer Research Intern
Indian Institute of Technology Bombay
Conducted scientometric and machine-learning-driven analysis of global research on catalysts and hydrogen storage materials.
- Analyzed 6,000+ research papers using Python, R, BibExcel, and VOSviewer
- Applied spaCy NLP models for citation and trend extraction
- Developed statistical indices for catalyst-class comparison using regex-based methods
Volunteer
-
2025.09 - Present United States
Voluntary Researcher
Human-Computer Interaction Center (HCI)
Worked on psychologically adaptive conversational AI systems for real-time human–robot interaction.
- Developed LangChain-based RAG architecture
- Enabled role-shifting conversational behavior using GPT APIs
Education
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2024.08 - 2026.12 Pittsburgh, PA, USA
Master's
Carnegie Mellon University
Artificial Intelligence in Materials Engineering
- Systems and Tool Chains
- Machine Learning for Engineers
- Generative AI
- Introduction to Deep Learning
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2021.08 - 2025.04 Odisha, India
Bachelor's
Indian Institute of Technology Bhubaneswar
Metallurgy and Materials Engineering
- Numerical Methods
- Simulation and Modelling
- Industrial Manufacturing
- Corrosion and Surface Engineering
- Elements of Electroceramics
- International Business
- Intro to Economics
Publications
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2025.01.01 A Confluence of Emerging Technologies: IoT, Edge and Cloud Computing, Blockchain, Industry 4.0 & 5.0, AI and ML toward the Realization of Eco-Friendly Supercapacitors
American Chemical Society
A comprehensive study exploring the convergence of emerging technologies for sustainable energy storage systems.
Skills
| Machine Learning & AI | |
| Python | |
| TensorFlow | |
| PyTorch | |
| Keras | |
| Scikit-learn | |
| LangChain | |
| spaCy | |
| HuggingFace Transformers | |
| DeepChem |
| Data & MLOps | |
| SQL | |
| Docker | |
| Neo4j | |
| PySpark | |
| Kafka | |
| MosaicML | |
| Model Context Protocol |
| Scientific Computing | |
| LAMMPS | |
| MATLAB | |
| Numerical Simulation | |
| Time-Series Analysis | |
| EEG Classification |
Languages
| English | |
| Fluent |
Interests
| AI for Materials Science | |||||
| Polymer Informatics | |||||
| Generative Models | |||||
| Scientific Machine Learning | |||||
| Autonomous AI Agents | |||||
Projects
- 2025.09 - Present
Agent Orchestration for Polymer Property Prediction
Developed an intelligent AI agent for polymer design and property prediction using LLMs and pretrained transformer models.
- Integrated TransPolymer for SMILES validation
- Used FastMCP server and finetuned Molecule Chef
- Enabled automated property prediction and molecular modification
- 2024.04 - 2025.04
Time Series Classification with Deterministic Learning
Bachelor’s thesis focused on EEG classification using RBF neural networks and wavelet-based feature extraction.
- Trained on 2,000+ EEG time-series samples
- Improved classification accuracy from 50% to 72%