Summary
AI/ML Engineer & Research Assistant
Building LLM and ML systems across RAG, time-series, computer vision, and SQL-grounded AI.
Principle I build by
"Make the model honest: tie every claim to data."
-- Raaj Patel
Featured
3Focus areas that define my research and engineering lens.
SQL-Grounded RAG
LLM reasoning tied directly to SQL retrieval for auditability.
Cyber-Physical Security
Simulation-backed datasets for DER anomaly and intrusion detection.
IEEE Publication
Forest fire severity detection pipeline published on IEEE Xplore.
Projects
4Four high-impact projects that highlight LLM systems, cyber-physical security, and computer vision research.
AI Expense Tracker with RAG-Enhanced Financial Reasoning
- ●Problem: Financial queries need trustworthy, non-hallucinated answers grounded in real data.
- ●Built: Full-stack system converting natural language -> SQL -> retrieved context -> grounded explanations.
- ●Built: RAG pipeline where all numerical values are strictly fetched from SQLite (LLM used only for reasoning).
- ●Built: Provider-swappable LLM architecture (Ollama local, OpenAI, Groq, HuggingFace, vLLM).
- ●Built: CRUD APIs, analytics SQL, budget vs actual analysis, anomaly detection, plus schema/index tuning.
DER Cyberattack Detection Platform
- ●Built: End-to-end DER simulations combining electrical telemetry and cyber events.
- ●Built: Modeled false data injection, spoofing, and command manipulation attacks.
- ●Built: Generated ML-ready labeled datasets for anomaly and intrusion detection.
Tiny LLM for Anomaly Pattern Learning
- ●Built: Evaluated lightweight open-source LLMs to learn normal vs anomalous telemetry patterns.
- ●Built: Prompt-based classification optimized for low-latency inference and rapid triage.
Forest Fire Severity Detection (IEEE Xplore)
- ●Built: End-to-end computer vision pipeline using PyTorch and OpenCV.
- ●Built: Applied preprocessing, augmentation, training, and evaluation.
Experience
3Research and industry roles focused on AI systems, simulation, and engineering delivery.
Research Assistant (AI & Cyber-Physical Systems) · Purdue University Northwest
Jul 2025 - PresentAdvisor: Prof. Shafkat Islam
- ●Designing AI-driven detection pipelines for cyberattacks in Distributed Energy Resource (DER) systems.
- ●Building OpenDSS-based IEEE 13-bus and 123-bus simulations with integrated PV/BESS assets for controlled anomaly studies.
- ●Creating reproducible datasets and evaluation pipelines to support research-grade ML experimentation and reporting.
Business Assistant & Technical Contributor · Navarang Engineering Works
Jul 2024 - Jul 2025- ●Built and deployed the company website (navarang.com) and introduced lightweight digital tooling to improve operations.
Engineering Intern · Einfochips (Arrow Electronics)
Jan 2024 - May 2024- ●Supported AI and embedded workflows via Linux-based scripting, debugging, and structured testing.
Education
2Graduate and undergraduate training with a focus on AI/ML systems.
M.S. in Computer Science
Expected May 2027Purdue University Northwest, Hammond, IN
GPA: 3.7 / 4.0B.Tech in Information and Communication Technology
2024Pandit Deendayal Energy University (PDEU), Gandhinagar, India
GPA: 9.68 / 10 CGPASkills
8A balanced stack across AI/ML, LLM systems, and production-ready engineering.
Languages
AI-ML
LLM Systems
Backend
DB
Systems
Frontend
Cloud
Publications
1Peer-reviewed work that demonstrates research rigor and delivery.
Now
What I am focused on this semester.
- ●Building simulation-backed DER security datasets
- ●Improving grounded RAG evaluation
Contact
Open to AI/ML engineering roles, research collaborations, and high-impact projects.