Navya Narula
Graduate Teaching Assistant @ Virginia Tech Bradley Department of Electrical & Computer Engineering
About
I'm a Computer Engineering grad student at Virginia Tech (GPA: 3.88) who builds end-to-end AI systems — from research to deployment. In the past year, I've fine-tuned T5 for reverse prompt engineering (↑18% BLEU, ↑15% ROUGE-L), built a multi-agent LLM orchestration system with LangChain + LangGraph + RAG on FAISS, and deployed a real-time emotion recognition app on Azure with P95 latency under 100ms. These are projects I scoped and shipped on my own — they're not class assignments. My stack spans the full ML arc: Python · PyTorch · TensorFlow · LangChain · LangGraph · AWS · Azure · Docker · Airflow · FastAPI. I'm equally comfortable in research-heavy and production-oriented environments, and I pick up new frameworks fast. Published on IEEE Xplore: benchmarked ConvNext on ImageNet-1K, ImageNet-22K, and CIFAR-10. Graduating in 2026 and actively exploring full-time AI/ML engineering roles. Open to connecting with engineers, researchers, and hiring teams. 📬 narulanavya3@vt.edu
United States
Boston
Computer Software
RAG, FastAPI, Model Deployment, Vector Databases, LLM Fine-tuning, MLOps, Agentic AI, Retrieval-Augmented Generation (RAG), LangChain, LangGraph, FAISS, Transformers, Reinforcement Learning, OpenAI Gymnasium, Stable Baselines3, NLP Security, TextBlob, Deep Learning, Large Language Models (LLM), Prompt Engineering
Experience
Graduate Teaching Assistant
Virginia Tech Bradley Department of Electrical & Computer Engineering
Blacksburg, VA
Support 40+ students weekly across lab sessions and office hours for an ECE course at Virginia Tech; responsibilities include circuit troubleshooting, grading technical lab reports, and helping students debug hands-on assignments throughout the semester
Machine Learning Intern
iHUB DivyaSampark @ IIT Roorkee
India
Built an end-to-end climate forecasting pipeline delivering precipitation predictions via Flask API to support drought risk indicators and irrigation planning; developed using Python, TensorFlow, and Scikit-learn with workflow orchestration on AWS S3 and Apache Airflow; added automated ETL and distribution-shift checks on seasonal features to flag performance issues from changing input patterns
AI/ ML Mentee @Microsoft Engage'22
Microsoft
Built Emotion2Rec, a real-time desktop app analyzing facial expressions to deliver emotion-aware Spotify recommendations; improved emotion classification accuracy by 12% through a CNN-based deep feature-learning pipeline with targeted fine-tuning and preprocessing; deployed on Azure via Flask APIs achieving P95 inference latency under 100ms
Education
Virginia Tech
Computer Engineering
Relevant Courses- Deep Learning, Deep Reinforcement Learning, Trustworthy Machine Learning, Advanced Machine Learning, Computer Vision, Data Engineering, Applications of Machine Learning
Maharaja Agrasen Institute Of Technology, Delhi
Electronics and Communications Engineering
St. Xavier School - Delhi
Navya Narula's Contact Information
Phone
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