About Me
I am a Ph.D. student in Computer Science at the University of Missouri, advised by Dr. Tanu Malik. My research focuses on Agentic AI Systems, Trustworthy AI, and Reproducibility in Systems. I build systems that reason, plan, and act autonomously — from multi-model orchestration and bandit-based model switching in ML workflows to closed-loop autonomous experimentation platforms. I received an offer from Microsoft for a Research Data Science Internship (Summer 2026).
I am also the creator of LearnLLM.dev, an educational platform with 83+ lessons and 30+ hands-on challenges that teaches LLM development from beginner prompt engineering to production-grade AI agents, serving 10,000+ active learners.
Previously, I completed my M.S. in Computer Science at Missouri, advised by Dr. Jianlin Cheng and Dr. Grant Scott. I received my B.Tech from VIT University (Vellore Institute of Technology), where I worked on multilingual sentiment analysis advised by Dr. Soughbhagya Barpanda, with dataset and collaboration support from Dr. P. Kumaraguru (PRECOG, IIIT Hyderabad).
I was selected as a Google PhD Fellowship Nominee (2025) in NLP, one of three nominees from Missouri, and received the Outstanding Master’s Student Award (2025).
Research Interests: Agentic AI Systems, LLMs, NLP, Trustworthy AI, Autonomous Experimentation, Scalable ML Systems, Reproducibility
News
- 2026.02: My presentation on “Evaluating Dependency Gaps in LLM-Generated Code” was selected for the Sixth Chameleon User Meeting (April 15–16, 2026) at NCAR’s Mesa Lab in Boulder, Colorado
- 2026.01: I presented “AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents” (Jan 26) and “Efficient Multi-Model Orchestration for Self-Hosted Large Language Models” (Jan 27) at AAAI 2026 in Singapore
- 2025.12: Our paper “AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents” was accepted at the RAI 2025 workshop
- 2025.11: Our paper “Efficient Multi-Model Orchestration for Self-Hosted Large Language Models” was accepted at the Deployable Artificial Intelligence (DAI2025) Workshop
- 2025.11: Received an offer from Microsoft for Research Data Science Internship (Summer 2026)
- 2025.05: Graduated with my M.S. in Computer Science and continued to pursue my Ph.D. in Computer Science at Mizzou
- 2025.04: Selected as a Google PhD Fellowship Nominee (NLP) — one of three nominees from the University of Missouri
- 2025.04: Presented our work on hallucination detection at the AAAI Spring Symposium 2025 (AI for Scientific Discovery track)
- 2025.03: Received the Outstanding Master’s Student Award at the Mizzou Engineering Awards Banquet 2025
- 2025.03: Started development of ReflectMemory, focused on persistent memory control for long-context LLM reasoning
- 2025.03: Deployed an updated KubeLLM framework for multi-tenant LLM inference on GPU-based HPC clusters
- 2025.01: Two papers accepted at AAAI 2025, including HalluMat and HalluFormer
- 2025.01: Released benchmarking tools for hallucination detection in scientific LLMs
- 2024.09: Initiated documentation work on scalable LLM-as-a-Service infrastructure using Helm charts and node affinity scheduling
- 2024.01: Working as a TA for over 100 students in a web development course, guiding full-stack app development
- 2023.12: Led deployment of GPU-efficient LLM inference systems in the university’s Kubernetes-based HPC environment (Nautilus)
- 2023.08: Began research on faithfulness, interpretability, and robustness in large generative language models
- 2023.06: Admitted to the Ph.D. program in Computer Science at the University of Missouri
- 2023.05: Graduated with a B.Tech in CSE (Data Analytics) from VIT Vellore
- 2023.04: Honored with the Excellence in Research Award at VIT for multilingual NLP and social media analytics contributions
- 2023.03: Volunteered as an AI Community Evangelist at Adobe, contributing to community education and developer engagement
- 2022.11: Served as an Internshala Student Partner (ISP), leading brand campaigns and peer mentoring on campus
- 2021: Collaborated with the Synergy Team at VIT, supporting student experience initiatives and university development programs
- 2020: Joined the Brandiverse team as a creative contributor, working on outreach and media strategy
Publications
2026
2025
Thesis & Earlier Work
Projects
Honors and Awards
Education
Ph.D. in Computer Science, University of Missouri
Advisor: Dr. Tanu Malik | GPA: 3.9/4.0
Research: Agentic AI Systems, Trustworthy AI, Autonomous Experimentation, Reproducibility
Funded by NASA, NSF, and Department of Defense
M.S. in Computer Science, University of Missouri
Advisors: Dr. Jianlin Cheng, Dr. Grant Scott | GPA: 4.0/4.0
Thesis: Deploying LLM-as-a-Service in Kubernetes HPC Clusters
B.Tech in Computer Science (Data Analytics), VIT Vellore
Thesis: Multilingual Sentiment Analysis on KOO platform
Awards: Dean's Research Excellence Award, Best Thesis Award
Experience
Microsoft — Research Data Science Intern (Offer Received)
University of Missouri, Radiant Lab — Research Assistant
NASA-funded research on reproducible scientific containers, AI-generated code reproducibility, and multi-model orchestration (Pick-and-Spin); work on bandit-based model switching (FlexiFlow) and autonomous experimentation (TRACE)
Advisor: Dr. Tanu Malik
University of Missouri, Data Intensive Computing Lab — Research & Teaching Assistant
DoD/ERDC-funded research on hallucination detection in LLMs (30% improvement); NSF-funded work on LLM-as-a-Service infrastructure
TA for Web Development: mentored 115+ students
Advisors: Dr. Grant Scott, Dr. Jianlin Cheng
Adobe — Volunteer Research Intern
Web scraping and information extraction for NLP team
Academic Service
Reviewer: NeurIPS (Outstanding Reviewer — AI4MAT Track), NeurIPS (Main Track), ICLR, ICML, ACL, AAAI, CIKM, IEEE
Teaching
- Teaching Assistant, Web Development (MERN Stack) — Fall 2025, Fall 2024, Spring 2024, Fall 2023