About
Building AI that can be trusted, not just used.
Vishwakarma University, Pune · B.Tech, Artificial Intelligence & Data Science · Class of 2027
I am Kundan Sagar Bedmutha — a fourth-year AI researcher at Vishwakarma University, Pune, graduating in 2027. My research investigates one central question: how do we build AI systems that are not just accurate but trustworthy, explainable, and accountable?
Across research submitted to IEEE conferences and IGI Global book chapters — spanning Explainable AI, Multi-Agent Reinforcement Learning, Large Language Models, Neuro-Symbolic AI, Ethical AI, NLP, Healthcare AI, and Quantum-Classical Computing — I've approached this question from every angle simultaneously, with 6+ papers already published.
Beyond research, I've been working as an AI research intern at Novae Healthcare, Pune, since June 2026, applying machine learning and predictive modelling to pharmaceutical drug discovery.
My undergraduate years at Vishwakarma University have been as much about learning how to learn as learning AI itself — coursework in machine learning, deep learning, and data structures built the fundamentals, while independent research taught me how to design experiments, write for peer review, and iterate through rejection. Along the way I've developed hands-on skills in explainable AI, multi-agent systems, LLM tooling and RAG pipelines, and end-to-end ML engineering — built less in lecture halls and more by shipping research and code.
Research Philosophy
"How do we build AI systems that are not just accurate, but trustworthy, explainable, and accountable?"
Current Position
AI Research Intern — Drug Discovery
Novae Healthcare Pvt Ltd · Pune, India · June 2026 – Present
Academic Journey
Four years, one thread
B.Tech in Artificial Intelligence & Data Science at Vishwakarma University — coursework, skills, and CGPA progress by year.
Programming fundamentals in Python and C++, Data Structures, Discrete Mathematics, Calculus for AI, and Digital Logic Design — building my first models and understanding how software systems are structured. First hands-on introduction to machine learning through self-study.
Machine Learning fundamentals, Statistics & Probability, Database Systems, Algorithms, and Linear Algebra for AI. Deepened core ML theory and began applying it to independent projects.
Deep Learning, Natural Language Processing, Reinforcement Learning, Explainable AI, and Cloud Computing. Began independent research collaboration with Prof. Rajkumar Jagdale — went on to publish 6+ papers at IEEE conferences and IGI Global, and started an AI Research Internship at Novae Healthcare.
Trading the classroom for the lab and the clinic problem set — applying AI to real drug discovery pipelines as an AI Research Intern at Novae Healthcare, alongside continued research collaboration with Prof. Rajkumar Jagdale and final-year coursework.
Current CGPA
Through Semester 6 · B.Tech AI & Data Science
Academic Profiles