Summary
Joe Eappen is a PhD candidate and graduate assistant at Purdue University specializing in multi-agent systems, specification-guided learning, and safe reinforcement learning, with 11 years of experience spanning research and applied ML. He combines deep academic training from IIT Madras (BTech & MTech) with practical industry experience—internships at JPMorgan Chase, Synopsys, and IBM—building ML frameworks for circuit behavior prediction, offline RL, and NLP. His work at C-BRIC and SRC focused on robustness and safety in RL, bridging theory to deployable solutions. Comfortable across research and engineering contexts, he has repeatedly moved ideas from prototype to production-grade code and is open to roles starting early 2026. An understated strength is his cross-domain fluency: electrical engineering foundations inform his approach to machine learning for systems and hardware-aware applications.
11 years of coding experience
4 years of employment as a software developer
Indian Institute of Technology Madras
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Purdue University
English, Malayalam, Tamil, French