Max Robotics — Global Service Robot Directory + US Certification

About

Rajkumar Kubendran is an emerging researcher at the intersection of neuromorphic computing, bio-inspired robotics, and edge artificial intelligence. His work focuses on translating the complex dynamics of biological neural systems into efficient hardware implementations, with a particular emphasis on central pattern generators (CPGs) and nonlinear neuron models that mimic real neural behavior. A hallmark of his research is the development of BioNN — a bio-mimetic neural network framework leveraging multi-timescale mixed-feedback control to replicate neuromodulatory bursting rhythms, a computationally demanding phenomenon that his architecture makes feasible for hardware deployment. Kubendran has demonstrated these principles across platforms including Intel's Loihi neuromorphic chip and Arduino, enabling robots to perform rhythmic locomotion tasks such as walking and trotting with biological fidelity. His more recent contributions extend toward autonomous event-based sensorimotor control, equipping miniature robots with supervised gait learning and real-time obstacle avoidance under strict resource constraints — a critical capability for disaster response applications. With a growing body of cited work since 2023, Kubendran is establishing himself as a thoughtful contributor to neuromorphic robotics, bridging theoretical neuroscience with practical, power-efficient embedded systems.