Abhronil Sengupta

About

Abhronil Sengupta is a pioneering researcher at the intersection of brain-inspired computing, robotics, and energy-efficient systems. His work spans two transformative domains: neuromorphic computing using complex oxides and intelligent robotic control via bio-signal processing. In his highly cited 2022 review on complex oxides for brain-inspired computing (65 citations), Sengupta explores how these electronic ceramics can emulate neural computation, offering a path toward hardware that mimics the brain’s remarkable efficiency. Earlier, he made significant contributions to robotics by developing energy-efficient trajectory planning methods using swarm intelligence, such as invasive weed optimization (29 citations). His groundbreaking work on EEG-controlled robotic systems (16 and 14 citations) demonstrates how motor imagery signals can wirelessly guide mobile robots, enabling private, brain-machine interfaces. Sengupta’s research uniquely bridges materials science, artificial intelligence, and robotics, achieving a total impact of over 130 citations. His innovative fusion of complex oxides with neuromorphic principles positions him at the forefront of next-generation computing, while his EEG-based control systems pave the way for assistive technologies and human-robot collaboration.

Research Focus

Key Achievements

Top Papers

1. 1
   Complex Oxides for Brain‐Inspired Computing: A Review

   65 citations · 2022
2. 2
   Energy efficient trajectory planning by a robot arm using invasive weed optimization technique

   29 citations · 2011
3. 3
   EEG controlled remote robotic system from motor imagery classification

   16 citations · 2012
4. 4
   Implementation of EEG based control of remote robotic systems

   14 citations · 2011
5. 5
   Application of Swarm Intelligence to a Two-Fold Optimization Scheme for Trajectory Planning of a Robot Arm

   6 citations · 2011

Key Collaborators

Contact & Links