Papers
13
Total Citations
110
H-Index
6
About
Heramb Nemlekar is a robotics researcher whose work lies at the intersection of human-robot interaction, assistive robotics, and multi-agent coordination. His most impactful contribution, "Object Transfer Point Estimation for Fluent Human-Robot Handovers" (40 citations), addresses a fundamental challenge in collaborative robotics: enabling robots to accurately predict where a human will hand over an object, making interactions more natural and efficient. Nemlekar has also pioneered methods for robots to learn and adapt to human preferences without requiring tedious demonstrations, as shown in his work on transfer learning for assembly tasks (14 citations). His innovative "Kiri-Spoon" project (10 citations) introduces a soft, shape-changing utensil for robot-assisted feeding, demonstrating a creative approach to assistive technology that could improve quality of life for elderly and disabled individuals. Beyond physical interaction, Nemlekar has explored fairness in AI decision-making through contextual multi-armed bandits (9 citations) and developed hindsight optimization techniques for multi-robot task allocation under uncertainty. His research consistently bridges theoretical advances with practical applications, from agricultural robotics (lime picking) to manufacturing, making him a rising figure in creating robots that work safely, efficiently, and equitably alongside humans.
Research Focus
Key Achievements
Top Papers
- 1Object Transfer Point Estimation for Fluent Human-Robot Handovers40 citations · 2019
- 2
- 3Robotic Lime Picking by Considering Leaves as Permeable Obstacles13 citations · 2021
- 4Kiri-Spoon: A Soft Shape-Changing Utensil for Robot-Assisted Feeding10 citations · 2024
- 5Fair Contextual Multi-Armed Bandits: Theory and Experiments9 citations · 2019
- 6
- 7Multi-Robot Task Allocation Under Uncertainty Via Hindsight Optimization5 citations · 2024
- 8
- 9Kiri-Spoon: A kirigami utensil for robot-assisted feeding2 citations · 2025
- 10