Papers
12
Total Citations
237
H-Index
9
About
Manish Sreenivasa is a computational researcher whose work bridges movement neuroscience, biomechanics, and robotics, with particular expertise in human motion modeling, exoskeleton design, and humanoid robot control. His most impactful contributions lie in the development of predictive simulations for wearable robotic systems, particularly lower-back exoskeletons aimed at reducing workplace injury risk. Through optimal control frameworks and parameter identification methods, his research helps engineers anticipate how exoskeletons influence wearer movement — work reflected in his most-cited papers (45 and 43 citations respectively), which have become key references in the exoskeleton design community. Earlier in his career, Sreenivasa made significant strides in humanoid robotics, developing methods for real-time human-to-robot motion transfer, human-like reaching based on movement primitives, and intuitive robot guidance through head steering — demonstrating a consistent interest in biologically inspired control strategies. His yoyo-playing humanoid study showcased an elegant fusion of motion capture, dynamic modeling, and optimal control. More recently, his editorial work on neuromechanics and bio-inspired technologies (23 citations) reflects a broader ambition to unify disciplines traditionally siloed from one another. With nearly a decade of cross-domain contributions, Sreenivasa's research offers valuable insights for students exploring the intersection of human movement science and intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Motion optimization and parameter identification for a human and lower-back exoskeleton model43 citations · 2017
- 3
- 4ON REAL-TIME WHOLE-BODY HUMAN TO HUMANOID MOTION TRANSFER24 citations · 2010
- 5
- 6Steering a humanoid robot by its head18 citations · 2009
- 7
- 8
- 9Humanoid human-like reaching control based on movement primitives12 citations · 2010
- 10