Imran Hameed

About

Imran Hameed is a rising leader in bio-inspired robotics, specializing in the design and control of agile, energy-efficient underwater robots. His research centers on biomimetic propulsion, nonlinear bistable mechanisms, and deep reinforcement learning for robotic swimmers. Hameed’s major contributions include the development of a controllable nonlinear bistable “fishtail” that dramatically boosts maneuverability and energy efficiency in robotic swimmers—a breakthrough highlighted in his most-cited work (10 citations). He also pioneered performance-oriented design for multijoint robotic tadpoles, achieving lower energy costs and higher speeds (6 citations), and introduced untethered bimodal robotic fish with tunable bistability for versatile motion (2 citations). His work on deep reinforcement learning has enabled robots like the BCFbot to learn multiple undulatory patterns from a single control scheme, advancing adaptive autonomy (4 citations). With over 25 total citations and publications in top venues from 2022 to 2025, Hameed’s innovations are shaping the next generation of underwater robotics for exploration, monitoring, and environmental tasks.

Research Focus

Key Achievements

Top Papers

1. 1
   A Controllable Nonlinear Bistable “Fishtail” Boosting Robotic Swimmer with Excellent Maneuverability and High Energy Efficiency

   10 citations · 2024
2. 2
   Performance‐Oriented Understanding and Design of a Robotic Tadpole: Lower Energy Cost, Higher Speed

   6 citations · 2024
3. 3
   Deep reinforcement learning enabling a BCFbot to learn various undulatory patterns

   4 citations · 2025
4. 4
   Training Dynamic Motion Primitives using Deep Reinforcement Learning to Control a Robotic Tadpole

   3 citations · 2022
5. 5
   Untethered Bimodal Robotic Fish with Tunable Bistability

   2 citations · 2024

Key Collaborators

Contact & Links