We are a team of scientists and engineers who are passionate about nature, technology, and anything that bridge them.
Lecturer (US equiv. Assistant Professor) in Neural Engineering & Bio-robotics
Imperial College London, Department of Bioengineering, London, UK
Experience Research Scientist, HHMI Janelia Research Campus, USA Research Associate, HHMI Janelia Research Campus, USA Postdoctoral Fellow, Harvard University, USA PhD, Tufts University, USA Teaching Animal Locomotion & Bioinspired Robotics [Y4 & Master] Systems Physiology: Neuroscience for Engineers [Master] Biomimetics [Y4 & Master] Contact: email@example.com
My research focuses on the visual control of insect flight behaviours, especially during predatory chases. I am interested in the control systems that guide predators during attacks and how animals balance competing navigational requirements (e.g. between hitting a target and avoiding an obstacle).
My research focuses on sensory systems and behaviour; specifically, flight control and stability in insects. I use electrophysiological techniques to study the encoding mechanisms of mechanosensors as well as ethological approached to link the function of these structures with flight behaviour. I am also interested in the diversity and evolution of flight and how interactions between morphology and behaviour have contributed to the co-evolution of body and brain.
My project investigates the signal encoding rules of visuomotor information.
Keywords: Dragonfly, vision, visual guidance and navigation, electrophysiology, visuomotor integration, software development.
I am interested in the function and biomechanics of mechanosensors on insect wings. Insect flight requires a high temporal resolution of the sensors as the wing state changes rapidly during flight. I am using computational methods (CFD and FSI) to understand how mechanosensory feedback could contribute to flight control.
My research focuses on the application and implementation of insect vision (as computational models) in machine vision, to develop bio-inspired low-cost visual navigation, guidance and control strategies for unmanned mobile systems.
My project focuses on the electrophysiological preparations to study mechanosensors on the dragonfly’s wings. The work will contribute to the understanding of the neural representation of aeroelasticity.
My work explores the effects of close proximity formation/swarm flying on UAS flight parameters derived through bio-inspired deep reinforcement learning.
Keywords: Deep reinforcement learning, bio-inspired, and swarm behaviour.
Want to work with us?
Matthew Coles, Master project student 2020 [machine learning]
Mingyi Wang, Master project student 2020 [machine learning]
Kwayne Teo, Master project student 2020 [robotics]
Ray Ng, Master project student 2020 [electrophysiology instrumentation]
Joseph Fabian, Postdoc 2018 & 2019 [neuroscience]
Jill Ueng, MEng project student 2019 [photogrammetry]
Adel Haddad, MEng project student 2019 [computational neuroscience]
Lukas Hann, UROP project student 2019 [robotics]
Xianglu Xiao, MSc project student 2018 [electrophysiology instrumentation]
Sumaya Rahman, MEng project student 2018 [computational mechanics]
Shao-Tuan Chen, Visiting PhD student 2018 [structural mechanics]
Areg Nzsdejan, UROP project student 2018 [robotics]
Julie Zhang, Summer intern student 2018 [animal behaviour]
Hannah Hashem, Summer project student 2018 [general instrumentation]
Jack McKeon, Summer project student 2018 [VR experience]
Linnea Evanson, Summer project student 2018 [image analyses]