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Dr. Subramanian Ramamoorthy  



Subramanian Ramamoorthy is a Lecturer (Assistant Professor) at the

School of Informatics, University of Edinburgh. He is a member of the

Institute of Perception, Action and Behaviour, and the Informatics

Life-Sciences Institute. He leads Team Edinferno.


Previously, Subramanian worked at the University of Texas and National

Instruments Corp where he was involved with the control design,

dynamic simulation and computer vision groups.


Subramanian’s research is centred on the problem of designing learning

agents that are capable of autonomous decision making to interact with

an incompletely known and continually changing world, motivated by

applications in robotics and agents such as in electronic markets. 

Prof. Sethu Vijayakumar 


Sethu Vijayakumar holds a Personal Chair in Robotics and is the

Director of the Institute of Perception, Action and Behaviour (IPAB)

in the School of Informatics at the University of Edinburgh.


Since 2007, he has been the Microsoft/Royal Academy of Engineering

Senior Research Fellow in Learning Robotics. He also holds additional

appointments as an Adjunct Faculty of the University of Southern

California (USC), Los Angeles, a Visiting Research Scientist at the

ATR Computational Neuroscience Labs, Kyoto-Japan and the RIKEN Brain

Science Institute, Tokyo.


Prof Vijayakumar has pioneered the use of large scale machine learning

techniques for motion control of complex anthropomorphic robotic

systems including the SARCOS humanoid, ASIMO, KUKA robot arm and Nao

mini-humanoids. He has over 100 scientific publications in the field

and holds several grants from Research Councils, EU and industry that

support his research. Currently Prof. Vijayakumar is exploring ways in

which robots can assist people with physical disabilities.

Team Members 

I am researching how to form causal models of an opponent through intervention tactics to improve interaction shaping. In particular, I am interested in how efficient strategies may be learnt from experience by understanding the causal relationships between observed events and performed actions. The context is robot football, where a player may need to learn effective actions that can reliably shape the interaction between the agents in the field.
4th year PhD student focused on improving robots ability to perceive semantic classes such as in gesture or activity recognition. Within the context of Robocup, he is the primary developer of the perception and localization modules.
  • Nantas Nardelli
  • Gwendolijn Schropp 
  • Mariela De Lucas Alvarez
  • Stanislav Manilov
  • Iris Kyr
  • Svetlin Penkov
  • Kshitij Tiwari



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