Harnessing control and systems theory to understand complex living systems

Professor Daniel Coca, The University of Sheffield

It has long been argued that control and systems theory provides the ideal framework to elucidate regulatory mechanisms and structures underlying biological function at different levels of biological organization from organelle to organism. To quote Arnold Tustin, feedback “is the fundamental principle that underlies all self-regulating systems, not only machines but also the processes of life and the tides of human affairs”.

The first part of this talk will demonstrate how existing methods and tools in control, nonlinear systems and information theory, including system identification, higher-order frequency response and rate-distortion analysis, can be combined with remarkable experimental approaches to elucidate gain adaptation mechanisms and the role of nonlinearity in early visual processing.

The second part will show how the quest for understanding cell fate determination of human embryonic stem cells leads to the formulation of new theoretical control and systems theory problems.

Biography

Daniel Coca received the MEng degree in Electrical Engineering from Transilvania University of Brasov, Romania, in 1993 and the PhD degree in Control Engineering from the University of Sheffield, UK in 1997. Between 1997-2002 he was Research Fellow in the Department of Automatic Control and Systems Engineering at the University of Sheffield. From 2002 to 2004 he was University Lecturer in the Department of Electrical Engineering and Electronics at the University of Liverpool. In 2004 he rejoined the Department of Automatic Control and Systems Engineering first as a lecturer and since January 2011 as Full Professor. He is currently serving as Head of Department and Director of the Centre of Complex Systems and Signal Processing.  His research interests include modelling, analysis, and control of complex systems, inverse problems, mathematical theory of neural computation and signal processing. Application areas include stem cell biology, stem cell manufacturing, brain modelling, urban sensing and automation, infrastructure systems.