Visakan Kadirkamanathan

Timeline

1. 1987–1992

   Cambridge degree and PhD

   Born in Jaffna, Sri Lanka, he leaves the University of Peradeniya for the UK and graduates from the Engineering Department at Cambridge with a Class I degree in Electrical and Information Sciences in June 1987. He earns a Cambridge PhD in Information Engineering with a 1992 thesis, Sequential learning in artificial neural networks.

2. 1992–1993

   Enhancing the resource allocating network

   In September 1992, he and Mahesan Niranjan issue a Cambridge University Engineering Department technical report on sequential learning with neural networks, published in Neural Computation in 1993. They replace the LMS update of the resource allocating network with an extended Kalman filter, and the enhanced network performs better with fewer hidden units.

3. 1993

   Lecturer at Sheffield

   After brief postdoctoral research positions at Cambridge and Surrey, he joins the Department of Automatic Control and Systems Engineering at the University of Sheffield as a lecturer in January 1993.

4. 2001

   A book on adaptive control

   He and S. G. Fabri publish Functional Adaptive Control: An Intelligent Systems Approach with Springer in 2001.

5. 2007

   Professor of signal processing

   He moves up through senior lecturer and reader to Professor of Signal and Information Processing at Sheffield in 2007.

6. April 2009–August 2014

   Head of Sheffield's control department

   He serves as Head of the Department of Automatic Control and Systems Engineering from April 2009 to August 2014, and the department doubles its size.

7. 2012

   A PNAS Cozzarelli Prize

   One of his research papers wins the 2012 Cozzarelli Prize of the Proceedings of the National Academy of Sciences.

8. As of October 2026

   Director of Rolls-Royce UTC

   He is Professor of Signal and Information Processing in the School of Electrical and Electronic Engineering, which his department joins in 2024, and Director of the Rolls-Royce supported University Technology Centre in Control, Monitoring and Systems Engineering, a post he takes up in July 2012. His research spans system identification, fault detection and signal processing for aerospace, manufacturing and healthcare, with coauthored papers on interpretable deep learning in 2024 and a deep reinforcement learning framework for robotic blood gas analyzers in 2025. Since 2021, he chairs the UK Automatic Control Council.