Dr Chandrasekhar Kambhampati

Reader in Computer Science

+44 (0)1482 465744 | C.Kambhampati@hull.ac.uk

Faculty and Department

Faculty of Science and Engineering
School of Computer Science

Teaching Outputs Research/PhD

Teach on

08131 - Computer Systems

08336 - NEAT

08018 - Trustworthy Computing

08325 - Tutor and PR for year in Industry

Recent outputs

View more outputs

Journal Article

Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure

Kazmi, S., Kambhampati, C., Cleland, J., Cuthbert, J., Kazmi, K. S., Pellicori, P., …Clark, A. L. (2022). Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure, https://doi.org/10.1002/ehf2.14028

Joe Cuthbert

Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection

Gordon, N., Kambhampati, C., & Alabad, A. (2022). Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection. AI, Computer Science and Robotics Technology, 1, 1-21. https://doi.org/10.5772/acrt.01

Neil Gordon

Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease

Alabed, A., Kambhampati, C., & Gordon, N. (in press). Genetic Algorithms as a Feature Selection Tool in Heart Failure Disease. Advances in Intelligent Systems and Computing, 1229 AISC, 531-543. https://doi.org/10.1007/978-3-030-52246-9_38

Neil Gordon

Ionic Imbalances and Coupling in Synchronization of Responses in Neurons

Sadegh-Zadeh, S., Kambhampati, C., & Davis, D. N. (2019). Ionic Imbalances and Coupling in Synchronization of Responses in Neurons. J — Multidisciplinary Scientific Journal, 2(1), 17-40. https://doi.org/10.3390/j2010003

Issues in the mining of heart failure datasets

Poolsawad, N., Moore, L., Kambhampati, C., & Cleland, J. G. (2014). Issues in the mining of heart failure datasets. International Journal of Automation and Computing, 11(2), 162-179. https://doi.org/10.1007/s11633-014-0778-5

Research interests

Over the years I have worked on problems dealing with optimisation, optimal control, learning algorithms, neural networks, and networked control systems as applied to a variety of different applications including Robots, chemical processes and bio systems. I have also worked on problems dealing with walking of robots. More recently I have been working on two problems,one dealing with risk prediction in the clinical domain using live clinical data and the other neurological disorders and computation models from a neurons perspective. AT the same time recently been developing sensors based on photonics for controlling robots