Email: B.P.Das@soton.ac.uk
Medical Signal processing
Brain Connectivity Estimation
Mathematical modelling
Core AI Development
Control system
Sensor and Transducers
Dr. Bed Prakash Das is a Postdoctoral Research Fellow in the School of Electronics and Computer Science at the University of Southampton, United Kingdom, currently contributing to the European Horizon project ETHEREAL. His research focuses on Brain Connectivity Estimation through multimodal biosignal integration, involving EEG and fNIRS and core development in the field of AI/ML driven analysis with causal modelling for ASD adoloscents.
He holds a Ph.D. (Tech.) in Electrical Engineering from the University of Calcutta, where his doctoral research explored Kalman filter variants for indoor thermal environment modeling and estimation under uncertain inputs. His academic journey includes an M.Tech. in Instrumentation and Control Engineering, and a B.Tech. in the same field, graduating with distinction in both.
Dr. Das has over Eight years of academic and research experience, including previous roles as Assistant Professor and Senior Research Fellow under competitive government fellowships. He has led and contributed to multiple state-funded research projects, focusing on intelligent system design, real-time estimation, embedded systems, and sensor-integrated hardware for environmental monitoring and energy efficiency.
His work has resulted in publications in reputed journals such as IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Instrumentation and Measurement and Journal of Building Performance Simulation, alongside numerous IEEE conference proceedings. He is a recipient of the Best Paper Award at IEEE IBSSC 2022 and has earned prestigious research fellowships from the Council of Scientific and Industrial Research (CSIR) and the Department of Science and Technology, Government of West Bengal.
With expertise in MATLAB, Python, C/C++, and microcontroller-based systems (Raspberry Pi, Arduino, PIC), Dr. Das brings a strong interdisciplinary background in estimation theory, AI/ML applications, and control systems. He has supervised undergraduate and graduate research projects, delivered courses in electrical and instrumentation engineering, and remains passionate about mentoring the next generation of researchers.
Dr. Das is committed to advancing impactful, interdisciplinary research at the intersection of signal processing, intelligent systems, and biomedical applications.
