Biomedical Signal and Image Processing, Machine Learning, Brain Computer Interface
Designation: Associate Professor
Email: email@example.com, firstname.lastname@example.org
Specialization: Biomedical Signal and Image Processing, Machine Learning, Brain Computer Interface
Dr. Upadhyay is working with Electronics and Communication Engineering Department, Thapar Institute of Engineering and Technology, Patiala since June-2016. He recently completed his Post-Doctoral research work from Reillylab (http://reillylab.net) in Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland. Dr. Upadhyay has obtained his Master’s and the Ph.D. degree in the area of Biomedical Signal Processing (BSP) and Machine Learning (ML) for Brain Computer Interface (BCI) design from the discipline of Electronics and Communication, Indian Institute of Information Technology, Jabalpur (M.P.), India, in 2013 and 2016, respectively. He has authored more than twenty-five research articles in the peer reviewed journals and reputed conference proceedings. He serves on the review boards for various journals of IEEE, Elsevier, Springer and Wiley. He has supervised four Master’s dissertations and currently supervising four Ph.D. students in TIET, Patiala.
• Artificial Intelligence and Deep Learning
• Biomedical Signal and Image Processing
• Brain Computer Interface
• Neural Engineering
• Machine Learning
• Data Structures and Algorithms
• Signals and Systems
• Microcontroller and Embedded System
• Embedded Systems
• Control System
• Organised “2019 International Workshop on Artificial Intelligence and Deep Learning methods for Human Centric Systems (AIDL-HCSy)” in the 11th International Congress on Ultra-Modern Telecommunications and Control Systems, Dublin, Ireland.
• Technical Program Committee member in the “International Conference on Advances and Applications of Artificial Intelligence and Machine Learning (ICAAAIML' 2020)”, Greater Noida, India.
• International advisory committee member “2nd International Conference on Advancing Knowledge from Multidisciplinary Perspectives in Engineering & Technology. June-2020”, Istanbul, Turkey.• Advisory committee member “International Conference on Emerging Technology in Electrical and Electronics Engineering (ICETEEE), Feb-2020”, Jaipur, India.
• Recognised as mentor in Atal Innovation Mission (a Govt. of India initiative) since May, 2018.
• Outstanding contribution in reviewing award from “Computers and Electrical Engineering”, Elsevier.
• Outstanding contribution in reviewing award from “International Journal Engineering Science and Technology”, Elsevier.
• Organised “2018 International Workshop on Artificial Intelligence and Deep Learning methods for Human Centric Systems (AIDL-HCSy)” in the 10th International Congress on Ultra-Modern Telecommunications and Control Systems, Moscow, Russia.
• Received the best paper in 12th IEEE India International Conference (INDICON), 2015.
• Best hardware project award in national seminar, held at SRIT, Jabalpur, M.P.
• Ministry of Human Resource & Development (India) fellowship holder for M.Tech Program.
• Ministry of Human Resource & Development (India) fellowship holder for Ph.D. Program.
Publications in refereed SCI/SCIE journals (Recent):
1) D. Singh, R. Upadhyay, H.S. Pannu, D. Leray, “Development of an Adaptive Neuro Fuzzy Inference System based Vehicular Traffic Noise Prediction Model”, Journal of Ambient Intelligence and Humanized Computing, 1-17, 2020. DOI: https://doi.org/10.1007/s12652-020-02431-y
2) K. Jindal, R. Upadhyay and H.S. Singh, “Application of Hybrid GLCT-PICA de-noising Method in Automated EEG Artifact Removal”, Biomedical Signal Processing and Control, 60, 101977, 2020.
3) T. Dovedi and R. Upadhyay, “Diagnosis of Ball Bearing Faults using Double Decomposition Technique” International Journal of Acoustics and Vibration, 2019. (Accepted)
4) K. Jindal, R. Upadhyay and H.S. Singh, “Application of tunable-Q wavelet transform based nonlinear features in epileptic seizure detection”, Analog Integrated Circuits and Signal Processing, 2019, https://doi.org/10.1007/s10470-019-01424-y
5) H.S. Singh, R. Upadhyay and R.M. Shubair, “Performances study of compact printed diversity antenna in the presence of user's body for LTE mobile phone applications”, International Journal of RF and Microwave Computer‐Aided Engineering, 2019, DOI: 10.1002/mmce.21743
6) S. Sethi, R. Upadhyay and H.S. Singh, “Stockwell-Common Spatial Pattern Technique for Motor Imagery based Brain Computer Interface Design”, Computers and Electrical Engineering, 71, 492-504, 2018.
7) H.S. Singh, R. Upadhyay and R.M. Shubair, “Free space and user proximity analysis of octaband monopole MIMO/diversity antenna for modern handset applications”, International Journal of RF and Microwave Computer‐Aided Engineering, e21566, 2018.
Papers in Conference Proceedings (selected)
1) H. Kaur, H.S. Singh, R. Upadhyay, “Simulation Study of Quasi Self-Complementary Shared-Radiator for UWB-MIMO Applications”, IEEE Indian Conference on Antennas and Propogation (InCAP), 1-4, 2019.
2) K. Jindal, R. Upadhyay and H.S. Singh, “EEG artifact removal and noise suppression using hybrib GLCT-ICA technique”, 10th International Congress on Ultra-Modern Telecommunications and Control Systems and Workshops, Russia, 2018.
3) K. Jindal, R. Upadhyay, H.S. Singh, M. Vijay, A. Sharma, K. Gupta, J. Gupta and A. Dube, “Migraine disease diagnosis from EEG signals using Non-linear Feature Extraction Technique”, IEEE ICCIC, 2018.
4) K. Jindal, R. Upadhyay, “Epileptic Seizure Detection from EEG Signal using Flexible Analytical Wavelet Transform”, IEEE International Conference on Computer, Communications and Electronics (Comptelix), 2017. S. Shruti, R. Upadhyay, “Classification of Mental Tasks Using S-Transform based Fractal Features”,IEEE International Conference on Computer, Communications and Electronics (Comptelix), 2017.
6) R. Upadhyay, P.K. Padhy and P.K. Kankar, “Ocular artifact removal from EEG signals using Discrete Orthonormal Stockwell Transform”, Annual IEEE India Conference (INDICON), 2015.
7) R. Upadhyay, P.K. Padhy, P.K. Kankar, “Alcoholism diagnosis from EEG signals using continuous wavelet transform”, Annual IEEE India Conference (INDICON), 2014.