Deepak Gupta

About

Dr. Deepak Gupta is Assistant Professor in the Department of Computer Science & Engineering of Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India. Previously he has worked in the Department of Computer Science & Engineering of National Institute of Technology Arunachal Pradesh. He received the Ph.D. degree in Computer Science & Engineering from the Jawaharlal Nehru University, New Delhi, India. His research interests include support vector machines, ELM, RVFL, KRR and other machine learning techniques. He has published over 70 referred journal and conference papers of international repute. His publications have more than 1300 citations with an h-index of 21 and i10-index of 44 (Google Scholar, 06/06/2023). He is currently the member of an editorial review Board member of Applied Intelligence. He is the recipient of the 2017 SERB-Early Career Research Award in Engineering Sciences which is the prestigious award of INDIA at early career level. He is a senior member of IEEE and currently an active member of many scientific societies like IEEE SMC, IEEE CIS, CSI and many more. He has served as a reviewer of many scientific journals and various national and international conferences. He was the General Chair of 3rd International Conference on Machine Intelligence and Signal Processing (MISP-2021) and associated with other conferences like IEEE SSCI, IEEE SMC, IJCNN, BDA 2021 etc. He has supervised 3 PhD students and currently 3 PhD students are enrolled under him. He is currently the Principal Investigator (PI) or Co-PI of 02 major research projects funded by the Science & Engineering Research Board (SERB), Government of India.

Employment

• Motilal Nehru National Institute of Technology Allahabad Assistant Professor
  2023 - Present
• National Institute of Technology Arunachal Pradesh Assistant Professor
  2016 - 2023
• IMS Engineering College Assistant Professor
  2011 - 2016

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (41)

• Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks
  Applied Soft Computing Journal 2020 DOI: 10.1016/j.asoc.2020.106626
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• A coiflet LDMR and coiflet OB-ELM for river suspended sediment load prediction
  International Journal of Environmental Science and Technology 2020 DOI: 10.1007/s13762-020-02967-8
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• Unconstrained convex minimization based implicit Lagrangian twin extreme learning machine for classification (ULTELMC)
  Applied Intelligence 2020 DOI: 10.1007/s10489-019-01596-0
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• Robust regularized extreme learning machine with asymmetric Huber loss function
  Neural Computing and Applications 2020 DOI: 10.1007/s00521-020-04741-w
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• Modeling suspended sediment load in a river using extreme learning machine and twin support vector regression with wavelet conjunction
  Environmental Earth Sciences 2020 DOI: 10.1007/s12665-020-08949-w
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• Lagrangian twin parametric insensitive support vector regression (LTPISVR)
  Neural Computing and Applications 2020 DOI: 10.1007/s00521-019-04084-1
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• Functional iterative approaches for solving support vector classification problems based on generalized Huber loss
  Neural Computing and Applications 2020 DOI: 10.1007/s00521-019-04436-x
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• End-to-End Analysis for Text Detection and Recognition in Natural Scene Images
  Proceedings of the International Joint Conference on Neural Networks 2020 DOI: 10.1109/IJCNN48605.2020.9207001
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• Efficient implicit Lagrangian twin parametric insensitive support vector regression via unconstrained minimization problems
  Annals of Mathematics and Artificial Intelligence 2020 DOI: 10.1007/s10472-020-09708-0
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• Density-weighted support vector machines for binary class imbalance learning
  Neural Computing and Applications 2020 DOI: 10.1007/s00521-020-05240-8
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