Smriti Srivastava

About

Prof. Smriti Srivastava received B.E. degree in Electrical Engineering and the M.Tech. degree in Heavy Electrical Equipment from MANIT Bhopal, India, in 1987 and 1991, respectively, and Ph.D. degree in Intelligent Control from Indian Institute of Technology (IITD) New Delhi, India, in 2005.Since August 1991, she has been with the Department of Instrumentation and Control Engineering, Netaji Subhas University of Technology (Erstwhile NSIT, University of Delhi), New Delhi, India, where she is presently working as Professor in the Deptt. of Instrumentation and Control Engineering,from September 2008 to till date. She has over 150 publications in International Journals and Conferences in the areas of AI,ML,Neural Networks, Fuzzy logic,Control Systems and Biometrics. Her current research interests include neural networks, fuzzy logic, and hybrid methods in modeling, identification and control of nonlinear systems and Biometrics.She is the reviewer of IEEE Transactions on Systems, Man and Cybernetics (SMC), Part-A. IEEE Transactions on Fuzzy Systems, Journal of Applied Soft Computing, Neurocomputing, ISA Transactions (Elsevier), Softcomputing, Neural Computing and Applications (Springer).

Employment

• Netaji Subhas University of Technology PROFESSOR
  1991 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (127)

• Modeling, Design and Automation of Optimized Control Strategies for Enhanced Brushless DC Motor Performance
  Journal of Circuits, Systems and Computers 2026 DOI: 10.1142/S0218126626501689
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• Brain Tumor Classification Using Deep Learning: A Comparative Study and Proposed Methodologies
  2026 DOI: 10.1007/978-981-95-0493-0_31
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• Deep Learning for Nonlinear MISO Systems: LSTM-Based System Modeling
  2026 DOI: 10.1007/978-981-95-0493-0_32
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• Human Gait Recognition: A Comprehensive Study Using Deep Learning and Gait Energy Images
  2026 DOI: 10.1007/978-981-95-0493-0_33
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• Modelling and control of fuzzy‐based systems using intelligent water drop algorithm
  Expert Systems 2024 DOI: 10.1111/exsy.13124
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• A novel Lyapunov-stability-based recurrent-fuzzy system for the Identification and adaptive control of nonlinear systems
  Applied Soft Computing 2023 DOI: 10.1016/j.asoc.2023.110161
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• A study on the estimation of global horizontal irradiance via deep learning technique
  2023 International Conference on Recent Advances in Electrical, Electronics and Digital Healthcare Technologies, REEDCON 2023 2023 DOI: 10.1109/REEDCON57544.2023.10151174
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• A systematic approach for COVID-19 predictions and parameter estimation
  Personal and Ubiquitous Computing 2023 DOI: 10.1007/s00779-020-01462-8
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• Design and application of a novel higher-order type-n fuzzy-logic-based system for controlling the steering angle of a vehicle: a soft computing approach
  Soft Computing 2023 DOI: 10.1007/s00500-023-09128-2
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• Optimizing kernel possibilistic fuzzy C-means clustering using metaheuristic algorithms
  Evolving Systems 2023 DOI: 10.1007/s12530-023-09542-9
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