Dr Shaheer Ansari

Dr Shaheer Ansari

  • Post-Doctoral Research Fellow
Department of Engineering
Google Scholar ORCID Scopus ResearchGate Web of Science
SDGs Focus
Affordable and Clean Energy
Climate Action

Biography

Shaheer Ansari received a B.Sc. degree in electrical and electronic engineering and a master’s degree in instrumentation and control from Integral University, Lucknow. Furthermore, he pursued a Ph.D. degree with the Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia in the year 2023. Currently, he is working as a postdoctoral researcher in the Department of Engineering, School of Engineering and Technology, Sunway University. His research interests include machine learning algorithms, optimization schemes for prognostics, and health management.

Academic & Professional Qualifications

  • PhD, Universiti Kebangsaan Malaysia, Malaysia (2023)
  • Master in Instrumentation and Control, Integral University, India (2015)
  • B.Sc. in Electrical and Electronic Engineering, Integral University, India (2011)

Research Interests

  • Battery state estimation
  • Artificial Intelligence
  • Battery management system
  • Optimization technique

Teaching Areas

  • Renewable Energy
  • Electrical Machines
  • Instrumentation and Measurement
  • Power Electronics

Courses Taught

  • Instrumentation and Measurement
  • Electrical Engineering
  • Electrical machines
  • Power Electronics

Notable Publications

  1. Ansari, S. (2024). Jellyfish optimized recurrent neural network for state of health estimation of lithium-ion batteries. Expert Systems with Applications 238.
  2. Alsuwain, T. Ansari, S (2024). A Review of Expert Hybrid and Co-Estimation Techniques for SOH and RUL Estimation in Battery Management System with Electric Vehicle Application.  Expert Systems with Applications 123123.
  3. Ansari, S. (2023). Optimized data-driven approach for remaining useful life prediction of Lithium-ion batteries based on sliding window and systematic sampling. Journal of Energy Storage 73. 
     

Achievements & Accolades

  1. Received Excellent thesis award and Graduate on time (GOT) award for Ph.D. thesis titled “ Remaining useful life prediction of lithium ion batteries using an optimized recurrent neural network”
  2. Received best paper award for paper titled “ Deep Learning Enabled State of Charge Estimation for Electric Vehicle Batteries Under Noise Effects at 4th International Conference on Sustainable Technologies for Industry 4.0 (STI 2022), Dhaka, Bangladesh.