Dikshit Chauhan

About

I am a Postdoctoral researcher @ the National University of Singapore, focusing on battery degradation in Electric Vehicles (EVs). I completed my Ph.D. in the Department of Mathematics and Computing at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India. During my Ph.D., I published research papers in international journals and conferences, focusing on soft computing techniques. My research interests span Evolutionary Computation, Machine Learning, and related fields. Recognizing my academic achievements, the Government of India honored me with the MHRD Fellowship in 2019. I am an active member of the IEEE CIS community.

Employment

• National University of Singapore Research Fellow
  2024 - Present

Education

• Dr. B. R. Ambedkar National Institute of Technology Jalandhar M. Sc.
  2017 - 2019

Projects & Funding

Projects & funding information is unavailable.

Publications (29)

• A hybrid of Genetic Algorithm and Differential Evolution for the Chiller Plant Operation Planning
  Energy and Buildings 2026 DOI: 10.1016/j.enbuild.2026.118168
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• Battery State-of-Health Estimation with Embedded Impedance Spectrum Features Under Multiple Battery Chemistry and Temperature Conditions
  Batteries 2026 DOI: 10.3390/batteries12020077
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• A multi-learning-based artificial electric field optimization algorithm with two mutations and 2D histogram for multi-level image segmentation
  Applied Soft Computing 2026 DOI: 10.1016/j.asoc.2025.114271
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• Restart mechanism-based multilevel gravitational search algorithm for global optimization and image segmentation
  Engineering Applications of Artificial Intelligence 2026 DOI: 10.1016/j.engappai.2025.112904
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• A Review on Bilevel Optimization Using Evolutionary Algorithms and Machine Learning Approaches
  IEEE Transactions on Evolutionary Computation 2026 DOI: 10.1109/TEVC.2026.3690256
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• Bi-timescale distributionally robust optimization for power-computing-carbon coordination in multi-microgrids with data centers
  Applied Energy 2026 DOI: 10.1016/j.apenergy.2026.128602
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• Optimization of hybrid active power filters using dynamic fitness-distance balance-based metaheuristic approach
  Neural Computing and Applications 2025 DOI: 10.1007/s00521-025-11652-1
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• Learning strategies for particle swarm optimizer: A critical review and performance analysis
  Swarm and Evolutionary Computation 2025 DOI: 10.1016/j.swevo.2025.102048
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• Self-adaptive and locally-guided artificial electric field algorithm for global optimization with aggregative learning
  Knowledge-Based Systems 2025 DOI: 10.1016/j.knosys.2025.113835
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• Advancements in multimodal differential evolution: a comprehensive review and future perspectives
  Artificial Intelligence Review 2025 DOI: 10.1007/s10462-025-11314-7
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