Academics

Faculty

Dr. Chetan Bhimrao Khadse
Assistant Professor
Dr. Chetan Bhimrao Khadse

Bio

Chetan B Khadse is an accomplished Assistant Professor in the School of Electrical Engineering at MITWPU, Pune, India. He holds a PhD in "AI applications in Electrical Engineering" from Visvesvaraya National Institute of Technology Nagpur, India, an MTech in Power System from Shivaji University, India, and a Bachelor's from Amravati University, India. With a research focus on artificial intelligence, power systems, power quality, optimization algorithms, and intelligent systems, he has published over 18 research papers in peer-reviewed reputed journals, chapters, and conferences. Dr. Khadse is an active participant in MITWPU's center of excellence for electric vehicles and uses AI techniques to improve EV performance. He also regularly reviews papers for IEEE, Elsevier, Taylor & Francis, and Willey journals.

Research Areas

AI & ML, Power System, Power Quality, Electric Vehicle

Publications

"C. B. Khadse, M. A. Chaudhari, V. B. Borghate, “Conjugate gradient back-propagation based artificial neural network for real time power quality assessment"", International Journal of Electrical Power & Energy Systems (Elsevier), vol. 82, pp. 197-206, 2016.

C. B. Khadse, M. A. Chaudhari, V. B. Borghate, “Electromagnetic Compatibility Estimator using Scaled Conjugate Gradient Back-propagation based Artificial Neural Network"", IEEE Transactions on Industrial Informatics, vol. 13(3), pp. 1036-1045, 2017.

C. B. Khadse, A. A. Patharkar, B. S. Chaudhari, “Electromagnetic field and artificial intelligence based fault detection and classification system for overhead transmission line"", Energy Sources, Part A: Recovery, Utilization and Environmental Effects (T&F), pp. 1-15, July 2021.

Y. Tatte, M. Aware, C. B. Khadse, “Torque ripple reduction in three level five phase invereter fed five-phase induction motor”, Electrical Engineering: Springer. (Accepted for Publication)

Narkhede, G.; Hiwale, A.; Tidke, B.; Khadse, C. “Novel MIA-LSTM Deep Learning Hybrid Model with Data Preprocessing for Forecasting of PM2.5”, Algorithms 2023

Kachhoria, R., Jaiswal, S., Khadse, C. et al. “Lie group dee learning technique to identify the precision errors by map geometry functions in smart manufacturing”, Int J Adv Manuf Technol (2023).

Google Scholar link :https://scholar.google.com/citations?user=mLJqXH8AAAAJ&hl=en

Scopus link :https://www.scopus.com/authid/detail.uri?authorId=57188687742

ORCID link :https://orcid.org/my-orcid?orcid=0000-0002-4719-8734

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