Prof. Ananda Shankar Hati

About

Dr. Ananda Shankar Hati is a Chartered Engineer and Assistant Professor in Electrical Engineering at IIT (ISM), Dhanbad, India, recognised for his multidisciplinary research at the intersection of Artificial Intelligence, Internet of Things, and sensor-driven systems for transformative electrical engineering applications. With a Ph.D. in Electrical Engineering from IIT (ISM), Dhanbad, Dr. Hati’s academic journey spans esteemed roles at IIT (ISM), NIT Arunachal Pradesh, and Bengal Institute of Technology & Management, contributing to pioneering teaching and research in machines, drives, and instrumentation. His principal research interests include prognostics, industrial AI in electrical drives, transformer diagnostics, and ventilation control, with deep expertise in applying deep learning for prognostics and health management, and developing intelligent solutions for energy efficiency.

Dr. Hati's prolific publication record comprises 27 journal articles—16 of which are in Q1 journals—19 conference papers, and two book chapters, alongside 38 granted patents in Australia, Germany, and the UK, reflecting global impact in AI, IoT, robotics, and sustainable technologies. His research excellence is further underscored by over ₹35 lakhs in competitive grants as principal investigator and core investigator, and recognition as an IET Top Cited Author and MDPI Highly Cited Author. Commitment to mentorship is demonstrated through the guidance of multiple Ph.D. and M.Tech. theses, enhancing the next generation of innovators in electrical and mining engineering.

Dr. Hati has received numerous honorary distinctions, including Honorary D.Sc., Ph.D. (h.c.), and D.Eng. from international bodies in the USA, Iran, Vietnam, Egypt, Russia, and the UK, and serves as Senior Honorary Fellow at the University of South Wales and Honorary Director of the Centre of Excellence, Robotics & Mechatronics, ITM Baroda. His leadership is visible in editorial appointments, serving as Associate Editor, Guest Editor, and Editorial Board member for journals spanning engineering systems and machine learning applications. Dr. Hati is an active member in committees such as IEEE MOVE India Technology, advisory panels, and academic governance roles at IIT (ISM), reflecting broad contributions to policy, disaster recovery, and academic quality.

A Fellow of the Royal Society of Arts (UK), Institution of Electronics & Telecommunication Engineers (IETE, India), and Senior Member of IEEE and the Iranian Neuroscience Society, among others, Dr. Hati maintains diverse professional memberships that facilitate global engagement. He has delivered invited and plenary talks at major international conferences, chaired sessions for IEEE events, and organised impactful special sessions and workshops fostering community, outreach, and professional development. With a career grounded in innovation, collaboration, and real-world problem solving, Dr. Hati exemplifies academic excellence and leadership in global electrical engineering research and education.

Employment

• OAE Publishing Inc. Associate Editor
  2022 - 2026
• Indian Institute of Technology (Indian School of Mines), Dhanbad Assistant Professor
  2013 - Present
• National Institute of Technology Arunachal Pradesh Assistant Professor
  2013 - 2013
• Indian Institute of Technology (Indian School of Mines), Dhanbad Research Scholar
  2010 - 2013
• Bengal Institute of Technology and Management Lecturer
  2009 - 2010

Education

• Indian Institute of Technology (Indian School of Mines), Dhanbad Ph.D
  2010 - 2016
• Heritage Institute of Technology M. Tech
  2007 - 2009
• West Bengal University of Technology B. Tech
  2003 - 2007

Projects & Funding

• Design & Development of energy efficient intelligent mine ventilation system TEQIP-II
  2017 - 2017
• Development of an intelligent helmet for safety & communication of underground mines Science and Engineering Research Board
  2016 - 2019

Publications (32)

• Enhancing Transformer Health Monitoring With AI-Driven Prognostic Diagnosis Trends: Overcoming Traditional Methodology’s Computational Limitations
  IEEE Industrial Electronics Magazine 2024 21 citations DOI: 10.1109/MIE.2023.3329277
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• Insulation aging condition assessment of transformer in the visual domain based on SE-CNN
  Engineering Applications of Artificial Intelligence 2024 16 citations DOI: 10.1016/j.engappai.2023.107409
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• A transfer learning‐based deep convolutional neural network approach for induction machine multiple faults detection
  International Journal of Adaptive Control and Signal Processing 2023 7 citations DOI: 10.1002/acs.3643
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• DSVM-Based Model-Free Predictive Current Control of an Induction Motor
  Energies 2023 10 citations DOI: 10.3390/en16155657
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• An adaptive neural fuzzy interface structure optimisation for prediction of energy consumption and airflow of a ventilation system
  Applied Energy 2023 25 citations DOI: 10.1016/j.apenergy.2023.120879
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• Deep Learning-Based Transformer Moisture Diagnostics Using Long Short-Term Memory Networks
  Energies 2023 15 citations DOI: 10.3390/en16052382
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• Deep Transfer Learning Framework for Bearing Fault Detection in Motors
  Mathematics 2022 33 citations DOI: 10.3390/math10244683
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• Convolutional neural network-long short term memory optimization for accurate prediction of airflow in a ventilation system
  Expert Systems with Applications 2022 27 citations DOI: 10.1016/j.eswa.2022.116618
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• Dilated convolutional neural network based model for bearing faults and broken rotor bar detection in squirrel cage induction motors
  Expert Systems with Applications 2022 59 citations DOI: 10.1016/j.eswa.2021.116290
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• Depolarization Current Prediction of Transformers OPI System Affected From Detrapped Charge Using LSTM
  IEEE Transactions on Instrumentation and Measurement 2022 15 citations DOI: 10.1109/TIM.2022.3181286
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