Abhishek Kumar

About

Dr. Abhishek Kumar is currently working as an Assistant Director and Professor in Computer Science & Engineering Department at Chandigarh University, Mohali, Punjab, India and Senior Researcher in Ingeniot Lab ,UCLM Spain from August 2025. Dr. Kumar has completed Post-Doctoral Fellowship from Ingenium Research Group Lab, Universidad De Castilla-La Mancha, Ciudad Real, and Ciudad Real Spain. . With his total teaching experience of more than 15 years, Dr. Kumar is committed towards academic excellence. Adding to his profile, Dr. Kumar is having more than 240+ publications in reputed, peer reviewed National and International Journals, Books & Conferences. He has guided more than 45 M.Tech. Projects at National and International level and has supervised 7 PhD Scholars.

Dr. Kumar's research area includes- Artificial Intelligence, Machine Learning Renewable Energy, Image Processing, Computer Vision, Data Mining, Computational Healthcare, and Bioinformatics. He has been Session Chair and Keynote Speaker of many International Conferences, Webinars in India and Abroad. He has been the Reviewer for IEEE and Inderscience Journal. He has Authored/Co-Authored 8 books published internationally and has edited over 111 books (Published & Ongoing with IET, Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Gruyter and CRC etc).

Employment

• Chandigarh University Assistant Director ||Professor
  2025 - Present
• Chandigarh University Assistant Director ||Associate professor
  2022 - 2025
• Chitkara University Assistant Professor research|| R&D (Head)
  2019 - 2022
• EUREKA GROUP OF JOURNALS ASSOCIATE EDITOR
  2018 - Present
• ACERC ASSISTANT PROFESSOR
  2015 - Present
• Maharshi Dayanand Saraswati University VISITING FACULTY
  2015 - Present
• Bhagwant University Assistant Professor
  2013 - 2015

Education

• Government Engineering College Ajmer Mtech
  2011 - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (105)

• Machine learning and hybrid intelligence for wind energy optimization: A comprehensive state-of-the-art review
  Expert Systems with Applications 2026 DOI: 10.1016/J.ESWA.2025.128926
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• A feature explainability-based deep learning technique for diabetic foot ulcer identification
  Scientific Reports 2025 DOI: 10.1038/S41598-025-90780-Z
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• Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises
  Proceedings of International Conference on Artificial Intelligence and Smart Energy 2025 DOI: 10.1007/978-3-031-91147-7
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• Blockchain in the Tourism Industry: A New Era of Secure and Transparent Travel Solutions
  Proceedings of International Conference on Artificial Intelligence and Smart Energy 2025 DOI: 10.1007/978-3-031-95341-5
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• DeepHybrid-CNN: A hybrid approach for pre-processing of skin cancer images
  Computerized Medical Imaging and Graphics 2025 DOI: 10.1016/J.COMPMEDIMAG.2025.102611
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• Evaluating Machine Learning Models for Cardiovascular Disease Prediction: Balancing Accuracy and Minority Class Detection
  Archives of Computational Methods in Engineering 2025 DOI: 10.1007/S11831-025-10383-9
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• Machine learning approaches for wind power forecasting: a comprehensive review
  Discover Applied Sciences 2025 DOI: 10.1007/S42452-025-07675-X
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• Secure healthcare data sharing and attack detection framework using radial basis neural network
  Scientific Reports 2025 DOI: 10.1038/S41598-025-99676-4
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• AI-Driven Alzheimer's Disease Detection and Prediction
  Internet of Things and Advanced Application in Healthcare 2024 DOI: 10.4018/979-8-3693-3605-2
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• An Adaptive Salp-Stochastic-Gradient-Descent-Based Convolutional LSTM With MapReduce Framework for the Prediction of Rainfall
  International Journal of Interactive Multimedia and Artificial Intelligence 2024 DOI: 10.9781/IJIMAI.2024.01.003
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