Moolchand Sharma

Maharaja Agrasen Institute of Technology, New Delhi

Moolchand Sharma is currently serving as an Assistant Professor in the Department of Computer Science and Engineering at Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has contributed significantly to scientific research, publishing numerous articles in renowned international journals and conferences, including those indexed in SCI and Scopus. His work has appeared in journals such as Cognitive Systems Research (Elsevier), Physical Communication (Elsevier), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience), and Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has also authored or co-authored chapters published by prominent international publishers, including Elsevier, Wiley, and De Gruyter.Dr. Sharma has edited and authored four books published by recognized national and international publishers, such as CRC Press and Bhavya Publications. His research interests span Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is affiliated with various professional organizations, including IEEE, ISTE, IAENG, ICSES, UACEE, the Internet Society, and holds a life membership with the Universal Innovators Research Lab.With over nine years of teaching experience, Dr. Sharma is deeply involved in academic and professional events. He serves as the co-convener for several Scopus-indexed conference series, including ICICC, DOSCI, ICDAM, and ICCCN (Springer), and the ICCRDA-2020 conference series (IOP Materials Science & Engineering). He is also the organizer and co-convener of the International Conference on Innovations and Ideas towards Patents (ICIIP). Additionally, he has been a member of advisory and technical program committees for conferences such as ICCIDS-2022 (Elsevier SSRN), and has reviewed for esteemed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis, IJEECS, and World Scientific Journal. Dr. Sharma has also served as a session chair at numerous international conferences.Dr. Sharma completed his Ph.D. from DCR University of Science & Technology (DCRUST), Haryana, in June 2024. He earned his Postgraduate degree in 2012 from SRM University, NCR Campus, Ghaziabad, and graduated in 2010 from KNGD Modi Engineering College, GBTU.

Syed Nisar Hussain Bukhari

National Institute of Electronics & Information Technology (NIELIT), Srinagar, India

Syed Nisar Hussain Bukhari is a Scientist-D at the National Institute of Electronics and Information Technology (NIELIT), Srinagar, under the Ministry of Electronics and Information Technology (MeitY), Government of India. With over 12 years of teaching and research experience, he holds a PhD in Machine Learning and Immunoinformatics from Chandigarh University's University Institute of Computing, as well as a master's and bachelor's degree in Computer Science from the University of Kashmir. Dr. Bukhari's expertise lies in applying Artificial Intelligence, Machine Learning, and Deep Learning to tackle complex challenges across interdisciplinary domains. His research in Immunoinformatics and Computational Biology focuses on epitope-based vaccine design and identifying primary vaccine candidates, thereby accelerating the discovery of novel therapeutics. In Medical Image Analysis, his work leverages deep learning techniques to enhance diagnostic precision and clinical outcomes, driving innovation in healthcare technology. Dr. Bukhari has contributed to numerous peer-reviewed publications in high-impact journals, conference proceedings, and book chapters. He is also the author and editor of several books published by leading publishers such as Taylor and Francis-CRC Press. Dr. Bukhari actively collaborates with scientists from prominent institutions both in India and abroad. He serves as a reviewer for prestigious journals and has chaired sessions at various international, Scopus-indexed conferences. His professional affiliations include memberships in the Institution of Electronics and Telecommunication Engineers (IETE) and the International Association of Engineers (IAENG). Dr. Bukhari’s research interests span Artificial Intelligence, Machine Learning, Deep Learning, Bioinformatics, Immunoinformatics, and Computational Biology, underscoring his commitment to advancing technology for global impact.

Nebojsa Bacanin

Singidunum University, Danijelova, Serbia

Nebojsa Bacanin received his Ph.D. in Computer Science from the Faculty of Mathematics, University of Belgrade, in 2015, with an outstanding average grade of 10.00. He served as the vice-dean of the Graduate School of Computer Science and the Faculty of Informatics and Computing in Belgrade, Serbia. Currently, Dr. Bacanin works as a Full Professor and Vice-Rector for Scientific Research at Singidunum University.His scientific research focuses on various areas of computer science, with particular expertise in artificial intelligence, machine learning, deep learning, stochastic optimization algorithms, swarm intelligence, soft-computing, optimization and modeling, image processing, computer vision, and cloud and distributed computing. Dr. Bacanin is also deeply involved in the emerging field of hybrid methods, combining machine learning and metaheuristics. In this domain, he applies metaheuristics to solve non-deterministic polynomial hard (NP-hard) problems in machine learning, such as hyperparameter optimization, training, and feature selection.In addition to improving machine learning and deep learning models for tasks like classification and regression, Dr. Bacanin's research includes optimizing deep learning models for univariate and multivariate time-series forecasting. As an expert in metaheuristics, he works on enhancing swarm intelligence and other types of metaheuristic algorithms. He modifies the algorithms by adjusting exploitation/exploration expressions, parameters, or through hybridization with other methods, including low-level and high-level hybrid metaheuristics.Dr. Bacanin applies his research to a wide range of practical applications, including cloud computing scheduling, wireless sensor networks (WSNs) localization, coverage, and energy consumption, X-ray image classification, stock price forecasting, and portfolio optimization, among others.