Intelligent Machining: Using Computational Intelligence to Optimize Manufacturing Processes

Explores high-strength steel sections, charting their importance and utility. Provides bibliometric insights into multi-objective optimization and metaheuristic algorithms. Covers development of high entropy alloys.

Kanak Kalita, PhD, is a prominent professor and researcher in mechanical engineering, acknowledged among the Top 2% Scientists Worldwide 2023 by Stanford University. He currently holds the position of Associate Professor in the Department of Mechanical Engineering at Vel Tech University, Chennai. Dr. Kalita’s scholarly output is both prolific and impactful, as evidenced by his authorship of over 75+ SCI and 125+ SCOPUS articles. His editorial expertise is also notable, having edited eight book volumes. He serves on the editorial boards of several esteemed journals such as Scientific Reports, Frontiers in Mechanical Engineering, and the SAE International Journal of Materials and Manufacturing. His guest editorship for numerous journals further demonstrates his commitment to advancing scholarly discourse in his field. His work is highly regarded in the academic community, as reflected by his impressive 1800+ citations and an h-index of 24. Dr. Kalita is an engaging speaker, having delivered over 20 expert lectures across various academic and professional platforms. He has successfully guided eight undergraduate and four postgraduate students and is currently supervising four PhD candidates. His research interests include machine learning, fuzzy decision making, metamodeling, process optimization, the finite element method, and composites. He earned both his ME and PhD in Applied Mechanics from the Indian Institute of Engineering, Science & Technology, Shibpur, India, in 2014 and 2019 respectively.

Ranjan Kumar Ghadai, PhD, is a distinguished academician with extensive research experience in the field of materials science and nanotechnology. He holds MTech and PhD degrees in Mechanical Engineering from the Indian Institute of Engineering, Science & Technology, Shibpur, India, along with a BTech in Mechanical Engineering from Biju Patnaik University of Technology, Odisha, India. He has over 10 years of teaching and research experience. Currently, he is working as an Associate Professor in the Mechanical and Industrial Engineering Department of Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India. He has published more than 75 SCI/Scopus-indexed research articles. His broad research area includes thin film coating deposition, process optimization, and development of composites. Currently, he is handling two sponsored projects as PI and one as Co-PI. His current h-index is 22, and his i10 index is 33. He has guided three postgraduate students and is currently guiding five PhD scholars. Also, he is the reviewer for many peer-reviewed journals like Robotics and Computer-Integrated Manufacturing, Scientific Reports, Advances in Manufacturing, Surface and Interface, Materials Chemistry and Physics, etc.

Xiao-Zhi Gao, PhD, is an esteemed academic with an extensive background in technology and computing. With over 22 years of experience in teaching and research, Dr. Gao has established himself as a leading figure in the field. Since 2018, he has been a Professor at the University of Eastern Finland, Kuopio, Finland, where he continues to contribute significantly to the academic community. Dr. Gao serves as chief editor, associate editor, and a member of the editorial board for several prominent soft computing journals, including Swarm and Evolutionary Computation, Information Sciences, and Applied Soft Computing. His scholarly output is impressive, with over 500 technical papers published in refereed journals and international conferences and more than 400 SCI/SCOPUS research articles to his name. In addition to his extensive list of articles, Dr. Gao has authored two books and edited four books for renowned publishers such as Springer and IGI Global. His research is particularly focused on nature-inspired computing methods, with applications spanning optimization, prediction, data mining, signal processing, control, and industrial electronics. This breadth of interest underscores his deep understanding and innovative approach to complex technological challenges. Dr. Gao’s academic achievements are further highlighted by his impressive Google Scholar H-index of 42, reflecting the widespread influence and high citation rate of his work. He commenced his academic journey at Harbin Institute of Technology, China, where he earned both his BSc and MSc degrees. Dr. Gao further advanced his education at the Helsinki University of Technology, now known as Aalto University, Finland, where he obtained his PhD in 1999.