Speakers
Prof. Ram Bilas Pachori
IEEE Fellow
Indian Institute of Technology Indore, India
Ram Bilas Pachori received B.E. degree with honours in Electronics and Communication Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India, in 2001, M.Tech. and Ph.D. degrees in Electrical Engineering from Indian Institute of Technology Kanpur, Kanpur, India, in 2003 and 2008, respectively. He is currently a Professor (HAG) in the Department of Electrical Engineering at IIT Indore, India. His research interests include signal and image processing, biomedical signal processing, non-stationary signal processing, speech signal processing, brain-computer interface, artificial intelligence and internet of things in healthcare, and machine learning for signal processing. He has supervised 27 Ph.D. theses and is currently supervising 09 Ph.D. theses. He has authored the textbook titled “Time-Frequency Analysis Techniques and their Applications” (CRC Press, 2023). He has 390 publications, which include journal articles (249), conference papers (99), books (12), and book chapters (30). He has also eleven patents, including six granted (01 Australian patent and 05 Indian patents), two published (Indian patents), and three filed (Indian patents). His publications have been cited more than 20,000 times with h-index of 78 according to Google Scholar. He is Fellow of Institute of Electrical and Electronics Engineers (IEEE), Indian National Academy of Engineering (INAE), Institution of Engineering and Technology (IET), Asia-Pacific Artificial Intelligence Association (AAIA), Institution of Electronics and Telecommunication Engineers (IETE), and Institution of Engineers (India) (IEI). He is IEEE EMBS Distinguished Lecturer (2025-2026) and Academy Mentor for EURASIP Academy. He was Associate Editor of IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021-2024). Currently, he is Associate Editor of Electronics Letters, IEEE Open Journal of Engineering in Medicine and Biology, Computers and Electrical Engineering, and Biomedical Signal Processing and Control. He is also serving as Deputy Editor-in-Chief of IETE Journal of Research, Handling Editor of Signal Processing, and Editor of IETE Technical Review journal.
Professor Kannimuthu Subramaniyam
Karpagam College of Engineering, India
Kannimuthu Subramaniyam is currently working as Professor in the Department of Computer Science and Engineering at Karpagam College of Engineering, Coimbatore, Tamil Nadu, India. He is also an In-Charge for the Center of Excellence in Algorithms. He is an IBM Certified Cybersecurity Analyst. He did PhD in Computer Science and Engineering at Anna University, Chennai. He did his M.E (CSE) and B.Tech (IT) at Anna University, Chennai. He has more than 16 years of teaching and industrial experience. He is the recognized supervisor of Anna University, Chennai. Three PhD candidate is completed their research under his guidance. He is now guiding 11 PhD Research Scholars. He has published 59 research articles in various International Journals. He published 2 books ("Artificial Intelligence" & “LinkedList Demystified-A Placement Perspective” and 3 Book Chapters (WOS / Scopus Indexed). He is acting as mentor / consultant for DeepLearning.AI, Hubino, MaxByte Technologies and Dhanvi Info Tech, Coimbatore. He is the expert member for AICTE Student learning Assessment Project (ASLAP). He has presented a number of papers in various National and International conferences. He has visited more than 100 Engineering colleges and delivered more than 138 Guest Lectures on various topics. He is the reviewer for 50 Journals and 3 Books. He has successfully completed the consultancy project through Industry-Institute Interaction for ZF Wind Power Antwerpen Ltd., Belgium. He has received funds from CSIR, DRDO and ISRO to conduct workshops and seminars. He has completed more than 610 Certifications (41 Specializations and 4 Professional Certifications) in Coursera, Hackerrank and NPTEL on various domains. He has guided a number of research-oriented as well as application-oriented projects organized by well-known companies like IBM. He is actively involving in setting up lab for Cloud Computing, Big Data Analytics, Open-Source Software, Internet Technologies etc., His research interests include Artificial Intelligence, Data Structures and Algorithms, Machine Learning, Big Data Analytics, Virtual Reality & Blockchain. One of his research works is incorporated SPMF Open-Source Data Mining Tool. Source: http://www.philippe-fournier-viger.com/spmf/index.php?link=algorithms.php. He Conferred Second Best Team in NLP Challenge as part of FIRE 2019 conference. He secured first Position in NLP Challenge as part of FIRE 2018 Conference.
Professor Azlan bin Mohd Zain
Universiti Teknologi Malaysia, Malaysia.
Azlan Mohd Zain (Member, IEEE) received the Ph.D. degree in computer science from Universiti Teknologi Malaysia (UTM), in 2010. He is currently a Professor with the Faculty of Computing, UTM. As an academic staff, he has successfully supervised more than 25 postgraduate students and received more than 20 research grant funding to support research students. He has published more than 100 research papers. He has been invited as keynote speaker at over ten international conferences, serves on numerous committees, and has served on editorial board for several international journals.
Prof. Ir. Ts. Dr. Yusri Yusof
Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia
Prof. Ir. Ts. Dr. Yusri Yusof is a Senior Professor (VK6) at the Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), and one of Malaysia’s foremost experts in smart manufacturing, digitalization, and sustainable production. With over 105 Scopus-indexed publications, more than 1,300 citations, and an h-index of 17, Prof. Yusri ranks among the top contributors at UTHM in mechanical and manufacturing engineering.
His pioneering research focuses on smart manufacturing systems, STEP-NC CNC retrofitting, CAD/CAM integration, digital factory automation, and green manufacturing technologies. During his Ph.D. at Loughborough University, UK (2007), he developed STEP-compliant CNC systems, laying the foundation for integrating legacy machines into modern Industry 4.0 environments. His work bridges traditional manufacturing practices with advanced technologies, including IoT, AI, and digital twins, enabling industries to modernize operations sustainably and efficiently.
Prof. Yusri has successfully secured 20 competitive research grants totaling approximately RM2 million, funded by MOSTI, MOHE, PRGS, and international collaborations. He has supervised numerous PhD, Master’s, and undergraduate projects, significantly enhancing Malaysia’s research capacity in smart manufacturing and Industry 4.0 applications.
Beyond research, he is actively engaged in university-industry technology transfer, mentoring the next generation of engineers, and promoting sustainable engineering solutions. His work has been widely presented at international conferences and published in leading journals, emphasizing practical and impactful solutions for the modernization of manufacturing systems.
Prof. Yusri’s contributions continue to shape the development of intelligent and sustainable manufacturing ecosystems both nationally and globally. His dedication to innovation, education, and the advancement of Industry 4.0 technologies underscores his leadership in transforming traditional manufacturing toward a more connected, efficient, and environmentally responsible future
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