Dr. Lianna Wijaya
BINUS UNIVERSITY, INDONESIA
Title: will update soon
Dr. Lianna Wijaya based in Indonesia, is currently a Online Lecturer Coordinator FM STR at Bina Nusantara University, bringing experience from previous roles at PT PIS Jakarta, Cruise Centre, English First and Montigo Resort. Lianna Wijaya holds a 2020 – 2023 Doctor’s Degree in Service Management @ Trisakti University. With a robust skill set that includes Resorts, Front Office, Front Line Management, Customer Oriented, Travel Management and more, Lianna Wijaya contributes valuable insights to the industry.
Abstract: will update soon.
Mr. SURENDAR RAMA SITARAMAN
Intel Corporation, Folsom, California, USA
Title: Empowering Industry 4.0 with AI, IoT, and Vision Intelligence for Sustainable Innovation
Mr. SURENDAR RAMA SITARAMAN is presently an AI Frameworks Engineer in INTEL CORPORATION, Folsom, CA, USA.
Abstract: The convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and Vision Intelligence is transforming industrial systems into intelligent, connected, and sustainable solutions. Advanced AI frameworks, combined with these technologies, are enabling smarter operations, enhancing efficiency, and promoting sustainability. AI-driven predictive maintenance, real-time data processing, and advanced computer vision techniques optimize industrial processes, reduce energy consumption, and improve resource utilization. AI frameworks support model optimization, efficient data handling, and intelligent decision-making across distributed environments. The integration of IoT devices with machine learning models enables real-time monitoring, data-driven predictive analytics, and seamless communication across industrial assets, while computer vision adds an extra dimension with quality control, visual inspection, and advanced recognition capabilities essential for automation. Techniques such as distributed inference, tensor optimization, and automated computation placement further enhance scalability and adaptability across diverse industrial settings, fostering sustainable growth. The importance of these converging technologies in creating scalable, adaptable solutions will be highlighted, as well as opportunities and challenges industries face in achieving a fully sustainable and intelligent future.
Dr. Maanak Gupta,
Tennessee Tech University, USA
Title: Intersection of AI, Ethics and Society
Maanak Gupta is an Assistant Professor in the Department of Computer Science at Tennessee Tech University, USA. He received his Ph.D. in Computer Science from the University of Texas at San Antonio and has worked as a Postdoctoral Research Fellow at the Institute for Cyber Security. He also holds an M.S. degree in Information Systems from Northeastern University, Boston. His primary area of research includes security and privacy in cyber space focused in studying foundational aspects of access control, malware analysis, AI and machine learning assisted cyber security, adversarial AI and their applications in technologies including cyber physical systems, cloud computing, IoT and Big Data. Dr Gupta has worked in developing novel security mechanisms, models and architectures for next generation smart cars, smart cities, intelligent transportation systems and smart farming. His scholarly work is regularly published at top peer-reviewed security venues including ACM SIGSAC conferences and refereed journals. He was recognized as the 2016 RSA Security Scholar, and received the 2019 Computer Science Outstanding Doctoral Dissertation research award from UT San Antonio, Kinslow Engineering Research and Wings up 100 awards 2022 at Tennessee Tech. He has published over 80 research articles and is regularly invited as conference keynote and expert speaker globally. His research has been funded by the US National Science Foundation (NSF), NASA, US Department of Defense (DoD) and private industry. He is a senior member of IEEE.
His website is at www.maanakgupta.com
Dr. Valery Vodovozov,
Tallinn University of Technology, Estonia
Title: Overview of trends and advancements in the field of power electronic converters used in robotics
Dr. Valery Vodovozov holds his PhD and Senior Researcher academic titles in Electrical Engineering from St. Petersburg Electrotechnical University, Russia, and is currently a senior expert in robotics, professor at Tallinn University of Technology, Estonia. He taught at St. Petersburg Electrotechnical University, Russian Customs Academy, Michigan University, and served as a visiting researcher at Ford Motor Company. He is an author of more than 300 professional publications, including textbooks, patents, articles, and papers in prominent journals and conferences. For a long time, he was a performer and manager of 26 research projects, an editor of Energies and Education Sciences MDPI journals, a producer of above 40 educational courses in robotics, industrial electronics, and electrical drives for engineering students, a supervisor of 14 PhD dissertations and multiple master and bachelor theses. He is a senior member of IEEE Education, Industrial Electronics, and Industrial Application Societies, and a chair of the IEEE Estonia Education Society Chapter.
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Prof. Mohd Helmy Abd Wahab,
Universiti Tun Hussein Onn Malaysia, Johor, Malaysia
Title: Smart Applications for Community: A Way forward
Mohd Helmy Abd Wahab is a senior lecturer and former Head of Intelligent System Lab at the Department of Computer Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM). He is currently a Visiting Research Fellow for Center of Excellence on Geopolymer and Green Technology under cluster Green ICT, Universiti Malaysia Perlis (2018 – present). He is also an Executive Committee member for IEEE System, Man and Cybernetics Society Malaysia Chapter (IEEE SMC). He has actively involved in many academic activities such as being Keynote speaker at ICRITO 2020 (India), ICCSNT 2020 (Pakistan), ICCMIT2019 (Austria) and ICDMAI 2019 (Malaysia). He hold several research grants, won several medals in research and innovation showcases and awarded several publication award and teaching awards. He has authored and co-authored 2 books in database system (2013) and this book received consolation prize by Society of Science and Mathematics Malaysia (PESAMA) in 2014 and WAP application (2009), published several both local and international book chapters (22), technical papers in conferences and peer-reviewed journals (>150) papers. He also involve in publishing articles in periodicals such as newspaper (Utusan Malaysia) and national magazine (Dewan Kosmik). He also served as Editor-in-chief for Journal of Advances in Computing and Intelligent System, guest editor for several Special Issues in International journals, Associate Editor for International Journal of Advanced Computer Science and Applications (2009 – present) and as Deputy Editor in Chief for Int. Journal of Software Engineering and Computing since 2009 and scholarly contributed as committee for conferences, editorial team and manuscript reviewers and also invited to be session chair in conferences. Latest, he also invited to be Advisory Committee for COMPe2020 India, and Vice Chair for GRaCe2020 and RETREAT2020. His research interests are in data mining, artificial intelligence, mobile and wireless computing, web-based applications. He is currently an active member of IEEE, IEEE Computer Society, IAEng, IACSIT and PECAMP (Society of Info. Retrieval and Knowledge Management Malaysia) and as Associate Member for Embedded Computing Research Group (UTHM), BigData Center (UTM), MySigBigData (UM), E-Community Research Center (UKM).
Mr. Prashant Gupta,
Software Development Manager, Amazon, Seattle, USA
Title: Responsible AI Product Development
Prashant is a seasoned leader currently serving as a Software Development Manager at Amazon where he leads a team of engineers developing data-driven algorithms to optimize global warehouse operations across Amazon’s vast network. With a Master’s in Computer Engineering from UC Davis and over 9 years of professional experience, Prashant specializes in software development, management, and artificial intelligence applications, utilizing state-of-the-art cloud solutions. As a cross-functional leader, he fosters global collaboration to ensure the quality and reliability of their projects while bridging technical innovation with practical business needs. His commitment to academic excellence is exemplified through his role as a Senior Member of IEEE and his extensive reviewing experience for prestigious publications, including multiple Elsevier journals such as Smart Health, Computer Standards & Interfaces, and Computers & Industrial Engineering, as well as numerous IEEE conferences like IEEE New Era 2024, ICEIA 2024, CICN 2024, ICDCC 2024, and HRI 2025. His overarching mission remains consistent: to innovate, delight customers, and drive growth while advancing the field of computer science through both practical applications and academic contributions.
Abstract: In an era of rapid technological advancement, the development of artificial intelligence products demands a delicate balance between innovation and ethical responsibility. This keynote address explores the critical frameworks and best practices for building AI products that are not only technically sophisticated but also socially responsible and ethically sound. We will examine the key pillars of responsible AI development, including robust fairness testing, transparency in algorithmic decision-making, and proactive bias mitigation strategies. The discussion will delve into practical implementation methods for privacy-preserving AI systems, addressing the growing concerns around data protection and user consent. Special attention will be given to the importance of diverse and inclusive development teams, governance structures, and the implementation of comprehensive impact assessments throughout the product lifecycle. Through real-world case studies and emerging industry standards, this talk will provide product developers, managers, and stakeholders with actionable insights to create AI solutions that align with societal values while driving technological progress.
Dr. Rajit Karmakar
Senior Design Engineer, Intel
Title: Towards Secure Hardware Design
Dr Rajit Karmakar is currently serving as the senior IP Logic Design Engineer at Intel. Prior to that he served as Senior R&D Engineer at Synopsys. Prior to that, he completed his Ph.D. from the Indian Institute of Technology, Kharagpur, India. His Ph.D. thesis titled “Hardware IP Protection Using Logic Encryption and Watermarking” has received the Best Doctoral Thesis Award at the Asian Test Symposium 2019 (Semifinal of IEEE TTTC E. J. McCluskey Doctoral Thesis Award). He was also the runner-up at the final of the TTTC E. J. McCluskey Doctoral Thesis Award at the International Test Conference 2020. He received his MS degree in Microelectronics and VLSI from the Indian Institute of Technology, Kharagpur, India, in 2015. His current research interests include Hardware Security and VLSI Testing. He is the recipient of the IEEE Richard E. Merwin scholarship 2018.
Abstract: The current global business model of the semiconductor industry divulges the Intellectual Property (IP) of design to multiple third-party agents involved in different phases of IC development. Notably, the fabrication of the ICs and test, assembly, and packaging services are often outsourced to dedicated specialist fab houses and outsourced assembly and test (OSAT) companies. However, this outsourcing reliant cost-effective global business model reinforces the inevitable security concern of IP piracy, counterfeiting, reverse engineering, and insertion of Hardware Trojans (HT), resulting in a yearly loss of several billion dollars. Design-for-Security (DfS) has emerged to be a conjoined part of IC design to withstand these security vulnerabilities. The state-of-the-art DfS solutions can broadly be classified into two classes: 1) Passive methods and 2) Active methods. Passive methods like Watermarking and Fingerprinting are used to detect IP piracy. On the other hand, active methods like IC camouflaging, split-manufacturing, and logic locking can prevent IP piracy. Logic Locking is the most popular and widely accepted method of IP protection. However, time and again, the security of various DfS solutions have been questioned by various attacks. The last few years have witnessed a relentless cat-and-mouse race between various attacks on logic locking and the respective countermeasures. This tutorial will present an in-depth discussion on different attack models and techniques as well as the state-of-the-art defense mechanisms.
Prof. Ram Bilas Pachori
IIT Indore, India
Title: Multivariate signal processing and machine learning based methods for medical applications
Ram Bilas Pachori received the B.E. degree with honours in Electronics and Communication Engineering from Rajiv Gandhi Technological University, Bhopal, India, in 2001, the M.Tech. and Ph.D. degrees in Electrical Engineering from IIT Kanpur, India, in 2003 and 2008, respectively. Before joining the IIT Indore, India, he was a Post-Doctoral Fellow at the Charles Delaunay Institute, University of Technology of Troyes, France (2007-2008) and an Assistant Professor at the Communication Research Center, International Institute of Information Technology, Hyderabad, India (2008-2009). He was an Assistant Professor (2009-2013) and an Associate Professor (2013-2017) at the Department of Electrical Engineering, IIT Indore, where he has been a Professor since 2017. He is also associated with the Center for Advanced Electronics, IIT Indore. He was a Visiting Professor at the Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria, Rende, Italy, in July 2023; Faculty of Information & Communication Technology, University of Malta, Malta, from June 2023 to July 2023; Neural Dynamics of Visual Cognition Lab, Free University of Berlin, Germany, from July 2022 to September 2022; School of Medicine, Faculty of Health and Medical Sciences, Taylor’s University, Malaysia, from 2018 to 2019. Previously, he was a Visiting Scholar at the Intelligent Systems Research Center, Ulster University, Londonderry, UK, in December 2014. His research interests include signal and image processing, biomedical signal processing, non-stationary signal processing, speech signal processing, brain-computer interface, machine learning, and artificial intelligence and the internet of things in healthcare. He is an Associate Editor of Electronics Letters, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Computers and Electrical Engineering, and Biomedical Signal Processing and Control, and an Editor of IETE Technical Review journal. He is a Fellow of IETE, IEI, and IET. He has 325 publications, which include journal articles (200), conference papers (88), books (10), and book chapters (27). He has also eight patents, including one Australian patent (granted) and seven Indian patents (published). His publications have been cited more than 15,500 times with h-index of 67 according to Google Scholar.
Abstract: In the last one or two decades, adaptive signal decomposition techniques have gained popularity for their broad applicability to almost all fields of science and technology. Empirical mode decomposition has been proposed to decompose the signal into amplitude-frequency modulated components (basis functions). Several methods have been proposed, followed by empirical mode decomposition for adaptive decomposition and to obtain improved signal representation. Empirical wavelet transform (EWT), Fourier-Bessel series expansion-based EWT (FBSE-EWT), iterative filtering, variational mode decomposition are a few popular techniques among adaptive decomposition techniques. Recent advancements in sensor technology make it easier to acquire signals from multiple sources simultaneously, which demands multivariate signal decomposition methods. The univariate iterative filtering has been extended for processing multichannel signals, which will be discussed in this talk. Also, applications of multivariate iterative filtering and machine learning in brain-computer interface and schizophrenia detection from multichannel electroencephalogram (EEG) signals will be presented. The obtained results show the effectiveness of the discussed multivariate adaptive signal decomposition techniques.
Prof. Raghvendra Kumar Chaudhary
IIT Kanpur, India
Title: Dielectric Resonator Antenna: Fundamentals and Ideas in High
Dr. Raghvendra Kumar Chaudhary is an Associate Professor of the Department of Electrical Engineering, Indian Institute of Technology (IIT) Kanpur, India. He has published over 270 papers in the leading journals and conferences along with a reference book published by Artech House, London, UK. Dr. Chaudhary has guided 19 M.Tech. Students, 11 PhD students and currently, several M.Tech./PhD students are working under him. He is recipient of the Young Scientist Platinum Jubilee Award (2021) of the National Academy of Sciences, India (NASI), the Young Engineers Award (2020) of the Indian National Academy of Engineering (INAE), Young Scientist Award (2020) of the Institution of Electronics and Telecommunication Engineers (IETE), Young Engineers Award (2019) of the Institution of Engineers, India (IEI) and many Best Paper awards in different categories in national & international conferences. Dr. Chaudhary is serving as the Associate Editor of three journals namely IET Microwave Antennas & Propagation, IEEE Access, and Microwave and Optical Technology Letters, Wiley. He is a Senior Member of IEEE, Senior Member of URSI, INAE Young Associate, and life member of InRaSS. He has also been featured and interviewed by IET Electronics Letters, UK.