Prof. Shuai Wang, University of Electronic Science and Technology of China, China

Biography: Shuai Wang received the PhD degree from the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China, in 2021. He is currently an assistant professor at the University of Electronic Science and Technology of China. Before that, he was a postdoctoral research fellow with the Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore. His current primary research interests include optimization algorithms for signal processing, machine learning and communication systems, distributed optimization and federated learning (FL), data security and privacy protection in distributed systems, integrated sensing and communication (ISAC), etc. He has published more than 30 academic papers and serves as the Youth Editorial Board Member of two journals, and the session chair of ICCT 2025.

Assoc. Prof. Thanapong Intharah, Khon Kaen University, Thailand

Speech Title: Harnessing Artificial Intelligence for Enhanced Screening of Regional Health Problems

Abstract: Opisthorchiasis and cholangiocarcinoma are significant public health concerns in Southeast Asia, requiring effective screening methods for early detection and management. This talk focuses on two innovative AI-powered platforms, OV-RDT and BiTNet, which aim to revolutionize the screening process for these regional diseases.
The OV-RDT platform utilizes AI algorithms to analyze images of the OV-Rapid Diagnostic Test, a urine-based test for opisthorchiasis. By automating the interpretation of test results and real-time data analytic dashboard, the OV-RDT platform improves the accuracy and efficiency of screening, reducing the reliance on skilled technicians and enabling broader access to testing in resource-limited settings.
BiTNet, on the other hand, is an AI-driven platform that analyzes ultrasound images to detect early signs of cholangiocarcinoma and other biliary tract abnormalities. Trained on a large dataset of annotated images, BiTNet employs deep learning techniques to identify subtle changes and patterns associated with the disease, assisting medical professionals in making accurate diagnoses.
The talk will present the development and validation of these platforms and their potential impact on enhancing regional disease screening. We will discuss how OV-RDT and BiTNet can be integrated into existing healthcare systems, enabling remote screening and telemedicine applications. Furthermore, we will highlight the collaborative efforts between researchers, healthcare professionals, and AI experts to ensure the responsible deployment and continuous improvement of these AI-powered tools.
By leveraging the capabilities of OV-RDT and BiTNet, we can significantly enhance the accessibility, accuracy, and efficiency of screening for opisthorchiasis and cholangiocarcinoma. These platforms have the potential to transform the landscape of regional disease management, ultimately improving patient outcomes and public health in affected communities.

Biography: Thanapong Intharah received his PhD in Computer Science from University College London (UCL), United Kingdom. Prior to his doctoral studies, he earned an MSc in Machine Learning from UCL and an MSc in Computer Science from Chulalongkorn University. Dr. Intharah is currently an Associate Professor in the Department of Statistics, Faculty of Science at Khon Kaen University. His research interests include computer vision, machine learning, deep learning, human-machine interaction, artificial intelligence, and cloud computing with specialized applications in healthcare and medical diagnostics. Dr. Intharah's research focuses on developing AI-powered medical diagnostic systems, including the BiTNet platform for ultrasound image analysis of cholangiocarcinoma risk groups and upper abdominal abnormalities, portable AI-ultrasound systems with tele-ultrasound capabilities, and the OV-RDT intelligence platform for opisthorchiasis screening. In 2020, he was awarded the Leaders in Innovation Fellowships by the Royal Academy of Engineering.

Assoc. Prof. Pavel Loskot, ZJU-UIUC Institute, China

Speech Title: Mathematical Models Beyond Vectors and Matrices

Abstract: The vast majority of contemporary computational models are built as low-level primitive arithmetic operations over elements of vectors and matrices. Such models are universal, but their downside is that they numerically very expensive, and require large computational resources. In many practical scenarios, it is useful to adopt more abstract models that can effectively describe systems and the underlying phenomena without requiring excessive computational resources, and while naturally offering interpretability. In this talk, I will survey fundamental mathematical concepts and objects that are useful in building these abstract models including the key ideas in abstract algebra, set theory, algebraic geometry and topology, and their applications in topological data analysis and geometric machine learning.

Biography: Pavel Loskot received his PhD in Wireless Communications from the University of Alberta, Canada. Before he joined the ZJU-UIUC Institute, he was 14 years a Senior Lecturer at Swansea University, UK. In the past 30 years, he was involved in numerous collaborative research and development projects, and also held a number of paid consultancy contracts with industry. His research interests focus on mathematical and probabilistic modeling, statistical and digital signal processing, and machine learning for multi-sensor, tabular, and longitudinal data. He is the Senior Member of IEEE, the Member of ACM, a Fellow of the HEA, UK, the Recognized Research Supervisor of the UKCGE, and the IARIA Fellow. He serves as the Editor in ICT Express and Frontiers in Genetics.

 

Prof. Moirangthem Marjit Singh, North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh, India

Biography: Dr. Moirangthem Marjit Singh is a Professor in Computer Science & Engineering Department at North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh, India. He received B.Tech. & M.Tech. degrees from NERIST and PhD degree from University of Kalyani, India in 2001,2010 and 2017 respectively. He was the Head of Department Computer Science & Engineering, NERIST (2018 – 2022), founder Honorary Joint Secretary of the IE(I), Arunachal Pradesh State Centre, India (2019-2021) and founder member Unnat Bharat Abhiyan NERIST Cell (2017-2024). Currently, he is In-charge of Educational Technology Cell at NERIST, Chief Information Security Officer (CISO) NERIST and Single Point of Contact (SPoC) for National Institute of Electronics and Information Technology (NIELIT, Ministry of Electronics and IT, Govt. of India) Itanagar Centre at NERIST. He is a Fellow of IETE India, Fellow of IE (I) and senior member IEEE, USA. He is an Editor of IETE- Journal of Research published by Taylor & Francis.
Prof. Marjit was honoured with “Academic Excellence Award” by Taylor’s University, Malaysia in recognition of his outstanding academic performance on 13 September 2023. He received the “IE(I) Young Engineers Award 2014–2015” in Computer Engineering Division from Institution of Engineers, India. He also received the “Best Paper Awards” at international conferences namely the ICEAI 2023(Taylors’ University, Malaysia), the SETSM 2025(Hanoi University of Industry, Vietnam) the ICACCT 2016, (APIIT, India) and Best Paper Award 1st Runner-Up in ICDAI2024(TINT, India).
Prof. Marjit did his schooling at JNVSA Kakching, Thoubal District, Manipur (1990-1997). He secured First Position in X and Second Position in XII Examinations conducted by CBSE, New Delhi, India, amongst the candidates sent up from Jawahar Navodaya Vidyalayas (JNVs) of North Eastern region states of India, in 1995 and 1997 respectively. He was felicitated as one of the Eminent Alumni (JNVs of North Eastern Region India) by Navodaya Vidyalaya Samiti Regional Office Shillong, Ministry of Education, Govt. of India on 22 April 2023 at JNV Rangia, Assam. He was Gold Medallist in the M.Tech.(CSE) program too.
Prof. Marjit has a patent granted for 20 years by the Patents office Govt. of India with effect from 30 July, 2021(Patent Number:542853). He has published several papers in international journals, book chapters and conferences of repute. He has been associated with many technical conferences held in India and abroad. He has delivered many technical/invited talks as well. His research interests include MaNet, WSN, Security, ML, DL and Image Classification.

 

Prof. Loc Nguyen, Sunflower Soft Company, Vietnam

Biography: Loc Nguyen is an independent scholar from 2017. He holds Master degree in Computer Science from University of Science, Vietnam in 2005. He holds PhD degree in Computer Science and Education at Ho Chi Minh University of Science in 2009. His PhD dissertation was honored by World Engineering Education Forum (WEEF) and awarded by Standard Scientific Research and Essays as excellent PhD dissertation in 2014. He holds Postdoctoral degree in Computer Science from 2013, certified by Institute for Systems and Technologies of Information, Control and Communication (INSTICC) by 2015. Now he is interested in poetry, computer science, statistics, mathematics, education, and medicine. He serves as reviewer, editor, speaker, and lecturer in a wide range of international journals and conferences from 2014. He is volunteer of Statistics Without Borders from 2015. He was granted as Mathematician by London Mathematical Society for Postdoctoral research in Mathematics from 2016. He is awarded as Professor by Scientific Advances and Science Publishing Group from 2016. He was awarded Doctorate of Statistical Medicine by Ho Chi Minh City Society for Reproductive Medicine (HOSREM) from 2016. He was awarded and glorified as contributive scientist by International Cross-cultural Exchange and Professional Development-Thailand (ICEPD-Thailand) from 2021 and by Eudoxia Research University USA (ERU) and Eudoxia Research Centre India (ERC) from 2022. He has published 101 papers and preprints in journals, books, conference proceedings, and preprint services. He is author of 5 scientific books. He is author and creator of 10 scientific and technological products.

 

Assoc. Prof. Chiagoziem Chima Ukwuoma, Chengdu University of Technology, China

Biography: Dr. Chiagoziem Chima Ukwuoma is an AI researcher and computing educator specializing in trustworthy artificial intelligence, attention-based deep learning, and sustainable machine learning with applications in healthcare, renewable energy, and remote sensing. He earned his Ph.D. in Software Engineering from the University of Electronic Science and Technology of China (UESTC) in 2023 and currently serves as a Lecturer and Module Leader at Chengdu University of Technology, Oxford Brookes College, where he leads large-cohort courses in Computing Systems and Secure Operating Systems. He has published over 50 peer-reviewed papers in high-impact journals such as Renewable Energy, Applied Energy, and the Journal of Advanced Research, accumulating over 1,500 citations and achieving an h-index of 21. He mentors undergraduate, master’s, and doctoral students, and he runs a free global Machine Learning & Computer Vision bootcamp that trains over 120 learners each cycle. His work bridges methodological rigor with societal impact, aligning strongly with priorities in health data science, data ethics, and sustainable AI. Dr. Ukwuoma’s scholarship, teaching excellence, and mentorship reflect his commitment to improving AI systems while broadening access to high-quality computing and data science education worldwide.

 

Asst. Prof. Yiwei Li, Xiamen University of Technology, China

Biography: Yiwei Li received his Ph.D. degree from National Tsing Hua University, Hsinchu, Taiwan, in 2024. He is currently an Assistant Professor at Xiamen University of Technology. Before that, he was a Visiting Ph.D. Student at The Chinese University of Hong Kong, Shenzhen, from September 2019 to February 2022, and a Research Assistant at the Quanzhou Institute of Equipment Manufacturing, Chinese Academy of Sciences, from April 2015 to August 2017. His research interests include distributed optimization, federated learning, data security and privacy protection, and machine learning for wireless communications. He is a Senior Member of IEEE and has served as a TPC member for several flagship international conferences, including IEEE VTC and IJCNN. He has published more than 30 academic papers, serves as a Youth Editorial Board Member of the journal AIAS, and is a session chair for ICCT 2025.

 

Asst Prof. Yanqing Xu, The Chinese University of Hong Kong, Shenzhen, China

Biography: Yanqing Xu received the Ph.D. degree in communication and information system from the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China, in 2019. He was a senior engineer with Huawei Technologies Company Ltd., from July 2019 to July 2020. From September 2020 to August 2022, he was a PostDoc researcher with The Chinese University of Hong Kong, Shenzhen, where he is currently working as a research assistant professor. He is also with the Shenzhen Research Institute of Big Data. Dr. Xu’s current research interest lies in machine learning and signal processing algorithm designs and their applications for wireless communication systems. Dr. Xu served as a special session co-organizer and chair in IEEE SPAWC 2024. He was a recipient of the Shenzhen Overseas High-Caliber Personnel, and the Top 3% Paper Recognition of the IEEE ICASSP 2023. Several of his research outcomes have been successfully deployed in Huawei’s base stations, for which he has received the Huawei Technical Cooperation Achievement Transformation Award (1st Prize) in 2024, the Huawei Wireless Product Line Outstanding Technical Cooperation Project Award in 2024, and the Huawei Technical Cooperation Achievement Transformation Award (2nd Prize) in 2022. He is currently serving as the Deputy Editor of IEEE Transactions on Signal and Information Processing over Networks and an Associated Editor of EURASIP Journal on Wireless Communications and Networking. He is a member of the IEEE.

 

Asst. Prof. Muhammad Shahid Khan, Suan Sunandha Rajabhat University, Thailand

Biography: Dr. Muhammad Shahid Khan is an accomplished academic and researcher with a Ph.D. in Management and over a decade of post-doctoral teaching and industry experience. Currently serving as a Lecturer at Suan Sunandha Rajabhat University (Thailand) and a Visiting Professor at ABA Teachers College and Sanmenxia Polytechnic College (China), he has also held key roles in international diplomacy and industry collaboration, including work with the Pakistan High Commission in Kuala Lumpur. With a strong research portfolio, Dr. Khan has authored 70+ publications in peer-reviewed journals and conference proceedings, including SSCIindexed and high-impact factor publications. His research expertise spans Innovative Management, Sustainable Business, Environmental Sustainability, Knowledge Management, and Green HRM, contributing to both academic scholarship and practical industry applications.

 

Dr. Zichi Wang, Shanghai University, China

Speech Title: Steganography in Neural Networks

Abstract: Steganography aims to achieve covert communication by hiding secret data into a normal cover and transmitting it over a public channel, which is significant for national information security. Traditional steganography transmits secret data through multimedia such as image, audio and video. Neural network model is a new type of data which grows rapidly in recent years and is widely used. Steganography for neural network models is an emerging research field that needs to be developed. Compared with multimedia, neural network model has complex structure, wide variety and large number of parameters. For this reason, traditional steganographic methods cannot be used for neural network model directly. This speech will discuss the secure steganography for neural network models.

Biography: Zichi Wang received the BS degree in electronics and information engineering from Shanghai University, China, in 2014, and received the MS degree in signal and information processing in 2017, the PhD degree in information and communication engineering from the same university in 2020. He is currently with the School of Communication and Information Engineering, Shanghai University, Shanghai, as an Associate professor. His research interests include steganography, steganalysis, and artificial intelligence security. He has published over 100 papers in these areas. He has served as a TPC member for several international conferences, including ICECI 2022 and AAIP 2025.