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

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.