Keynote Lectures

Available soon.

 

Brief Bio
Prof. Dr. Sjaak Brinkkemper is full professor of Software Production at the Department of Information and Computing Sciences of Utrecht University, the Netherlands. He leads a group of about twenty-five researchers specialized in large-scale software product development and software entrepreneurship. The main research themes of the group are the methodology of software production, digital ecosystems, IT sustainability, and requirements engineering. Brinkkemper's research interests: software production, requirements engineering, software architecture, and method engineering. In 2018 he started the Care2Report research program on the architecting and development of automated reporting in societal sectors, such as healthcare, police, and business analysis.

Available soon.

 

Brief Bio
Jordi Solé-Casals currently holds a permanent position as a Full Professor of the Department of Engineering of the University of Vic – Central University of Catalonia and is the head of the Data and Signal Processing Research Group (DSP, UVic-UCC). He is also Visiting Scientist (2016 ~) at the Brain Mapping Unit of the Department of Psychiatry of the University of Cambridge (UK) and Visiting Scientist (2020 ~) at the College of Artificial Intelligence, Nankai University (China). He obtained the Ph.D. degree with European label in 2000, and the B.Sc. degree in Telecommunications in 1995, both from the Polytechnic University of Catalonia (UPC), Barcelona; and the B.Hum in 2010 from the Open University of Catalonia (UOC), Barcelona. In 1994 he joined the Department of Engineering of the University of Vic – Central University of Catalonia, where he was the Director (2010-2012). He was Visiting Research/Scientist with the GIPSA Lab. in Grenoble (France), the Lab. for Advanced Brain Signal Processing, BSI-RIKEN in Wako (Japan) and the Tensor Learning Team, at the RIKEN Center for Advanced Intelligence Project (AIP), Tokyo (Japan). Currently he continues the relationships with these laboratories. His research interests include signal processing specially in the biomedical field (EEG, fMRI, speech, handwritten, biometric applications), machine learning/deep learning and statistical modelling for applied sciences.

Available soon.

 

Brief Bio
Dr. Peter Kharchenko is a Principal Investigator at the Altos Labs San Diego Institute of Science. Prior to joining Altos, Peter was a Gilbert S. Ommen Associate Professor of Biomedical Informatics at Harvard Medical School. His group has developed key methods for genomic analysis of single cells, enabling statistical separation of distinct cellular states, detection of genomic aberrations in transcriptional data, and inference of cellular dynamics from snapshots of cellular state. His group has also applied these approaches to study the organization of different tissues and the impact of diseases ranging from cancer to schizophrenia. At Altos, Peter’s group studies how cells coordinate their activity within complex biological tissues, how these mechanisms break down in the context of aging or disease, and investigate the potential interventions that may improve tissue function. Much of the effort is focused on development and application of novel statistical methods and computational tools for understanding tissue function, including analysis of multi-omics and spatial assays.

Data-and Knowledge-driven Medical Image Computing and its Contribution to Precision Medicine

 

Brief Bio
Jun Xu is the Director of Jiangsu Provincial Key Laboratory of Intelligent Medical Image Computing (iMIC) and the Vice Dean of the School of Future Technology at Nanjing University of Information Science and Technology, China. He had been a postdoctoral scientist and visiting professor at the Department of Biomedical Engineering at Rutgers University and Case Western Reserve University in the United States, respectively. He and his iMIC research group are developing and applying novel quantitative image analysis, natural language processing, signal processing, and machine learning tools for disease prevention, diagnosis, and prognosis in the context of breast, liver, colorectal, prostate, brain disease, and ophthalmology. Our group is also exploring the utility of these methods in studying correlations of disease markers across multiple scales and modalities-- from digital pathology to X-ray, CT, and multi-parametric MR images, electronic health records, and biosignals.