AI Augmented Biology                                   
                                                                        

Fleishman is a professor at the Weizmann Institute of Science and chief scientist of Scala Biodesign. His research team develops a computational protein-design methodology to address fundamental and “real-world” challenges in biologics and enzyme design. As a postdoc (2007-2011) with the 2024 Nobel Laureate in Chemistry, Prof. David Baker, Sarel developed the first accurate methods for designing protein binders, culminating in designing broad-specificity influenza blockers. At the Weizmann Institute (2011-), his team created a reliable and general protein design strategy that has been used to optimise dozens of different classes of enzymes, binders, and antibodies — one of which recently entered phase II clinical trials as a malaria vaccine. Sarel helped found two Israeli biotech companies, Infinite Acres, in agritech, and Scala Biodesign, in biologics and enzyme design. Among Sarel’s academic awards was the Clore Ph.D. Fellowship (2003-2006), the Science Magazine award for a young molecular biologist (2008), a postdoctoral fellowship (2006-2009) and a career-development award (2012-2015) from the Human Frontier Science Program, European Research Council Starting, Consolidator, and Advanced Grants (ongoing), the Alon Fellowship, the Henri Gutwirth Prize, and the Weizmann Scientific Council Award.

As biology turns increasingly into a data-rich science, the massive amount of data generated by high-throughput technologies present both new opportunities and serious challenges. As a bioinformatician, Dr. Ge Gao is interested in developing novel computational technologies to analyze, integrate and visualize high-throughput biological data effectively and efficiently, with applications to decipher and understand the function and evolution of gene regulatory systems. Since 2011, when he was first recruited as a Principal Investigator (tenure-track) by Peking University, Dr. Gao has developed fourteen online bioinformatic software tools and databases for efficient analyses of large-scale omics data. More than 1.5 billion hits for these resources as well as 30,000+ citations for 30+ published peer-reviewed papers from world-wide research community during past five years well demonstrates their global significance and impact. Taking advantage of these powerful bioinformatics technical infrastructures, Dr. Gao has been delineating the regulatory map and characterizing the functional genome in action globally. Dr. Gao is an active member of global bioinformatic society. He has been elected as a member of Executive Committee and the China Liaison for Asia-Pacific Bioinformatics Network (APBioNET) since 2011, and the Vice President on Education during 2016 and 2018. He is also a Founding Member of Expert Committee for Computational Biology and Bioinformatics, Chinese Society of Biotechnology (established in 2014), as well as of Expert Committee for Big Data and Biocuration, Genetics Society of China (established in 2015). His academic achievement has been well recognized through the Clarivate Highly Cited Researcher, the Elsevier Chinese Most Cited Researchers, the Bayer Investigator Award, the Cheung Kong Scholar and the National Top-notch Young Professionals programs. In the coming years, Dr. Gao will continue his scientific pursuit to decipher the “coded messages” in genomes with cutting-edge bioinformatic and genomic technology.

Dr. Xin Gao is Chair and Professor of Computer Science Program at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He is also the Co-Chair of Center of Excellence for Smart Health, Theme Lead of Center of Excellence on Generative AI, Chair of Bioinformatics Platform, and the Lead of the Structural and Functional Bioinformatics (SFB) Group at KAUST. Prior to joining KAUST, he was a Lane Fellow at Lane Center for Computational Biology at Carnegie Mellon University. He earned his bachelor degree in Computer Science in 2004 from Tsinghua University and his Ph.D. degree in Computer Science in 2009 from University of Waterloo.

He is a world-renowned expert on developing AI solutions for diagnostics of genetic diseases and cancers, drug development, and biomedical imaging. He is co-founder of Syneron Technology and NANOFAI. He serves as the scientific advisor to a number of companies and organizations, such as SFDA in Saudi Arabia, Bioaster in France, DermAssure in USA, Myant in Canada, BioMap in China, and Proteinea in Egypt. He is an elected Fellow of National Academy of Artificial Intelligence and Life Fellow of Royal Society of Arts.

He has published more than 410 papers in the fields of bioinformatics and machine learning, with a total citation of over 13000 and h-index of 61. He is the leading inventor of over 60 international patents, and have been the PI on research grants of more than USD$30 million. He is the associate editor of Bioinformatics, npj Artificial Intelligence, Journal of Translational Medicine, Genomics, Proteomics & Bioinformatics, Big Data Mining and Analytics, BMC Bioinformatics, Journal of Bioinformatics and Computational Biology, Quantitative Biology, Complex & Intelligent System, and International Journal of Artificial Intelligence and Robotics Research, and the guest editor-in-chief of IEEE/ACM Transactions on Computational Biology and Bioinformatics, Methods, and Frontiers in Molecular Bioscience. He has been invited to review research grant proposals for various funding agencies, such as the Swiss National Science Foundation, Italian Ministry of Health, Research Grant Council of Hong Kong, UK Research and Innovation-BBSRC, The Netherlands e-Science Center and The Dutch Research Council, National Science Centre of Poland, and Ministry of Health of Saudi Arabia. Twenty four of his former students and postdocs are now independent PIs at leading institutes all over the world, such as Tsinghua University, Chinese University of Hong Kong, City University of Hong Kong, Toyota Technological Institute at Chicago, MBZUAI, Shandong University, King Abdulaziz University, and University of Benevento, Italy.

Brian is an Assistant Professor of Chemical Engineering at Stanford University, the Dieter Schwarz Foundation Stanford Data Science Faculty Fellow, and an Innovation Investigator at Arc Institute, where his group conducts research at the intersection of biology and machine learning.

Professor Jakob Kather holds dual appointments in medicine and computer science at the Technical University (TU) Dresden, Germany, serves as a senior physician in medical oncology at the University Hospital Dresden and holds an additional affiliation with the National Center for Tumor Diseases (NCT) in Heidelberg. His research is focused on applying artificial intelligence in precision oncology. Prof. Kather’s research team at TU Dresden is using deep learning techniques to analyze a spectrum of clinical data, including histopathology, radiology images, textual records, and multimodal datasets. Guided by the belief that medical and tech expertise needs to be combined, medical researchers in his team learn computer programming and data analysis, while computer scientists are immersed in cancer biology and oncology. Prof. Kather chairs the “Working group on Artificial Intelligence” at the German Society of Hematology and Oncology (DGHO) and is a member of the pathology task force of the American Association for Cancer Research (AACR). His work is supported by numerous European and national grants, which enable the team to develop new deep learning methods for medical data analysis techniques and to apply them in precision oncology.

Dr. Li received her PhD in Biostatistics from the University of Michigan in 2005. Initially trained as a statistical geneticist, she transitioned her research focus to statistical genomics after joining the faculty at the University of Pennsylvania in 2006. Her work aims to deepen our understanding of the molecular mechanisms underlying human diseases. The central theme of her current research involves leveraging statistical, machine learning, and artificial intelligence methods to explore cellular heterogeneity in disease-relevant tissues, characterize gene expression diversity across cell types, study patterns of cell state transitions, and investigate cell-cell crosstalk using single-cell and spatial omics data. More recently, Dr. Li has expanded her expertise to computational pathology, a critical area for processing and analyzing spatial omics data. In addition to developing algorithms and tools, she collaborates with researchers to identify susceptibility genes and key acting cell types for complex diseases. At the University of Pennsylvania, she serves as the Director of the Statistical Center for Single-Cell and Spatial Genomics and chairs the Graduate Program in Biostatistics. Dr. Li is an elected member of the International Statistical Institute, a Fellow of the American Statistical Association, and a Fellow of the American Association for the Advancement of Science.

Henrik Nielsen works in the bioinformatics section at Department of Health Technology, Technical University of Denmark, where he has been an associate professor since 2006. He holds an M.Sc. in biology from University of Copenhagen (1993) and a PhD in biochemistry / theoretical chemistry from Stockholm University (1999). His main research interest has always been the prediction of protein subcellular location in all domains of life. Where is the information that tells the cell where to put which proteins, and what is the nature of this information? To answer these questions, he has used various kinds of machine learning algorithms, notably artificial neural networks and hidden Markov models. His most well-known contribution to the field is the program and web site SignalP which predicts secretory signal peptides. The SignalP web server was launched in 1995 and is now in its sixth major version, based on protein language models (https://services.healthtech.dtu.dk/services/SignalP-6.0/). It is used more than 1,000 times daily, thousands of users have downloaded the program for use on their own computers, and the papers about SignalP have been cited more than 30,000 times.

Web site: https://www.healthtech.dtu.dk/protein-sorting

Jovan Tanevski is a group leader at the Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University and Heidelberg University Hospital, where he also heads the computational platform of the Translational Spatial Profiling Center. His research lies at the intersection of systems sciences and machine learning, focusing on the development of explainable AI/ML and optimization-based methods for data analysis, hypothesis generation, and computational discovery in spatial omics to advance translational biomedicine. In addition to his position in Heidelberg, he is also affiliated with the Department of Knowledge Technologies at the Jožef Stefan Institute in Ljubljana, Slovenia, where he works on applying machine learning to model dynamic biological systems and developing machine learning approaches for surrogate-based modeling of complex dynamical systems.

Kotaro Tsuboyama

M.D., Ph.D.

Degrees

The University of Tokyo Ph.D. (Science)              2019

The University of Tokyo M.D.      2016

Research Experience

2023-present     Lecturer (PI), IIS (Institute of Industrial Science), UTokyo (The University of Tokyo)

2020-2023         Postdoctoral Researcher, Rocklin lab, Feinberg School of Medicine Northwestern University

                          Research Advider: Dr. Gabriel J ROCKLIN

2019-2020         Postdoctoral Researcher, RNA function Lab, IQB (Institute for Quantitative Biosciences, UTokyo

                          Research Adviser: Dr. Yukihide TOMARI

2016-2019        Graduate Student, RNA function Lab, IQB, UTokyo Research Adviser: Dr. Yukihide TOMARI

2014-2016        Undergraduate Student, Molecular biology Lab, Faculty of Medicine, UTokyo

                         Research Adviser: Dr. Noboru MIZUSHIMA

Honors and Awards (selected)

2019     JSPS Ikusi-Prize (The most prestigious prize for graduate students in Japan)

2019     The University of Tokyo President’s Award for Students (for graduate students)

2016     The University of Tokyo President’s Award for Students (for undergraduates)

Jianyi Yang is a Professor of Mathematics and Interdisciplinary Sciences at Shandong University. He has made significant contributions to the field of protein and RNA structure prediction, co-developing several widely-used algorithms, including trRosetta, trRosettaRNA and I-TASSER. His research group achieved remarkable success, winning the protein structure prediction competitions in both CASP15 and CASP16.

Professor Kai Ye

Position: Professor and Director, Bioinformatics Institute of Xi’an Jiaotong University

Institution: Xi’an Jiaotong University, China

Research Focus:

Professor Kai Ye is an expert in bioinformatics, specializing in developing advanced algorithms and tools for analyzing complex genomic data. His research encompasses structural variant detection, single-cell multi-omics, and systems biology approaches to elucidate mechanisms underlying human diseases and evolution.

Education and work experience

• 1995-09~1999-06 Wuhan University, China, B.S.
• 2000-09~2003-06 Wuhan University, China, M.S.
• 2003-07~2003-12 Wuhan University, China, lecturer
• 2004-01~2008-12 Leiden University, the Netherlands, PhD
• 2008-07~2009-06 European Bioinformatics Institute, United Kingdom, Postdoctoral
• 2009-07~2012-11 Leiden University Medical Center, the Netherlands, Assistant Professor
• 2012-12~2016-02 Genome Institute at Washington University in St. Louis, United States, Assistant Professor
• 2016-02~now      Automation department, Xi’an Jiaotong University, China, Professor

Xiaomin Ying is a professor at Beijing Institute of Basic Medical Sciences. She received her B.S. degree in Automatic Control and Applications and her Ph.D. in Control Science and Engineering. Since then, she has been dedicated to interdisciplinary research on machine learning and biology. Her research interests include multimodal data integration and AI algorithm development for deciphering the mechanisms of biological processes and major diseases. She has received many national grants, including the National Key R&D Program of China (where she served as Chief Scientist) and the National Natural Science Foundation of China. Her research has been published in top-tier journals such as Nature Biotechnology and Gut.