Computational Biosciences and Bioinformatics

Dr. Gao received his B.A. in Computer Science in 2004 from Tsinghua University, China, and his Ph.D. in Computer Science in 2009 from the David R. Cheriton School of Computer Science at the University of Waterloo, Canada. Before joining KAUST, he served as a Lane Fellow at the Lane Center for Computational Biology at Carnegie Mellon University, U.S., from 2009 to 2010.

He is the Associate Editor of numerous journals, including 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 Systems, and the International Journal of Artificial Intelligence and Robotics Research.

Gao has co-authored more than 400 research articles in bioinformatics and AI and is the lead inventor on over 60 international patents.

Professor Gao's research interest lies at the intersection between AI and biology/health. His research focuses on building novel computational models, developing principled AI techniques, and designing efficient and effective algorithms. He is particularly interested in solving key open problems in biology, biomedicine, health and wellness.

In the field of computer science, he is interested in developing machine learning theories and methodologies related to large language models, deep learning, probabilistic graphical models, kernel methods and matrix factorization. In the field of bioinformatics, he works on developing AI solutions to key open problems along the path from biological sequence analysis, to 3-D structure determination, to function annotation, to understanding and controlling molecular behaviors in complex biological networks, and to biomedicine and health care. He is a world-leading expert on developing novel AI solutions for challenges in biology, biomedicine, health and wellness, in particular AI-based drug development, large language models in biomedicine, biomedical imaging analysis, and omics-based disease detection and diagnostics.

Robert Hoehndorf is an Associate Professor of Computer Science at King Abdullah University of Science and Technology (KAUST), where he is the principal investigator of the Bio-Ontology Research Group (BORG).

Before joining the University in the fall of 2014, Professor Hoehndorf obtained his Ph.D. in Computer Science from the University of Leipzig, Germany, in 2009. Post-graduation, he spent several years in the U.K. as a research fellow and a research associate at Aberystwyth University and the University of Cambridge, respectively. He was also a postdoctoral fellow at the European Bioinformatics Institute, U.K.

Professor Hoehndorf’s main academic interests are knowledge representation, neuro-symbolic methods and their application in life sciences. He develops knowledge-based methods for analyzing large, complex and heterogeneous biological datasets and applies them to understanding genotype-phenotype relations.

His group developed the DeepGO methods for protein function prediction, neuro-symbolic methods applicable to Semantic Web ontologies and knowledge graphs, and several approaches to represent, reason over, and predict genotype-phenotype relations.

Ivan Viola received an M.Sc. in Computer Science (Dipl.-Ing.) in 2002 and a Ph.D. in Computer Science (Dr. techn.) in 2005 from TU Wien, Austria. In 2006, he joined the University of Bergen (UiB), Norway, as a postdoctoral researcher and contributed to the establishment of a new visualization research group at UiB’s Department of Informatics.

In 2008, Viola was promoted to associate professor and, in 2011, to full professor at the University of Bergen (UiB). During this period, he also served as a scientific adviser at the Christian Michelsen Institute in Norway.

Throughout his career, he has received numerous honors and recognitions for his contributions to computing visualization, including the Austrian Computer Graphics Award in 2016, the Eurographics Dirk Bartz Prize for Visual Computing in Medicine in 2013 and three Best Paper Honorable Mention awards at the IEEE VIS conference.

Aside from serving as an area or program chair at conferences such as the IEEE Visualization Conference, EuroVis, and Eurographics, Viola has been a reviewer and IPC member for several conferences in computer graphics and visualization. He was an associate editor of the Computer Graphics Forum journal and is currently serving as an associate editor for IEEE Transactions on Visualization and Computer Graphics.

In addition to co-authoring over a hundred scientific papers, he is a member of Eurographics and the IEEE Computer Society’s Visualization and Graphics Technical Community (VGTC).

Viola’s research group seeks to develop next-generation computer graphics and technologies for visualizing life forms in all scales. Focusing on scalable approaches, the research group introduces new methods to model, construct and visualize the entire complex biological cell to atomistic detail. This technology allows people to interact, explore, study and understand life at the nanoscale.

Dr. Wittum obtained his Ph.D. (Dr. rer. nat.) in 1987 from Kiel University, Germany. He then pursued further academic qualifications at the University of Heidelberg, Germany, where he received his Habilitation in 1991 and began his first professorship in numerical analysis.

His academic career continued to advance as he served as Director of the Institute for Computer Applications at the University of Stuttgart, Germany, from 1994 to 1998. Following this, he became the Director of the Simulation in Technology Center at the University of Heidelberg, Germany, a position he held from 1998 to 2008. In 2008, he transitioned to the University of Frankfurt, where he led the Gauss Center of Scientific Computing (G-CSC).

After 25 years of serving as a professor at several leading universities in Germany, he joined KAUST, where he is currently a professor in the Applied Mathematics and Computational Science program.

Wittum’s work developing robust and scalable multi-grid methods and software systems for large-scale computing has led to numerous collaborative projects with industry partners, including ABB, Boston Consulting, Commerzbank, Daimler-Benz, the GICON Group, GRS, Porsche and more. 

His contributions to science have been recognized with several prestigious awards, including the Heinz-Maier-Leibnitz Prize, the Controlled Release Society's Award and the doIT Software Award. Professor Wittum has also authored over 200 scientific publications.

Professor Wittum’s research focuses on a general approach to modelling and simulation of problems from empirical sciences, in particular using high-performance computing (HPC).

Particular areas of focus include the development of advanced numerical methods for modelling and simulation, such as fast solvers like parallel adaptive multi-grid methods, allowing for application to complex, realistic models; the development of corresponding simulation frameworks and tools; and the efficient use of top-level supercomputers.

Wittum applies his methods and tools toward problem-solving in computational fluid dynamics, environmental research, energy research, finance, neuroscience, pharmaceutical technology and beyond.

Professor Jesper Tegnér holds a dual role as a professor at KAUST and a Strategic Professor at the Karolinska Institute in Stockholm, Sweden. He earned the rank of chaired full professor just 4.5 years after completing his M.D./Ph.D. in 1997. In 1998, he was recruited as an Assistant Professor in the Department of Computer Science and Numerical Analysis at the Royal Institute of Technology, Stockholm. During a leave of absence, Tegnér pursued postdoctoral research in Boston, U.S., supported by a Wennergren Fellowship and the Alfred P. Sloan Foundation Fellowship from 1998 to 2001.

By 2002, Tegnér had become the first chaired full professor and director of the Division of Computational Biology in Sweden. In January 2010, he took on the role of strategic professor in computational medicine at the Center for Molecular Medicine, Karolinska Institute, and Karolinska University Hospital. In 2014, he furthered his research pursuits by joining the Science for Life Laboratories in Stockholm.

Tegnér is also a Senior Editor of Progress in Preventive Medicine, an acting Section Editor for Clinical and Translational Systems Biology in Current Opinion on Systems Biology, and serves on the editorial boards of BMC Systems Biology and Neurology: Neuroinflammation & Neurodegeneration. He is a fellow of the European Society for Preventive Medicine and the founder of two BioIT companies.

Professor Tegnér's research focuses on computational medicine, systems biology, and the development of AI-driven tools for translational and preventive medicine. His interdisciplinary work integrates biological, computational, and clinical data to explore complex disease mechanisms and develop innovative therapeutic strategies. With over 350 publications, an H-index exceeding 60, and more than 20,000 citations, Tegnér is recognized as a leader in his field.

Professor Jesper Tegnér’s research is driven by two fundamental questions:

1. How can we construct reasoning or intelligent systems?
2. How can we understand living systems, specifically as a form of matter?

These two questions are deeply intertwined. Progress in constructing intelligent systems (question 1) informs the understanding of living systems (question 2), and insights gained from studying living systems guide the development of intelligent systems.

To address question 2, Tegnér’s work focuses on cellular systems as the basic building blocks of life and the brain. His team develops algorithms, theory, and data, while also conducting experiments (such as Single-Cell Genomics and Spatial Transcriptomics) to decode and model cellular networks, tissues, and organs. Their goal is to create a comprehensive field theory for non-equilibrium, dissipative, non-linear cellular systems, and ultimately, a 3D molecular map of the human brain.

In tackling question 1, Tegnér’s research targets the creation of systems capable of generating models of their environment through observation, functioning as an "artificial scientist." These systems utilize algorithmic complexity, network theory, and dynamical systems as constraints for machine learning-driven analysis, particularly in understanding living systems.

Interconnected Hypothesis

Tegnér’s work is based on the hypothesis that the mechanisms governing living systems, from molecular circuits to brain function, are deeply interconnected. He believes that a deeper understanding of cellular and brain operations is crucial for making fundamental advancements in artificial intelligence beyond mere engineering applications.

Translational Research

Tegnér’s work has significant translational applications, driven by expertise in genomics, bioinformatics, machine learning, and medicine. His projects span a wide range of biomedical systems analyses, including collaborations with clinicians worldwide on diseases such as melanoma, breast cancer, multiple sclerosis, Alzheimer’s, and others. Additional projects include:

• HLA-based banking of induced stem cells in Saudi Arabia.
• Development of large language models for Arabic speech.

Tegnér has published over 150 papers related to this translational work, reflecting the broad impact of his research across multiple fields.