We work on the intersection between computer science and biology. In the computational side, we develop theories and methods in the field of machine learning, algorithms, and optimization. In the biological side, we develop novel methods to tackle a wide range of open problems, from sequence analysis, to 3D structure determination, to function annotation, to biological networks, and to healthcare.
- Building 3, Office 4217
- Data Analytics
- 2009-2010, Lane Fellow, Lane Center for Computational Biology, Carnegie Mellon University, US
- 2004-2009, Ph.D., Computer Science, University of Waterloo, Waterloo, Canada.
- 2000-2004, B.Sc., Computer Science, Tsinghua University, Beijing, China.
- Genomics, Proteomics & Bioinformatics
- BMC Bioinformatics
- Special issues of BIOKDD2017 and BIOKDD2018 at IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Special Issue of “Deep learning in bioinformatics” at Methods (Elsevier)
- "Intelligent Computing in Protein-Ligand Interaction and Drug Design" of Biomedical Research International
Xin Gao is an associate professor at KAUST and the principal investigator of the Structural and Functional Bioinformatics Group.
Education and early career
Prof. Gao received his PH.D. degree in Computer Science from the University of Waterloo in Canada. Prior to joining KAUST, he was a Lane Fellow at the Lane Center for Computational Biology at Carnegie Mellon University, U.S.A.
Areas of expertise and current scientific interests
Prof. Gao's group works on the intersection between computer science and biology. In the computational side, they work on developing theories and methods for deep learning, graphical models, kernel methods, matrix factorization, optimization and graph algorithms. In the biological side, they collaborate closely with experimental scientists to develop novel computational methods to solve key open problems in biology and medicine. The biological problems they are working on range from analyzing biomolecular sequences to determining their 3D structures to annotating their functions and understanding and controlling their behaviors in complex biological networks. His group also works on medicine and healthcare.
Prof. Gao was selected as a KAUST DIstinguished Teaching Award Finalist in 2018. He held the Lane Fellowship at Carnegie Mellon from 2009-2010. His scientific and professional memberships include:
- Professional member for the Association for Computing Machinery (ACM)
- American Association for the Advancement of Science (AAAS)
- International Society for Computational Biology (ISCB)
- Life Science Society (LSS)
Prof. Gao is an Editorial Member of Genomics, Proteomics & Bioinformatics as well as BMC Bioinformatics. He was previously a Guest Editor for the special issues of BIOKDD2017 and BIOKDD2018 at IEEE/ACM Transactions on Computational Biology and Bioinformatics; Special Issue of “Deep learning in bioinformatics” at Methods (Elsevier); "Intelligent Computing in Protein-Ligand Interaction and Drug Design" of Biomedical Research International.
Why computational bioscience?
The massive amount and complex nature of biological and clinical data generated by high-throughput technologies have posed numerous challenges and opportunities to computational scientists. I believe to overcome the challenges, we have to combine both the experimental and the computational expertise.
KAUST offers us, computational biologists, a unique platform to have an equal dialogue to collaborate with biologists. At KAUST, you can work on both curiosity-driven research and mission-driven research.