Links within this page: John Jumper | Amos Bairoch | James Zou | Charlotte Deane | David Baker | Fabian Theis
John Jumper
Google DeepMindUnited Kingdom
Introduced by: TBD
Time: Sunday, July 202, 2025 at 18:30-19:30
Room: TBD
Title TBD
Abstract coming soon.
Biography
John Jumper received his PhD in Chemistry from the University of Chicago, where he developed machine learning methods to simulate protein dynamics. Prior to that, he worked at D.E. Shaw Research on molecular dynamics simulations of protein dynamics and supercooled liquids. He also holds an MPhil in Physics from the University of Cambridge and a B.S. in Physics and Mathematics from Vanderbilt University. At Google DeepMind, John is leading the development of new methods to apply machine learning to protein biology. John has won numerous awards for his work, including the Lasker Award, Breakthrough Prize in Life Sciences, the Canada Gairdner International Award, and the 2024 Nobel Prize in chemistry.
ISCB 2025 Accomplishments by a Senior Scientist winner:
Amos Bairoch
SIB Swiss Institute of BioinformaticsSwitzerland
Introduced by: TBD
Time: Monday, July 21, 2025 at 09:00-10:00
Room: TBD
Title TBD
"Plus ça change, plus c'est la même chose": from Swiss-Prot to Cellosaurus, 40 years of biocuration
Biography
Amos Bairoch is an Emeritus Professor at the University of Geneva and a group leader at the SIB Swiss Institute of Bioinformatics. A pioneer in bioinformatics, he is best known for developing foundational protein and genome databases, including UniProtKB/Swiss-Prot, which have transformed how biological data is curated and used worldwide.
Throughout his career, Amos has led efforts to enhance protein sequence annotation and develop widely used computational tools, shaping the field of molecular biology. His contributions to knowledge sharing in bioinformatics continue to influence research and innovation globally.
ISCB 2025 Overton Prize winner:
James Zou
Stanford UniversityUnited States
Introduced by: TBD
Time: Tuesday, July 22, 2025 at 09:00-10:00
Room: TBD
Title TBD
Abstract coming soon.
Biography
James Zou is an associate professor of biomedical data science at Stanford University, where he develops cutting-edge machine learning and AI techniques for applications in genomics and biomedical research. His work spans algorithmic advancements, ethical AI in healthcare, and precision medicine.
James has made key contributions to deep learning for biological data, interpretable AI, and fair and robust machine learning models for clinical applications. His research helps bridge computational methods with real-world medical impact.
Charlotte Deane
University of OxfordUnited Kingdom
https://www.stats.ox.ac.uk/~deane/
Introduced by: TBD
Time: Wednesday, July 23, 2025 at 09:00-10:00
Room: TBD
Title TBD
Abstract coming soon.
Biography
Charlotte Deane MBE is a Professor in the Department of Statistics at the University of Oxford and the Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC).
From 2022 to 2023, Charlotte was Chief AI Officer at Exscientia, a biotech with ~450 employees, where she led its computational scientific development.
She served on SAGE, the UK Government’s Scientific Advisory Group for Emergencies, during the COVID-19 pandemic, and acted as UK Research and Innovation’s COVID-19 Response Director.
At Oxford, Charlotte leads the Oxford Protein Informatics Group (OPIG), who work on diverse problems across immunoinformatics, protein structure and small molecule drug discovery; using statistics, AI and computation to generate biological and medical insight.
Her work focuses on the development of novel algorithms, tools and databases that are openly available to the community. These tools are widely used web resources and are also part of several Pharma drug discovery pipelines. Charlotte is a member of several advisory boards and has consulted extensively with industry. Additionally, she has established a consulting arm within her research group as a way of promoting industrial interaction and use of the group’s software tools.
David Baker
University of WashingtonUnited States
https://www.bakerlab.org/
Introduced by: TBD
Time: Thursday, July 24, 2025 at 16:20-18:00
Room: TBD
Title TBD
Abstract coming soon.
Biography
Nobel Laureate David Baker is a professor of biochemistry, HHMI investigator, and the director of the Institute for Protein Design at the University of Washington School of Medicine. The Baker Lab develops protein design software and uses it to create molecules that solve challenges in medicine, technology, and sustainability. Among his recent work is the development of powerful machine-learning methods for generating functional proteins.
David is also an adjunct professor of genome sciences, bioengineering, chemical engineering, computer science, and physics at the University of Washington. He has published over 640 research papers, co-founded 21 companies, and been awarded more than 100 patents. Ninety of his mentees have gone on to independent faculty positions.
David is an elected member of the National Academy of Sciences and a recipient of numerous awards, including the 2024 Nobel Prize in Chemistry. TIME named him among the world’s 100 Most Influential People in health.
He received his PhD in biochemistry with Randy Schekman at the University of California, Berkeley, and did postdoctoral work in biophysics with David Agard at UCSF.
ISCB 2025 Innovator Award winner:
Fabian Theis
Helmholtz MunichGermany
Introduced by: TBD
Time: Thursday, July 24, 2025 at 16:20-18:00
Room: TBD
Title TBD
Abstract coming soon.
Biography
Fabian Theis is the Director of the Computational Health Center at Helmholtz Munich and a full professor at the Technical University of Munich. A leading expert in computational biology, he applies machine learning to biomedical data, with a particular focus on single-cell analysis and its implications for precision medicine.
Fabian’s work bridges AI, genomics, and healthcare, pioneering methods that drive biological discovery and advance our understanding of human health. His research has contributed to major breakthroughs in single-cell transcriptomics and the integration of deep learning into biomedical sciences.