Draft:Karsten Borgwardt

Karsten Borgwardt
Born	December 1980 (age 43–44) Kaiserslautern
Nationality	German
Alma mater	LMU Munich, University of Oxford
Scientific career
Fields	Computer science, Machine learning, Computational biology, Systems biology, Bioinformatics,
Institutions	Max Planck Institute of Biochemistry (2023-), Ludwig Maximilian University of Munich (2023-), ETH Zurich (2014-2023), University of Tübingen (2011-2014), Max Planck Institute for Biological Cybernetics (2008-2014), University of Cambridge (2007-2008)
Thesis	Graph Kernels (2007)
Doctoral advisor	Hans-Peter Kriegel
Website	https://www.biochem.mpg.de/borgwardt

Karsten Borgwardt (born 1980) is a German computer scientist specializing in machine learning and computational biology. Since February 2023, he has been a director at the Max Planck Institute of Biochemistry in Martinsried, Germany, where he leads the Department of Machine Learning and Systems Biology.

Early life and education

Borgwardt was born in 1980 in Kaiserslautern. He obtained a Diplom (equivalent to a master’s degree) in computer science from LMU Munich in 2004 and a Master of Science in biology from the University of Oxford in 2003. During his studies, he was a scholar of the Stiftung Maximilianeum, the Bavarian Foundation for the Promotion of the Gifted, and the German Academic Merit Foundation (Studienstiftung).

Academic career

In 2007, Borgwardt earned his Ph.D. in computer science from LMU Munich. His dissertation received the Heinz Schwärtzel Dissertation Award for Foundations of Computer Science. Following a postdoctoral position at the University of Cambridge, he became a research group leader for machine learning and computational biology at the Max Planck Institute for Biological Cybernetics and the former Max Planck Institute for Developmental Biology in Tübingen in 2008.

In 2011, Borgwardt was appointed professor of data mining in the life sciences at the University of Tübingen. In 2014, he joined ETH Zurich as an associate professor in the Department of Biosystems Science and Engineering (D-BSSE) and was promoted to full professor in 2017. During his tenure at ETH Zurich, he coordinated significant research programs, including two Marie Curie Innovative Training Networks and the Personalized Swiss Sepsis Study, focusing on the prediction of sepsis using machine learning.

Research contributions

Borgwardt’s research integrates big data analysis with biomedical research. He develops novel machine learning algorithms to detect patterns and statistical dependencies in large biological and medical datasets. His work aims to enable the automatic generation of new knowledge from big data and to understand the relationship between the function of biological systems and their molecular properties, which is fundamental for personalized medicine.

Awards and honors

Throughout his career, Borgwardt has received several accolades, including:

2023:

• Appointment as Scientific Member of the Max Planck Society and as Director at the Max Planck Institute of Biochemistry in Martinsried.

• Honorary Professorship from Ludwig Maximilian University of Munich, awarded by the Faculty of Chemistry and Pharmacy.

2022:

• Swiss Institute of Bioinformatics Remarkable Output Award (“Must-read paper of 2021”) as joint last author of Weis et al., Nature Medicine 28:164–174 (2022)

2021:

• Swiss Institute of Bioinformatics Remarkable Output Award (“Must-read paper of 2020”) as joint last author of Höllerer et al., Nature Communications 11:3551 (2020).

• Swiss Institute of Bioinformatics Graduate Paper Award as supervisor and co-author of PhD student Thomas Gumbsch for Hyland et al., Nature Medicine 26:364–373 (2020).

2019:

• ELLIS Fellow and ELLIS Faculty Member.

2018:

• Named among “25 individuals who have the potential to shape the next 25 years” by Focus magazine (January 13, 2018).

2017:

• Golden Owl Award for Best Teaching in the Department of Biosystems at ETH Zurich.

2016:

• Named among the “Top 40 under 40 in Science & Society” in Germany by Business Journal Capital.

2015:

• One of the “Top 40 under 40 in State & Society” in Germany (including 12 scientists) by Business Journal Capital.

• Starting Grant Awardee (ERC backup scheme of the Swiss National Science Foundation, CHF 1.42 million, 5 years starting May 1, 2015).

2014:

• Named among the “Top 40 under 40 in Science” in Germany by Business Journal Capital.

2013:

• Alfried-Krupp-Förderpreis für junge Hochschullehrer (Annual Krupp award of EUR 1 million for one professor in Germany under 38).

2009:

• NIPS Outstanding Student Paper Award as supervisor and co-author of PhD student Nino Shervashidze.

2007:

• Heinz-Schwärtzel-Dissertation-Award for Foundations of Computer Science (Best PhD thesis in Computer Science at TUM, LMU, and UniBW).

• Scholar of the German Academic Merit Foundation (Studienstiftung des deutschen Volkes) as a PhD student.

2002:

• Scholar of the German Academic Merit Foundation (Studienstiftung des deutschen Volkes) as an undergraduate student.

1999:

• Scholar of the Stiftung Maximilianeum in Munich (5–10 students out of 30,000 per year in Bavaria).

• Scholar of the Bavarian Foundation for the Gifted (Stipendium für besonders Begabte, BayBFG) (250 students out of 30,000 per year in Bavaria).

Professional service

Borgwardt has served in various leadership roles, including:

• Scientific Coordinator of Swiss National Data Stream on infection-related ICU research (jointly with Prof. Adrian Egli, UZH; CHF 5 million funding, 21 partner labs, 3 years).
• Scientific Coordinator of the SPHN-PHRT Driver Project “Personalized Swiss Sepsis Study” (jointly with Dr. Adrian Egli, UZH; 2022-2025).
• Scientific Coordinator of a Marie Curie Innovative Training Network on Machine Learning Frontiers in Precision Medicine.
• President of the Community of Special Interest for Machine Learning in Computational and Systems Biology in the International Society for Computational Biology (2017–2020).
• Chairman of the Steering Committee of the Annual Meeting for Machine Learning in Systems Biology (2015–2018).
• Scientific Coordinator of a Marie Curie Initial Training Network on Machine Learning in Personalized Medicine.

Entrepreneurial activities

In 2012, Borgwardt co-founded Computomics, a bioinformatics service company based in Tübingen, where he serves as a scientific mentor.

Selected publications

Borgwardt has published extensively, with over 37,000 citations . Notable works include:

• Weisfeiler-Lehman Graph Kernels (’‘Journal of Machine Learning Research’’, 2011): Introduced an efficient graph kernel based on the Weisfeiler-Lehman algorithm.
• “Early Prediction of Circulatory Failure in the Intensive Care Unit Using Machine Learning” (’‘Nature Medicine’’, 2020): Presented a machine learning approach for early detection of circulatory failure in ICU patients.
• “Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning” (’‘Nature Medicine’’, 2022): showcased the feasibility of predicting antimicrobial resistance from readily collected mass spectrometry data in the hospital. The new method is able to identify antibiotic resistance 24 hours earlier than previous methods.