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Draft:Karsten Borgwardt

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Karsten Borgwardt
Born (1980-12-03) December 3, 1980 (age 44)
NationalityGerman
Alma materLMU Munich, University of Oxford
Scientific career
FieldsComputer science, Machine learning, Computational biology, Systems biology, Bioinformatics,
InstitutionsMax Planck Institute of Biochemistry, Ludwig Maximilian University of Munich, ETH Zurich, University of Tübingen, Max Planck Institute for Biological Cybernetics, University of Cambridge
ThesisGraph Kernels (2007)
Doctoral advisorHans-Peter Kriegel
Websitehttps://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.[1]


Early life and education

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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 [de], the Bavarian Foundation for the Promotion of the Gifted, and the German Academic Merit Foundation (Studienstiftung).[1]


Academic career

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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.[1]

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. [2] 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.[3]

Research contributions

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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. [4]

Awards and honors

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

2023:

2022:


2021:

2019:

  • ELLIS Fellow and ELLIS Faculty Member.[11]

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.[12]

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). [13]


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).[14]

2009:

  • NIPS Outstanding Student Paper Award as supervisor and co-author of PhD student Nino Shervashidze.[15]

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:

Professional service

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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

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In 2012, Borgwardt co-founded Computomics[16], a bioinformatics service company based in Tübingen, where he serves as a scientific mentor.[1]

Selected publications

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Borgwardt has published extensively, with over 37,000 citations[17] . 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.[3]

References

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  1. ^ a b c d "Karsten Borgwardt's profile at the Max Planck Institute of Biochemistry". Retrieved 3 December 2024.
  2. ^ Orizet, Joel (14 March 2017). "ETH Zürich ernennt Professor für Data Mining". Netzwoche. Retrieved 3 December 2024.
  3. ^ a b c Henderson, Emily (1 March 2022). "Using AI to detect antibiotic resistance". New Medical. Retrieved 5 December 2024.
  4. ^ Luchetta, Simone (20 October 2017). "Der Schatzsucher". Tagesanzeiger (in German). Retrieved 3 December 2024.
  5. ^ "Karsten Borgwardt becomes director at the Max Planck Institute of Biochemistry". Retrieved 3 December 2024.
  6. ^ a b "Max Planck Society, Scientific Members, Karsten Borgwardt". Retrieved 3 December 2024.
  7. ^ "AI offers a faster way to predict antibiotic resistance". ETH Zürich. 10 January 2022. Retrieved 3 December 2024.
  8. ^ "Discover the SIB Remarkable Outputs 2021". Swiss Institute of Bioinformatics. 28 March 2022. Retrieved 3 December 2024.
  9. ^ "Discover the SIB Remarkable Outputs 2020". Swiss Institute of Bioinformatics. 5 April 2021. Retrieved 3 December 2024.
  10. ^ "Bioinformatics Awards 2021: Swiss Bioinformatics Graduate Paper Award". Swiss Institute of Bioinformatics. 6 October 2021. Retrieved 3 December 2024.
  11. ^ "ELLIS Munich Unit". ELLIS. Retrieved 3 December 2024.
  12. ^ "Golden Owl for D-BSSE Professor Karsten Borgwardt". ETH Zürich. Retrieved 3 December 2024.
  13. ^ "Three researchers of ETH Zurich receive a SNSF Starting Grant". ETH Zürich. Retrieved 3 December 2024.
  14. ^ "Alfried Krupp-Förderpreis für junge Hochschullehrer 2013". Ärzteblatt. Retrieved 3 December 2024.
  15. ^ "NIPS 2009 Awards". NIPS. Retrieved 3 December 2024.
  16. ^ "Computomics". Retrieved 3 December 2024.
  17. ^ "Karsten Borgwardt's Google Scholar Profile". Retrieved 3 December 2024.