Bio

Research topics that interest me are applications of optimization and machine learning that help tackle pressing issues in people's lives, particularly applications in the medical or the humanitarian field. I am therefore involved in two lines of research. The first concerns the development of techniques that allow for the analysis of large genomics datasets. These techniques can be used by bioinformatics- or medical researchers to identify the genetic characteristics that cause a disease, which is a strong lead towards developing medication. The second line of research is in the humanitarian sector: I am a member of the Zero Hunger Lab, where our goal is to support organizations by developing optimization- and data analysis tools to improve their operations. In this way we help these organizations achieve sustainable development goal number 2: zero hunger. I very much enjoy collaborations with people in the medical or humanitarian sector as this allows us to learn from each other.

Expertise

My expertise lies in optimization and machine learning. I work in interdisciplinary projects in bioinformatics, the medical field and the humanitarian sector.

Genetics: Many diseases that cannot be cured today have a genetic cause. Often the exact disease-causing genetic characteristics are unknown, while knowing these would improve understanding the disease and developing medication. Currently large databases with genetic information of diseased people and healthy individuals are composed. I develop methods to analyze these large, complex datasets. (Funding: NWO Veni, Stichting ALS)

Zero Hunger Lab: every day 811 million people go to bed hungry. Many organizations are working hard to feed people around the world and help them improve their livelihoods so they can feed themselves. At Zero Hunger Lab we use data analytics to help organizations improve their operations and gain new insights. We call this Bytes for Bits. We aim to help achieve sustainable development goal 2: zero hunger

Teaching

Current courses:

- Operations Research Methods (third year bachelor Econometrics & OR)

- Operations Research and Machine Learning (master Business Analytics & Operations Research)

 

Past Courses:

- Wiskunde 1 voor bedrijfseconomie (first year Economie & Bedrijfseconomie)

- Improving Society Lab (first year bachelor Econometrics & OR)

Courses

Collaboration

Bioinformatics and medical sector:

- dr. David Craft, Massachusetts General Hospital/Harvard Medical School

- dr. Steven Petit and dr. Nienke Hoffmans-Holzer, Erasmus Medical Center

- prof. dr. Alexander Schönhuth, Bielefeld University

- dr. Jan Veldink, University Medical Center Utrecht

- dr. Basten Snoek, Utrecht University

 

Humanitarian sector:

- World Food Program

- Welthungerhilfe

- Nuffic

Highlights

A CV can be found here.

Recent publications

  1. OGRE - Overlap Graph-based metagenomic Read clustEring

    Balvert, M., Luo, X., Hauptfeld, E., Schonhuth, A., & Dutilh, B. E. (2021). OGRE: Overlap Graph-based metagenomic Read clustEring. BMC Bioinformatics, 37(7), 905-912.
  2. Forecasting the spread of SARS-CoV-2 is inherently ambiguous given th…

    Koenen, M., Balvert, M., Brekelmans, R., Fleuren, H., Stienen, V., & Wagenaar, J. (2021). Forecasting the spread of SARS-CoV-2 is inherently ambiguous given the current state of virus research. PLOS ONE, 16(3 March), [e0245519].
  3. Predicting human body dimensions from single images: A first step in …

    Mohammedkhan, H., Balvert, M., Güven, Ç., & Postma, E. (Accepted/In press). Predicting human body dimensions from single images: A first step in automatic malnutrition detection. In Proceedings of the 1st International Conference on AI for People: Towards Sustainable AI EAI. https://aiforpeople.org/conference/assets/papers/CAIP21-P06.pdf
  4. Robust dose-painting-by-numbers vs. nonselective dose escalation for …

    Petit, S. F., Breedveld, S., Unkelbach, J., den Hertog, D., & Balvert, M. (2021). Robust dose-painting-by-numbers vs. nonselective dose escalation for non-small cell lung cancer patients. Medical physics, 48(6), 3096-3108.
  5. Forecasting the Spread of SARS-CoV-2 is inherently Ambiguous given th…

    Koenen, M., Balvert, M., Brekelmans, R., Stienen, V., & Wagenaar, J. (2020). Forecasting the Spread of SARS-CoV-2 is inherently Ambiguous given the Current State of Virus Research. (CentER Discussion Paper; Vol. 2020-026). CentER, Center for Economic Research.

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