I received my MSc in Veterinary Medicine at the Ghent University (Belgium) in 2006 and was granted my PhD entitled “Health and Fertility Challenges in High Yielding Dairy Cows during the Transition Period and the Use of Dietary Fatty Acids as an Optimization Strategy” in 2012 at the department of Reproduction, Obstetrics and Herd Health. After my PhD appointment (2007-2010), I was working as teaching assistant (2007-2012) and post-doc assistant (2012-2018) in clinical and theoretical MSc courses in Ruminant Herd Health Medicine. My profound interest in the dairy science is strongly supported by attendance on more than 50 national and international trainings between 2007 and 2020. In 2019, I started as Assistant Professor at the Department of Population Health Sciences of the Faculty of Veterinary Medicine at Utrecht University (UU, 0.9 FTE) with focus on the interdisciplinary field of dairy and data science. Due to ongoing data-driven research projects at Ghent University, I still have a 0.1 FTE position at Ghent University. I’m currently coordinating courses on data-driven precision agriculture at both universities. I have guided over 70 MSc students in Veterinary Medicine. I am a member of the steering committee to revise the MSc in Veterinary Medicine and new post-graduate in animal health sciences at the UU. In 2020, I wrote an advisory report around “De Tolakker” research farm of the Faculty of Veterinary Medicine for the faculty board. This has supported a large investment of the UU to gradually transform the research farm into a research innovation centre for circular agriculture.

Driven by a strong personal interest in the data science domain, I successfully finished over 15 post-graduate educations in the epidemiological, statistical and data science domain, I finished a professional certificate in Epidemiology (Prince Edward Island, 2009) and Bio-informatics (Dublin, 2016), and started guiding students in BSc (6) and MSc (4) in Applied Internet, Communication and Technology and MSc in Business Informatics. To further deepen my data science knowledge, I enrolled in a MSc in Computational Statistics in 2016  and finished 45 ECTS credits yet. In 2013, a prototype of an analytical data pipeline developed during my PhD was adopted by delaval.com, one of the largest milking equipment manufacturers in the world which was subsequently merged into the company dairydatawarehouse.com. This novel methodology subsequently accelerated my involvement in several research projects. In 2014, the European gpluse.eu consortium (FP7) executed by 15 research and industry partners was awarded €9.000.000 to use heterogenous agricultural data to exploit genomic data and develop novel phenotyping approaches. I was leader for the data integration work package and together with the project consortium over 40 peer-review articles were successfully published. The project, although officially finished in 2018, is still actively generating results. In 2018, the Flemish government awarded  my team a €1.300.000 VLAIO project (Veerkracht – 170830) in a collaboration with the department of animal sciences and aquatic ecology (Ghent University) and department of Biosystems (KU Leuven) to continue earlier methodological work and monitor dairy cows using machine learning techniques. Two of my PhD students are actively working on this project (Matthieu Salamome and Arno Liseune). Recently, a research proposal was awarded by ZonMW (541003004 - SUMmarizing antimicrobial transmission data to Enable data Reanalysis and prediction by FAIR data use). The research team of M. Hostens initiated the eventually honored idea on ontology and federated learning in a One Health approach between human and veterinary medicine. In 2014 and 2018, I was awarded twice by Microsoft with grants of €150.000 and €25.000 to further explore machine learning techniques in monitoring sustainable agriculture practices. Upon appointment at UU, I became project leader of a large research-industry consortium “Sense of Sensors” which focuses on prediction of health indicators using common sensor technology in the Netherlands. Due to clear interest and experience in applied data science, I’m involved as lecturer in several master programs in bioinformatics in Europe (UU and University College Dublin).

Due to my extensive international network following active project participation in both dairy and data science, I became an experienced keynote speaker at conferences such as annual meetings of the American Dairy Science Association and European Association for Animal Production as well as data science conferences (Spark Summit, Big Data Conference, Semantics Conference). In 2016, I co-organised the ADSA Discover Conference on Big Data for Dairy (Chicago, USA). In 2019, I became a member of the “Dairy Cattle Milk Recording Working Group” of the International Committee for Animal Recording due to my interest to apply federated learning to the globally horizontally partitioned milk recording organizations. Furthermore, I have a quarterly section in the Dutch dairy magazine ‘Melkveebedrijf’ which enables nationwide dissemination of ongoing research results.

I established a new research and focus area on the emerging interdisciplinary field between dairy and data science. I gradually grew my research group by attracting MSc and PhD students. This has resulted in the PhD of Jenne de Koster in 2016 and daily supervision of 5 on-going PhDs (Chen Y., Hermans K., Salamone M., Liseune A., Hut P).

• Promotor of Matthieu Salamone, a Ph.D. focusing on "The transition period as time window to monitor the nutritional and metabolic resilience of high productive dairy cattle - Predictive milk production modeling" (2019-ongoing).
• Promotor of Kristof Hermans, a Ph.D. focusing on data quality in dairy cows as a follow up on the development of the DairyDataWarehouse (2013-ongoing)
• Co-promotor of Jenne De Koster (2016), Ph.D. title: “Influence of body condition score of dairy cows at the end of pregnancy on peripheral tissue insulin response and metabolic properties of adipose tissue”
• Co-promotor of Chen YongYan, a Ph.D. focusing on non-linear lactation curve modelling in dairy cows.
• Co-promotor of Arno Liseune, a Ph.D. focusing on prediction of health events in dairy cows using deep learning.
• Co-promotor of Peter Hut, a Ph.D. focusing on using sensor technology in dairy cows to predict transition disease.

My group is often expanded by visiting researchers as illustrated by publications by Anise Asaadi and Hadi Atashi.