Work Experience

Data Science at Visma

At Visma, I've been developing, deploying and monitoring machine learning models for predicting the amount of calories required for a race for the benefit of Team Jumbo-Visma (ranked first on the UCI World Team Rankings and winner of the Tour de France 2022, considered as the most prestigious cycling race). Until 2020, Team Jumbo-Visma would start preparing their calorie estimates up to three weeks in advance to ensure they had adequate estimates per cyclist and per stage. This is a time-consuming task. To improve the team performance, I, along with the data science team of Visma Connect, built regression models to predict the calories burned by a rider without needing any human computation. The models provide coaches with the calorie needs for each cyclist per race. I was invited to the broadcast "Wetenschap Vandaag" (Science Today) on the Dutch national radio to cover my work. A replay of the show can be found below (half in Dutch, half in English).

At the end of my bachelor's, I wrote my thesis Conformal Regression in Calorie Prediction for Team Jumbo-Visma, supervised by Dr. Christof Seiler. I investigated conformal regression techniques to provide prediction sets, quantifying the reliability of the models predictions. This allows Team Jumbo-Visma to adapt predictions based on the uncertainty of the forecasts. A paper on my bachelor's thesis can be found here.

I also worked on developing a Talent Identification Dashboard for the cycling team using performance statistics, race results and rider profiles. We predict relative PCS (Pro Cycling Stats) points for the upcoming two seasons per specialty (ITT, climber, sprinter). The model helps Team Jumbo-Visma identify the best talents at an early age.

Papers

Multi-Modal Embeddings for Isolating Cross-Platform Coordinated Information Campaigns on Social Media (co-authored with Prof. Dr. Anda Iamnitchi and Dr. Jerry Spanakis): multi-modal approach that identifies the social media messages potentially engaged in a coordinated information campaign across multiple platforms. Our approach incorporates textual content, temporal information and the underlying network of user and messages posted to identify groups of messages with unusual coordination patterns across multiple social media platforms. We apply our approach to content posted on four platforms related to the Syrian Civil Defence organization known as the White Helmets: Twitter, Facebook, Reddit, and YouTube. Results show that our approach identifies social media posts that link to news YouTube channels with similar factuality score, which is often an indication of coordinated operations. Our paper can be found here (Proceedings of the 5th Symposium on Multidisciplinary International Symposium on Disinformation in Open Online Media)

Argumentative Explanations for Group Recommender Systems (co-authored with Dr. Francesco Barile and Dr. Tjitze Rienstra): In this work, we propose a novel approach, which makes use of an argumentative framework built using information about the aspects that are connected to the recommended items. Such framework is used to generate recommendations, and related explanations. We provide a proof of concept on how to generate explanations for the group, as well as specific explanations for the group members, which use the information in the argumentative frameworks to enrich the explanations. Furthermore, we propose privacy-preserving versions for the explanations, as well as a graphical approach based on tag clouds. Our paper can be found here (Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization).

Conformal Regression in Calorie Prediction for Team Jumbo-Visma (co-authored with Dr. Christof Seiler): see work experience at Visma. Our paper can be found here (Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, volume 204 of Proceedings of Machine Learning Research).

Extracurricular

Board Member & External Officer at MSV Incognito

Elected external officer (academic year 2021-2022) of MSV Incognito, the study association of the Department of Advanced Computing Sciences from Maastricht University. My role was to maintain and develop the relations with companies, sponsors, other student associations, and manage the yearly Career Day. I signed the biggest sponsorship contract in the history of the study association with Arvato Bertelsmann. Furthermore, I organized and led private tutoring for freshmen in computer science and mathematics courses (Discrete Mathematics, Calculus, Linear Algebra, Software Engineering, Data Structure and Algorithms).

Student Ambassador for Data Science & AI at Maastricht University

As Student Ambassador, I present the Department of Advanced Computing Sciences from Maastricht University to prospective students during information fairs, open days, student for a day experience, campus tours and other events. I also take part in other communication and marketing activities such as interviews for the university website or photo shoots for the study programme's brochures.