Our Team

Francesca Grisoni

Principal Investigator

Francesca Grisoni is an Assistant Professor at the Eindhoven University of Technology, where she leads the Molecular Machine Learning team. After receiving her Ph.D. in 2016 at the University of Milano-Bicocca (Prof. R. Todeschini) with a dissertation on machine learning for (eco)toxicology, Francesca worked as a data scientist and as a biostatistical consultant for the pharmaceutical industry. Later, she joined the University of Milano-Bicocca and the ETH Zurich as a postdoctoral researcher (Prof. G. Schneider), working on machine learning for drug discovery and de novo design. Her team’s research focuses on developing novel chemistry-centred deep learning methods to augment human intelligence in drug discovery, at the interface between computation and wet-lab experiments.

Derek van Tilborg

PhD Candidate

Derek van Tilborg is a Ph.D. candidate in the Molecular Machine Learning team. Derek holds a MSc degree in bioinformatics from Wageningen University & Research and has a background in biomedical research. He currently works on developing machine learning methods for molecular property prediction, aiming to bridge the gap between predictions and experiments in drug discovery. His research interests are focused on graph neural networks and active learning.

Rıza Özçelik

PhD Candidate

Rıza Özçelik is a Ph.D. candidate in the team. He received his MSc. degree from the Department of Computer Engineering at Boğaziçi University, Turkey, where he applied machine learning to structure-based drug-target affinity prediction. Rıza currently focuses on developing novel generative deep-learning approaches for de novo drug design.

Yves Gaetan Nana Teukam

PhD Candidate @ IBM Zurich

Yves Gaetan Nana Teukam is currently a PhD candidate at IBM Research Europe – Zurich, and he is concurrently affiliated with the Eindhoven University of Technology. His academic journey began with a Bachelor’s degree in Bioinformatics, followed by a Master’s degree in Data Science. Yves’s current focus revolves around the intriguing intersection of language models and protein optimization/design/engineering. By combining data science methodologies with bioinformatics concepts, he aims to unravel the intricate patterns of protein structures, functions, and their potential for engineering. His ultimate goal is to contribute to an innovative venture that utilizes the power of artificial intelligence in the field of bioinformatics. Yves finds the potential impact of this endeavor in areas such as drug discovery and genetic diseases particularly exciting. As he navigates the world of research and development, Yves looks forward to expanding his horizons in this interdisciplinary domain.

Cristina Izquierdo Lozano

PhD candidate

Cristina Izquierdo Lozano is from Reus, a small town in Catalonia. In 2020, she obtained her BSc in Biotechnology and BENG in Computer Engineering from Universitat Rovira i Virgiliin Tarragona. During her time there, she joined the Nanoscopy for Nanomedicine group at IBEC inBarcelona in 2019, where she conducted both of her bachelor theses, utilizing Correlative Light and Electron Microscopy to characterize polymeric nanoparticles and developing a computer vision application in MATLAB, enabling automatic image correlation between two distinct microscopes. In 2021, she moved to Eindhoven to pursue her PhD in the TU/e. In her current research, she uses Machine Learning techniques to analyze super-resolution microscopy data, under the guidance of her supervisors Lorenzo Albertazzi (n4n) and Francesca Grisoni (molML).

Emanuele Criscuolo

Postdoctoral Fellow

Emanuele Criscuolo studied Chemistry at Sapienza University and Tor Vergata University, in Rome. During his master studies he spent about one year at IRBM Science Park, focusing his work on fragment-based drug discovery. In February 2023, He obtained his Ph.D. cum laude in Biochemistry and Molecular Biology, working in the Department of experimental medicine at the University of Rome Tor Vergata. During his doctoral studies, he discovered his passion for computational techniques, combining them with experimental procedures. In 2021, He has received a short-term FEBS fellowship and he was hosted at Leiden University. One year later, he joined Grisoni’s group in Eindhoven, as guest PhD student, to combine his passion for Molecular Dynamics with Machine Learning. In 2023, he joined the team as a Postdoctoral fellow. 

Luke Rossen

PhD Candidate

Luke Rossen is a prospective PhD Candidate in the Molecular Machine Learning team (starting in 2024). Previously, he joined the group as a Master student at TU/e in the Biomedical Engineering department – Chemical Biology cluster, where he managed and participated in the ‘international genetically engineered machine’ (iGEM) Competition team. His research interests are reflected in a recently completed thesis on active learning for drug discovering using graph neural networks, working at the interface between the wet lab and computational work to efficiently navigate the chemical space. Luke has pursued an internship at the Novartis Institute for Biomedical Research, Switzerland, working on generative deep learning models for molecular (scaffold) design.

Helena Brinkmann

PhD candidate

Helena Brinkmann is a Ph.D. candidate at the Molecular Machine Learning Team. She completed her undergraduate studies in the subjects Mathematics and Chemistry at the Eberhard Karls University Tübingen in Germany. After working as a teacher for two years, she received her MSc degree in Medicinal Chemistry from the University of Gothenburg, where she first applied machine learning for drug discovery. Currently, she focuses on the encoding of chemical information to augment the capabilities of de novo molecule design and chemical space exploration.

Meilina Reksoprodjo

Master student

Meilina Reksoprodjo is a Master Student in Data Science at the Eindhoven University of Technology. Her research interests encompass a diverse range of topics in machine learning, with a particular focus on AI for accelerated scientific discovery and geometric deep learning. In 2021, she obtained her BSc in Artificial Intelligence from Radboud University where she conducted research on designing value-sensitive, data-driven healthcare systems. At the time of writing, she is finishing her degree by writing her thesis in the field of structure-based drug design, where she is developing a graph-based generative model for the hit-to-lead optimization step of small therapeutic molecules. Outside of her academic pursuits, she finds joy in great puns and travelling.

Laura van Weesep

Master Student

Laura van Weesep is a Master student in the Biomedical Engineering Department at TU/e. Her curiosity spans a wide range of subjects, and she is particularly enthusiastic about merging human expertise with insights from AI. Her research focuses on utilizing machine learning techniques to predict the properties of peptides. Prior to joining our team, she successfully completed her bachelor’s degree in biomedical engineering. In addition to machine learning for molecules, she finds joy in engaging in sports, with a particular passion for gymnastics.

Sarah de Ruiter

Master Student

Sarah de Ruiter is a Master Student of Biomedical Engineering.

Inge Groffen

Master student

Inge Groffen is a Master student at the TU/e pursuing Data Science and Artificial Intelligence. Prior to this, she completed a joint Bachelor’s degree in Data Science at the TU/e and Tilburg University. She has always had a strong interest in biology, and her current thesis allows to apply her knowledge in a biomedical context. Specifically, her research involves generating new molecules using target-based generative models. Aside from her studies, she enjoys playing tennis, practicing the piano, and traveling.


Francesca Mori (Bachelor student @Chemical Engineering)
Joelle Bink (Bachelor student @Chemical Engineering)
Laura Lemmens (guest Master student @UAM)
Lisa Nooren (Bachelor student @Chemical Engineering)
Max Pordon (Bachelor student @Biomedical Engineering)
Silvia Multari (guest Master student @ University of Milano)
Teo Yordanov (Bachelor student @Chemical Engineering)
Viktorija Mamula (Master student @Industrial Engineering)