People

Prof. Dr. Holger H. Hoos Chair Holder, Alexander von Humboldt Professor

E-mail: hh[at]aim[dot]rwth-aachen[dot]de
Phone: +49 241 80 21451

Holger H. Hoos holds an Alexander von Humboldt professorship in AI at RWTH Aachen University (Germany), as well as a professorship in machine learning at Universiteit Leiden (the Netherlands) and an adjunct professorship in computer science at the University of British Columbia (Canada).

He is a Fellow of the Association of Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI) and the European AI Association (EurAI), past president of the Canadian Association for Artificial Intelligence and one of initiators of CLAIRE, an initiative by the European AI community that seeks to strengthen European excellence in AI research and innovation (claire-ai.org).

Dr. Mitra Baratchi Associate Professor

Mitra is an associate professor of artificial intelligence at Leiden University. Her research interests lie in spatio-temporal, time-series, and mobility data modelling. She strongly focuses on developing algorithms for wearable sensors data, Earth observations and other open spatio-temporal data sources. Specifically, she explores the design of algorithms that can automatically handle all necessary data processing tasks from the point of data collection to high-level modelling, extraction of information, and effective decision-making from such data.

Her research targets applications in a broad range of urban, environmental, and industrial domains, for which she has collaborated, notably with the European Space Agency, Netherlands Institute for Space Research, Honda Research Institute, various municipalities, and researchers in other scientific disciplines.

Dr. Jan van Rijn Assistant Professor

Jan N. van Rijn holds a tenured position as assistant professor at Leiden University, where he works in the computer science department (LIACS) and Automated Design of Algorithms cluster (ADA). His research interests include trustworthy artificial intelligence, automated machine learning (AutoML) and metalearning. He obtained his PhD in Computer Science in 2016 at Leiden Institute of Advanced Computer Science (LIACS), Leiden University (the Netherlands).

During his PhD, he developed OpenML.org, an open science platform for machine learning, enabling sharing of machine learning results. He made several funded research visits to the University of Waikato (New Zealand) and the University of Porto (Portugal). After obtaining his PhD, he worked as a postdoctoral researcher in the Machine Learning lab at the University of Freiburg (Germany), headed by Prof. Dr. Frank Hutter, after which he moved to work as a postdoctoral researcher at Columbia University in the City of New York (USA). His research aim is to democratize access to machine learning and artificial intelligence across societal institutions, by developing knowledge and tools that support domain experts. He is one of the authors of the book ‘Metalearning: Applications to Automated Machine Learning and Data Mining’ (published by Springer).

MSc Laurens Arp Postdoc

Laurens is a postdoc at LIACS supervised by Mitra Baratchi, researching causal machine learning for spatio-temporal data with a particular focus on satellite data. His research often involves interdisciplinary collaboration, most prominently with the Institute of Environmental Sciences (CML) and the European Space Agency (ESA). During his PhD, he also spent some time at ESA as a visiting researcher. The focus of his PhD was to combine physical models founded on scientific domain knowledge with machine learning and optimisation methods.

Laurens' previous work focused strongly on the estimation of biophysical parameters from satellite data, physical model inversion, and the ill-posedness associated with model inversion and noisy, sensitive systems. In his current research he works on a framework for causal machine learning in spatio-temporal settings, with a focus on remote sensing and Earth science applications.

MSc Annelot Bosman PhD Candidate

Annelot joined the ADA Research group in February, 2022 as a PhD candidate under the supervision of Holger H. Hoos and Jan van Rijn. Before this, Annelot completed her master degree in Econometrics with a specialisation in Operations Research and Quantitative Logistics from Erasmus University Rotterdam.

Her research is funded by the TAILOR network , a collaborative project containing the top research labs and industry partners across Europe (members from, e.g., Leiden University, University of Freiburg, INRIA). Annelots research focusses on robustness verification of Deep Neural networks.

MSc Andreas Paraskeva PhD Candidate

Andreas is a PhD candidate at LIACS, supervised by Jan N. van Rijn, Suzan Verberne and Maarten de Rijke. His research focuses on parsimonious architectures, applying AutoML to improve the efficiency of language models and reduce their compute footprint. He is part of the NWO-funded LESSEN project, collaborating with researchers across Dutch universities and industry partners.

LinkedIn

MSc Guilherme Castro Dallasta External PhD Candidate

Guilherme is an external PhD candidate supervised by Jan van Rijn.

MSc Inês Gomes PhD Candidate

Inês is a PhD candidate at LIACS and the University of Porto (Portugal), supervised by Jan van Rijn from the ADA group, Thomas Bäck from the Natural Computing group, and Luís Teixeira from the Faculty of Engineering of the University of Porto.

Her research lies at the intersection of computer vision and responsible AI, with a particular focus on stress testing. Stress testing is a model auditing approach that identifies weaknesses by examining a model’s behavior near decision boundaries. Inês aims to enhance model trustworthiness by revealing potential limitations. Her work is supported by the AISym4Med project.

MSc Julia Wąsala PhD Candidate

Julia is a PhD candidate at LIACS and SRON supervised by Mitra Baratchi and Bram Maasakkers. She joined the ADA group in 2021 as a Master student. Additionally, she was a visiting researcher at the European Space Agency (ESA) as a visiting researcher.

Julia's research in the field of Automated Machine Learning for Earth Observation focuses on designing new methods and validating them in real-world applications such as atmospheric plume detection. Additionally, Julia actively participates in public engagement. She writes a blog on machine learning for Earth Observation and academic skills, publishes a newsletter for the general public, writes columns for the magazine 'De Ingenieur', and gives public talks about her research.

MSc Khashayar Fathinejad PhD Candidate

Khash started as a PhD candidate at the ADA Research Group in February 2024. He is supervised by Mitra Baratchi, Wessel Kraaij, and Saber Salehkaleybar.

Khash completed his master's degree in Computer Science: Decision and Knowledge Sciences at the University of Tehran. His master’s thesis was on Explainable AI in Financial Markets. His research focuses on Causality and AutoML for time series data, particularly wearable sensor data in collaboration with the LABDA MSCA Doctoral Network.

LinkedIn

MSc Nansheline Daal Dual PhD Candidate

Nansheline is an external PhD candidate supervised by Jan van Rijn and Frank Takes from the Computational Network Science group since November 2024. In addition to her PhD, she is employed by the Dutch government, where she currently works as a Data Scientist. Prior to this, Nansheline obtained her Master’s degree in Data Science & Society from Tilburg University.

Nansheline’s research focuses on algorithmic fairness in Dutch law enforcement. Her work analyses the impact of sensitive attributes in governmental data and develops methodological approaches for identifying and mitigating bias in algorithmic decision making.

MSc Sietse Schröder External PhD Candidate

Sietse is a PhD candidate at LIACS supervised by Jan van Rijn and Mitra Baratchi. Sietse's research focuses on overtuning and meta-overfitting in Automated Machine Learning.

LinkedIn

MSc Sandra Straková External PhD Candidate

Sandra is an external PhD candidate supervised by Jan van Rijn.

BSc Andrei Baroian Master Student

Andrei is a MSc student supervised by Jan van Rijn.

BSc Andrew Spiro Master Student

Andrew is a MSc student at Leiden University and is completing his MSc Thesis under the supervision of Dr. Jan van Rijn.

Andrew's thesis research focuses on assessing the reliability of AI models by evaluating their robustness to "adversarial attacks" which are attacks designed to disrupt an AI model. Specifically, robustness distributions will be used as a lens to analyze the robustness of brain-inspired neural networks to adversarial attacks. Andrew completed his BSc at Maastricht University in the Maastricht Science Program with a specialization in Physics.

LinkedIn

BSc Abygail Stegenga Master Student

Abygail is a MSc student at Leiden University and is completing her MSc Thesis under the supervision of Dr. Mitra Baratchi.

Abygail's thesis research involves the integration of cross-validation methods for spatially correlated data in Automated Machine learning systems. Abygail completed her BSc at Leiden University in Astronomy.

LinkedIn

BSc Bart Holterman Master Student

Bart is a MSc student supervised by Mitra Baratchi.

BSc Ivar van der Spoel Master Student

Ivar is currently pursuing an MSc in Advanced Computing in Systems, with a strong interest in computing performance optimizations (including GPU, cloud, and cryptographic optimizations) and in applying AI to satellite and medical practicalities. For his Master's thesis project, he will be a Visiting Researcher at the ESA phi-lab in Frascati, working under the supervision of Dr. Jan van Rijn.

His research focuses on investigating and improving the robustness of satellite-derived models, building on previous work on hardware-aware models developed at phi-lab. The goal is to create more reliable and robust-aware approaches for Earth observation applications. Ivar completed his BSc in Informatica at LIACS, where he wrote his thesis under the supervision of Dr. Anna V. Kononova. His work focused on benchmarking the Coyote Optimization Algorithm using IOHprofiler and the BBOB suite, comparing COA to established heuristics and analyzing its performance across different dimensionalities and problem classes.

LinkedIn

BSc Kasper Notebomer Master Student

Kasper is a MSc student supervised by Jan van Rijn.

BSc Lorenzo Madiai Master Student

Lorenzo is a Master’s student in Computer Science (AI track) at Leiden University. He obtained his Bachelor’s degree in Automation Engineering from Politecnico di Milano and is currently completing his master’s thesis through an internship at TNO, under the supervision of Jan van Rijn.

Lorenzo’s research focuses on risk awareness in autonomous systems, particularly on methods for their validation and verification in novel environments.

BSc Lucas Schreurs Master Student

Luc is a MSc student supervised by Laurens Arp and Mitra Baratchi.

BSc Remco Stuij Master Student

Remco is currently doing the Master of Computer Science: Data Science at Leiden University. Started in February 2024 with a focus on courses in the field of AutoML, NLP and algorithms. Before his master Remco finished the bachelor of Systems Engineering, Policy Analysis and Management CUM LAUDE at the Delft University of Technology. During his bachelor Remco has done a minor of Computational Statistics at the University of Waterloo in Canada, Ontario.

Currently Remco is working on the master thesis which is supervised by Jan van Rijn, Suzan Verbene and Andreas Paraskeva titled 'Automating data science by harnessing the powers of Large Language Models'. The Masters thesis focuses on building a framework that iteratively generates and improves code from scratch based on a prompt and given data. A framework of multiple agents iteratively generates code, fixes errors to ultimately generate code to solve a given problem.