Holger H. Hoos (professor, head of group)
ADA @ LIACS
ADA @ RWTH Aachen
ADA @ UBC
Former members ∙ PhD genealogy
ADA @ LIACS
Holger H. Hoos
Holger founded the ADA Research Group in 2017, after being appointed Professor of Machine Learning at the Leiden Institute of Advanced Computer Science (LIACS). He is also an Adjunct Professor of Computer Science at the University of British Columbia (Canada), where he holds an additional appointment as Faculty Associate at the Peter Wall Institute for Advanced Studies. He is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and past president of the Canadian Association for Artificial Intelligence / Association pour l'intelligence artificielle au Canada (CAIAC). Holger completed his PhD in 1998 at TU Darmstadt (Germany), where he previously studied computer science, mathematics and biochemistry.
Holger's research interests span artificial intelligence, empirical algorithmics, bioinformatics and computer music. He is known for his work on machine learning and optimisation methods for the automated design of high-performance algorithms and for his work on stochastic local search. Based on a broad view of machine learning, he has developed - and vigorously pursues - the paradigm of programming by optimisation (PbO); he is also one of the originators of the concept of automated machine learning (AutoML). Holger has a penchant for work at the boundaries between computing science and other disciplines, and much of his work is inspired by real-world applications.
In 2018, together with Morten Irgens (Oslo Metropolitan University) and Philipp Slusallek (German Research Center for Artificial Intelligence), Holger launched CLAIRE, an initiative by the European AI community that seeks to strengthen European excellence in AI research and innovation. CLAIRE promotes excellence across all of AI, for all of Europe, with a human-centred focus and aims to achieve an impact similar to that of CERN. The initiative has attracted major media coverage in many European countries and garnered broad support by more than 1000 AI experts, more than one hundred fellows of various scientific AI associations, many editors of scientific AI journals, national AI societies, top AI institutes and key stakeholders in industry and other organisations (for details, see claire-ai.org).
Mitra is an assistant professor in LIACS. She joined ADA Research Group in February 2018. Before joining LIACS, she was a postdoctoral researcher in Design and Analysis of Communication Systems Research (DACS) Group at University of Twente. Prior to that, she was a researcher in Ambient Intelligence Research Group at Saxion University of Applied Sciences. In June 2015, she received her PhD degree in Computer Sciene from University of Twente.
Mitra's research is focused on spatio-temporal and mobility data modeling. She designs algorithms that process trajectories of moving objects such as cars, people, and animals. Such research is targeting applications in crowd monitoring, smart mobility, and urban planning. Her goal is to make such variety of mobility-based applications more accessible through automating the process of learning models from raw mobility data.
Jan van Rijn
Jan van Rijn obtained his PhD at Leiden University under supervision of Joost Kok and Joaquin Vanschoren. During his PhD he developed OpenML.org, and leveraged it to do research towards machine learning on Data Streams and Meta-Learning. After his PhD he did post-docs at Freiburg University (under supervision of Prof. Dr. Frank Hutter) and at Columbia University in the City of New York. Currently he holds a position as Assistant Professor at Leiden University affiliated to the ADA research group. His current research interest include Automated Machine Learning, meta-learning and combinatorial algorithms.
Samira Rezaei Badafshani
Can joined the ADA Research Group in January, 2018 as a PhD candidate under the supervision of Holger H. Hoos and Thomas Bäck. Before joining the ADA Research Group, she was a researcher under the supervision of Beng Chin Ooi at School of Computing, National University of Singapore. Can received her master degrees from Ecole Centrale Paris (France) and Universite libre de Bruxelles (Belgium) by majoring in computer science in 2017.
Can's research interests include automated machine learning, dynamic data analytics, data mining and general machine learning. Currently she is working at project 'Dynamic Data Analytics through automatically Constructed Machine Learning Pipelines'. This research aims at developing a platform for dynamic data analytics that is based on techniques for automatically constructing machine learning pipelines for the task at hand.
Matthias joined the ADA research group in February 2020 as a PhD student. Previously, he wrote his master thesis on automated age estimation from unconstrained facial imagery under the supervision of Holger Hoos and Jan van Rijn, while doing an internship at PwC's Data Analytics unit. He holds a master's degree in Media Technology from Leiden University and, next to that, followed the Information Studies/Data Science master's course at the University of Amsterdam.
Matthias' research is concerned with detecting when (Auto-)AI systems are "out of their depth" and developing mechanisms to fill potential gaps in the training space of these systems.
Bram joined the ADA research group in June 2020 as a PhD student under the supervision of Prof. dr. Holger H. Hoos and Prof. dr. Catholijn M. Jonker. He obtained a BSc in Marine Technology and a MSc in Embedded Systems/Computer Science at Delft University of Technology where he wrote his master thesis on the topic of automated configuration and portfolio selection of negotiation strategies for multi-agent bargaining games.
Bram's research focusses on automated algorithm configuration in changing/non-i.i.d. data scenarios, which are often found in human-centered AI applications. He has a special focus on decentralized learning in multi-agent negotiation scenarios where the environment is constantly changing relative to the agent.
Bram is funded through a Zwaartekracht grant from the Dutch Ministry of Education that is awarded to the Hybrid Intelligence Centre. This center is a consortium of six Dutch universities that aim to advance research at the intersection of human and machine intelligence.[ Personal Website ]
Laurens is a PhD student at Leiden University supervised by dr. Mitra Baratchi, Prof.dr. Holger Hoos and Prof.dr. Peter van Bodegom. Prior to starting his PhD studies in January 2020, he joined the ADA research group in November 2019 as a Master student supervised by dr. Mitra Baratchi and Prof.dr. Holger Hoos.
Laurens' research is funded by an NWO ENW-KLEIN grant awarded to dr. Mitra Baratchi for her project named "Physics-aware Spatio-temporal Machine Learning for Earth Observation Data", which involves a collaboration with the European Space Agency. The goal of the project is to create hybrid models of mutually interacting environmental processes on Earth, combining theory-driven physical models and data-driven machine learning models using Earth observation data.
Maedeh Nasri is a PhD candidate at the Department of Developmental and Educational Psychology (Institute of Psychology) at Leiden University. Her PhD project is embedded in a larger research project called “Data‐driven, urban policymaking for social inclusion of young, vulnerable people” within the Centre for BOLD Cities, as part of the NWO-funded ‘Breaking the cycle’ project. Within this larger project, Maedeh will focus on designing algorithms that extract patterns representing individual and social behaviours of pupils; and their use of space; thus exploring the complex interaction patterns over time and in space of prosocial behaviour and its links with structural and functional developmental changes. Maedeh’s PhD project is supervised by Prof.dr. Carolien Rieffe, Dr Mitra Baratchi (LIACS), Dr Sarah Giest (Leiden University) and Dr Alexander Koutamanis (Delft University of Technology).
After obtaining his BSc. in Artificial Intelligence and MSc. in Computer Science, Mike Huisman joined LIACS in March 2021 as teaching PhD candidate. He conducts research in the field of deep meta-learning, with the aim of increasing the data efficiency of deep learning algorithms as well as our understanding thereof. His supervisors are Aske Plaat and Jan N. van Rijn.
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.
Julia started as a PhD candidate at the ADA Research group in September, 2022. She is supervised by Mitra Baratchi and Holger Hoos, as well as Ilse Aben and Bram Maasakkers from SRON. Previously, she completed her master degree in Computer Science: Artificial Intelligence at Leiden University. Her master’s thesis was on the topic of Automated Machine Learning for Earth Observation. She will continue to work on this topic during her PhD, in collaboration with ESA Phi-lab and SRON.
Tobias is a Master student Data Science : Computer Science at Leiden University and joined the ADA group in March 2021. He obtained his bachelor's degree in Data Science and Knowledge Engineering from Maastricht University (The Netherlands) in 2020. He is currently working on his master thesis project under supervision of Mitra Baratchi. His research is focused on applications of automated machine learning(AutoML) (including Neural Architecture Search(NAS)) in the domain of spatial-temporal data. The topic is broadly applicable in several active research fields including environmental science, sports data science, computer vision and urban computing.
[ LinkedIn ]
Ziwei studied Computer Science at the University of Nottingham (UK) for his Bachelor. He came to Leiden University in 2020, now working on his Master thesis under the supervision of Mitra Baratchi. He has a great interest in AutoML, transfer learning and computer vision. His thesis research direction is 'Person Re-identification by Transfer Learning of Spatial-Temporal Patterns'.
Gareth is a Master's student in Computer Science (following the Data Science track) with a Bachelors degree in Computer Science from the Vrije Universiteit Amsterdam. His fields of interest are in Urban Computing, Data Mining, Data Management and Automated Machine Learning. His Masters research topic will be in the field of automated machine learning for routing problems, supervised by Mitra Baratchi and Yingjie Fan.
Maria is a master’s student in Statistics and Data Science at Leiden University, following the Data Science track. She has previously obtained a bachelor’s in Mathematics from Aristotle University of Thessaloniki. Currently, she is working on her master thesis under the supervision of Jan van Rijn and Matthias König. The project focuses on exploring the topic of Self-assessing AI systems and extending on precedent approaches.
Guus followed the Informatics and Economy track at LIACS for his Bachelors, currently he is in his Masters Computer Science with a specialisation in Data Science. For his master thesis project he is working on the topic of Automatic Detection/Prevention of Fake News. Guus is also a part of the Sports Data Science group at LIACS where he works on the APEX project, which deals with the automatic detection of Ice Skate blades in order to create data for further analysis of the optimal skate path of long distance ice skaters.
Thijs Simons started his Bachelor of Informatics at the University of Leiden in 2016. He currently is a Computer Science Master student at the University of Leiden with the focus on machine learning. He started working on his Master thesis in March 2022 and from that moment also joined the ADA research group. The supervisors of Thijs’ Master thesis are Mike Huisman and Jan van Rijn.
The field of his Master thesis and current main focus is Learning to Optimize, a meta-learning subfield which specializes on meta-learning an optimizer. The main focus of the thesis is, in addition to only parameterizing the update function of the optimizer, also, parameterizing the full backwards pass that normally would be responsible for the calculations of the gradients.
Hadar is a Master's student in Computer Science: Artificial Intelligence. He obtained his Bachelor's degree in 2019 after studying most of it while in high school. He also worked as a software developer. Hadar joined the ADA research group in March 2022 and is working on his thesis on automated algorithm selection for SAT solvers under the supervision of Marie Anastacio and Holger H. Hoos.
Sven van Collenburg
ADA @ RWTH Aachen
Jakob received his doctorate degree in Information Systems at the WWU Münster in 2018. Prior to this he studied computer science and statistics at the TU Dortmund University. He held postdoctoral positions at the WWU Münster and the University of Adelaide before he joined the Chair for AI Methodology (AIM), a branch of the ADA group, at the RWTH Aachen University in April 2022 as an Assistant Professor (Akademischer Rat). His broad research interest is currently focused on various aspects of evolutionary optimisation, e.g., evolutionary diversity optimisation (EDO), theoretical aspects of randomised search heuristics, multi-objective combinatorial optimisation and - most recently - quality diversity.
Marie received a Computer Science engineering degree from the Technology University of Belfort-Montbéliard (France) in 2012. During her studies, she did a research internship on Computer Vision at the Université du Québec à Trois-Rivières (Canada), where she stayed until 2015 to complete a Master’s there in Natural Language Processing. In 2017, she started a PhD under the supervision of Holger Hoos about automated algorithm configuration at Leiden University (The Netherlands) and is now a postdoc at RWTH Aachen University (Germany). Besides research, she emphasises improving the inner dynamics of her community - by organising research talks in her institute, being part of a Diversity Committee and co-founding the CLAIRE Rising Researcher Network - and the outreach toward future researchers - by participating in initiatives aimed at pre-university students or high-school students.
Malte is currently studying for a master's degree in computer science at RWTH Aachen. Previously, he did a dual program for a bachelor's degree at DHBW in Heidenheim, while working at a subsidiary of Daimler. In his master's degree, he is specialising in machine learning. Before his current position at AIM, he worked as a student assistant at the Institute for Energy Efficient Building and Indoor Climate, as well as at the Chair of Biotechnology.
ADA @ UBC
Sam Bayless (postdoctoral fellow) - works on SAT solvers and applications to circuit design and data centre operations, co-supervised by Alan Hu at UBC.
Chris Fawcett (PhD student) - works on algorithm parameter importance, empirical performance analysis, compiler parameter optimisation, AI planning and scheduling.
Julieta Martinez (PhD student) - works on vector compression, deep learning and computer vision applications, co-supervised by Jim Little at UBC.
Chris Cameron (PhD student) - works on algorithm selection and configuration; co-supervised by Kevin Leyton-Brown at UBC.
Yasha Pushak (PhD student) - works on algorithm configuration for scaling and empirical performance analysis (scaling analysis, environment noise).
Thomas Bäck - Professor of Natural Computing, Leiden University
Lars Kotthoff - Assistant Professor, University of Wyoming
Siegfried Nijssen - Assistant Professor of Data Mining and Artificial Intelligence, Université catholique de Louvain
Pieter Leyman - Post-doc, KU Leuven
Chuan Luo - Researcher, Microsoft Research Asia
Jeroen Rook - Promovendus, University of Twente