Holger H. Hoos (professor, head of group)
ADA @ LIACS 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.
Koen van der Blom
Koen started as a post-doctoral researcher in the ADA group in March 2019. Under the supervision of Michael Emmerich, Hèrm Hofmeyer (Eindhoven University of Technology), and Thomas Bäck he did this PhD research on multi-objective evolutionary optimisation for early-stage building design at LIACS, Leiden University. He received his MSc from the same institute in 2014, and his B ICT from The Hague University of Applied Sciences in 2012.
In his research he focuses on algorithm configuration. Specifically, he looks at when and how to reconfigure, and how to make configuration procedures more accessible. Besides this, Koen continues to be interested in evolutionary multicriterion optimisation, particularly with regard to navigating mixed-integer spaces, and self-adaptive variation operators. He also has a strong interest in eusocial insect behaviour, and algorithms inspired thereon.
Marie joined the ADA Research Group in september 2017 as a PhD student. She is working on grey-box algorithm configuration, under the supervision of Holger H. Hoos and Thomas Bäck. She graduated in computer engineering at Université Technologique de Belfort-Montbéliard (France) in 2012. She did a research internship in computer vision followed by a master thesis in natural language processing, at Université du Québec à Trois-Rivières (Canada).
Marie's research interests include image processing, intelligent agents, and general machine learning. She likes to combine them with her interests in music, art, and social sciences.
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.
Anna Louise Latour
Anna Louise is a PhD student at Leiden University and a guest researcher at Université catholique de Louvain (Belgium), under the supervision of dr. Siegfried Nijssen, prof. dr. Joost Kok and prof. dr. Holger Hoos. She started her PhD in January 2017, and joined the ADA Research Group in November 2018. She earned her BSc in Physics and Astrophysics at the University of Amsterdam (NL) and her MSc in Computer Science from Leiden University. Anna Louise did her Master's research at KU Leuven (BE), for which she received the KNVI master thesis award for Informatics (second prize).
Her research is funded by an NWO TOP grant awarded to prof. Nijssen for his PROFIDDS (PRObabilistic Features for Intelligent Declarative Data Science) project, and focuses on the intersection of Constraint Programming and Probabilistic Logic Programming.
Anna Louise was awarded Google's WTM 2018 scholarship for her efforts to make academia more welcoming to underrepresented groups. She is a member of Leiden University's Diversity Policy Feedback Group and of the Studium Generale Programme Committee.
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.
Zhou joined the ADA Research Group in September 2019 as a visiting PhD student. In his research he focuses on time series data mining techniques, including pre-processing, representation, classification and prediction. He is now working on online time series segmentation with the purpose of dimension reduction, especially on how to apply Automated Machine Learning methods for this task.
Jeroen is a Master student who joined the ADA Research Group in September 2019. He obtained his Bachelor&rquo;s degree in Computer Science at Leiden University in 2018. He will study the classic computer science problem of model counting, which is the counting version of the satisfiability problem (SAT). Model counting has applications in probabilistic inference, which is a crucial component in planning and optimisation problems. Specifically, he aims to gain a better understanding of behaviour of state-of-the-art model counters.
[ LinkedIn ]
Gilles is a Master's student Computer Science at LIACS. Previously he finished his BSc Computer Science and Economics at LIACS and the Erasmus School of Economics. Parallel to that he completed his BSc Psychology at Leiden University. His interests span the fields of AI, Machine Learning, Optimization and High Performance Computing, and their applications to real world problems.
Preveously, he developed an author centered graphical interface to the Microsoft Academic data base called ACE. He did this at ADA under supervision of Jesper van Engelen and Holger Hoos. Currently, he is working on his Master's thesis where he is developing a system for the automated selection and configuration of early time series classification algorithms, under supervision of Can Wang, Mitra Baratchi, and Holger Hoos.
[ LinkedIn ]
Laurens is a Master student at Leiden University, who joined the ADA group in November 2019. He received his Bachelor's degree in Lifestyle Informatics (human-centered AI) at VU Amsterdam. He is currently working on his Master Thesis under the supervision of Mitra Baratchi and Holger Hoos, studying the prediction of performance measures and optimisation of geographical regions, with an emphasis on spatial representation learning.
Laurens' main interest is in the intersection of AI and humanities, and he likes to undertake projects aiming to leverage the possibilities of AI to contribute to social and societal issues.
[ LinkedIn ]
Nelly Rosaura Palacios Salinas
Nelly is a Master's student in the CS and Advanced Data Analytics program at LIACS who joined the ADA Research Group in April 2020. She holds a Bachelor's degree in Applied Mathematics and Computer Science from the National Autonomous University of Mexico. She completed a research program on Information Analysis of Web Contents in Social Media at the Kanazawa Institute of Technology supported by the Japan International Cooperation Agency. Her fields of interest are Urban Computing, Distributed Data Mining, and Automated Machine Learning.
Nelly currently working on her Master Thesis proposal under the supervision of Mitra Baratchi and Jan van Rijn. In the project she will be studying the effects of applying Automated Machine Learning (AutoML) methods to Satellite Imagery analysis, as well as the importance of their hyperparameters.
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Jaco is a master's student in Computer Science & Advanced Data Analytics within the Artificial Intelligence track. He is working on his master thesis project on COVID-19 spread prediction. The aim of his project is to enhance existing epidemiology models using new mobility data sets. He works under supervision of Mitra Baratchi and Holger Hoos.
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