Holger H. Hoos (professor, head of group)
ADA @ LIACS ADA @ UBC
Former members ∙ PhD genealogy
ADA @ LIACSHolger 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.
Yanyan Xu is a visiting scholar in LIACS. She joined ADA Research Group in September 2018. She received her PhD degree in Institute of Software, Chinese Academy of Sciences and her MSc and BSc degrees in Sun Yat-sen University. Since then, she has worked in School of Information Science and Technology, Beijing Forestry University, and now she is an associate professor.
Yanyan Xu has a broad interest in artificial intelligence and algorithm design, and she is particularly interested in pattern recognition and deep learning, as well as heuristic algorithms in robotics and formal methods. Especially, she is working on combining formal methods with deep learning.
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.
Yi joined the ADA Research Group in September 2018 as a visiting PhD candidate. She is a PhD candidate at the Institute of Computing Technology, Chinese Academy of Sciences. Yi received her master's degree in computer technology from Beijing University on Posts and Telecommunications in 2014.
Yi's research interests include heuristic algorithms for NP-hard problems and automatic algorithm design using optimization and learning techniques. Currently, she is working on using programming by optimisation to improve the performance of heuristic algorithms for solving the maximum clique problem.
Jesper van Engelen
Jesper joined the ADA Research Group in August 2017 and is currently conducting research in the field of automated semi-supervised learning for his Master's thesis. He obtained his Bachelor's degree in Computer Science from Leiden University in 2013, and started his Master's degree there in 2015. In the Fall of 2016, he was a visiting student at the ETH Zürich in Switzerland.
Jesper's research interests include semi-supervised learning, AutoML, social network analysis, and general machine learning. Besides the occasional skiing or hiking trip, he enjoys working on open-source software in his spare time.
Daniël joined the ADA Research Group in September 2018 as a Master's student. He obtained his Bachelor's degree in Computer Science from Leiden University in 2017. For his Master's thesis he is conducting research in methods solving Stochastic Constraint Optimization Problems specifically the possibilities of applying Automated Algorithm Configuration. Among others, this research includes the fields of Probabilistic Logic Programming and Constraint Programming.
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
Chuan Luo - Researcher, Microsoft Research Asia