ADA Research Group

Group members.

 

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).

[ Google Scholar ∙ ResearchGate ∙ Twitter ∙ LinkedIn ∙ Personal Website ∙ UBC Homepage (somewhat dated) ]

 

Mitra Baratchi

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.

[ Google Scholar ∙ Personal Website ∙ Twitter ∙ LinkedIn ]

 

Jan van Rijn

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).

[ Google Scholar ∙ Personal Website ]

 

Matthias König

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 Renting

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 Arp

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.

[ Google Scholar ∙ LinkedIn ]

 

Maedeh Nasri

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).

 

Annelot Bosman

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 Wąsala

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.

 

Andreas Paraskeva

Andreas starated his PhD research with the ADA research group in September 2023, under the supervision of dr. Jan N. van Rijn and Prof.dr. Maarten de Rijke. Prior to this, he joined the ADA research group in January 2023 as a Master student, when he began his initial research under the guidance of dr. Jan N. van Rijn and dr. Joao Pedro Correia dos Reis.

Andreas' research revolves around the realm of parsimonious architectures, with a particular focus on the application of Automated Machine Learning (AutoML) methods for improving the efficiency of conversational agents, and reducing their compute footprint.

Andreas is part of the LESSEN project, a collaborative project working with a diverse team of researchers based at multiple universities in the Netherlands and industrial stakeholders. The LESSEN project and his research are funded by the Dutch Research Council (NWO).

[ LinkedIn ]

 

Sandra Straková

 

Ziwei Zhang

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'.

 

Maria Kavvadia

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.

 

Óscar Nebreda Bernal

 

Peter van Driel

 

Ramiro Kroonenburg

 

Pablo Rojas Sedo

 

Tomke Meyer

 

Sam Vermeulen

 

Tim Haasdijk

 

ADA @ RWTH Aachen

Igor Vatolkin - (Assistant Professor (Akademischer Rat))

Marie Anastacio - (Post-doc)

Anja Jankovic - (Post-doc)

Anna Münz - (PhD candidate)

Julian Dierkes - (PhD candidate)

Henning Duwe - (PhD candidate)

Wadie Skaf - (PhD candidate)

Justin Dettmer - (PhD candidate)

Nick Kocher - (PhD candidate)

Hadar Shavit - (PhD candidate)

Thijs Snelleman - (Research programmer)

Robin Trautmann - (MSc student)

Nils Eberhardt - (MSc student)

Marcel Baumann - (Student assistant)

Tobias Amelingmeyer - (Student assistant)

Tilman Hoffbauer - (Student assistant)

Jyotirmaya Patra - (Student assistant)

Brian Schiller - (Student assistant)

Noah Peil - (Student assistant)

Aylin Özek - (Student assistant)

Andreas Romann - (Student assistant)

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).

 

Adjunct members

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

Jasmin Kareem - PhD Candidate, JADS/TU Eindhoven