[TYPES/announce] Postdoc Position on Verification of Concurrent Systems via Model Learning, Royal Holloway University of London -- Application deadline 9 Jan 2022
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] - Application deadline: Midnight, 9 Jan 2022 - Starting date: As soon as possible - Salary: £35,931-£37,979 - Duration: until February 2023 Applications are invited for the post of Post-Doctoral Research Assistant in the Computer Science Department at Royal Holloway, University of London. Successful applicants will be working on the EPSRC-funded "Verification of Hardware Concurrency via Model Learning" (CLeVer) project (EP/S028641/1), led by Alexandra Silva (UCL/Cornell) and Matteo Sammartino (Royal Holloway University of London). This is a joint research effort involving Royal Holloway University of London, University College London, and ARM, world-leading designer of multi-core chips. For an informal discussion about the post, please contact Dr. Matteo Sammartino on matteo.sammart...@rhul.ac.uk. # Project Description Digital devices increasingly rely on multi-threaded computation, with sophisticated concurrent behaviour becoming prevalent at any scale. As the complexity of these systems increases, there is a pressing need to automate the assessment of their correctness, especially with respect to concurrency-related aspects. Formal verification provides highly effective techniques to assess the correctness of systems. However, formal models are usually built by humans, and as such can be error-prone and inaccurate. The CLeVer project aims to: - develop a novel verification framework that relies on learning techniques to automatically build and verify models of concurrency, with a particular focus on multi-core systems. - apply the framework to real-world verification tasks, in collaboration with ARM. # The ideal candidate We are looking for candidates with a PhD in one of the following areas: model-based testing and verification, formal methods for concurrency, automated analysis of hardware systems. Experience in multiple areas will be valued. Candidates ideally should also have strong programming skills. # Where to apply https://urldefense.com/v3/__https://jobs.royalholloway.ac.uk/0721-259-R-R__;!!IBzWLUs!GBUI4ogBjKihbUy7Zjvs5uy-jYLfnkDBmHoLxe66Aocp0u-vNUn0dwNvEzw0ElB4e1xgKh3NbHDrlQ$
[TYPES/announce] Postdoctoral position on verification of concurrent systems via model learning, Royal Holloway University of London -- Application deadline extended to 17 Oct 2021
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] - Application deadline: Midnight, 17 Oct 2021 - Starting date: As soon as possible after Oct 1 - Salary: £35,931-£37,979 - Duration: until February 2023 Applications are invited for the post of Post-Doctoral Research Assistant in the Computer Science Department at Royal Holloway, University of London. Successful applicants will be working on the EPSRC-funded "Verification of Hardware Concurrency via Model Learning" (CLeVer) project (EP/S028641/1), led by Alexandra Silva (UCL) and Matteo Sammartino (Royal Holloway, University of London). This is a joint research effort involving Royal Holloway University of London, University College London, and ARM, world-leading designer of multi-core chips. For an informal discussion about the post, please contact Dr. Matteo Sammartino on matteo.sammart...@rhul.ac.uk. # Project Description Digital devices increasingly rely on multi-threaded computation, with sophisticated concurrent behaviour becoming prevalent at any scale. As the complexity of these systems increases, there is a pressing need to automate the assessment of their correctness, especially with respect to concurrency-related aspects. Formal verification provides highly effective techniques to assess the correctness of systems. However, formal models are usually built by humans, and as such can be error-prone and inaccurate. The CLeVer project aims to: - develop a novel verification framework that relies on learning techniques to automatically build and verify models of concurrency, with a particular focus on multi-core systems. - apply the framework to real-world verification tasks, in collaboration with ARM. # The ideal candidate We are looking for candidates with a PhD in one of the following areas: model-based testing and verification, formal methods for concurrency, automated analysis of hardware systems. Experience in multiple areas will be valued. Candidates ideally should also have strong programming skills. # Where to apply https://urldefense.com/v3/__https://jobs.royalholloway.ac.uk/0721-259-R__;!!IBzWLUs!B30ivyr_dXHAqITFCIhJmgB781RnlqNHUmGcyfTSRAXlL4L6VMBKQOYi2uWy6lSqc4yr1QCiENRCMw$
[TYPES/announce] Postdoctoral position on verification of concurrent systems via model learning, Royal Holloway University of London, Deadline: 4 May 2020
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] - Application deadline: Midnight, 04 May 2020 - Interview Date: To be confirmed - Starting date: as soon as possible, flexible due to COVID-19; remote working options can be explored. - Salary: £35,931-£37,979, including London allowance (grade 7, pay scales 31-33) - Duration: 33 months Applications are invited for the post of Post-Doctoral Research Assistant in the Computer Science Department at Royal Holloway, University of London. Successful applicants will be working on the EPSRC-funded "Verification of Hardware Concurrency via Model Learning" (CLeVer) project (EP/S028641/1), led by Alexandra Silva (UCL) and Matteo Sammartino (Royal Holloway, University of London). This is a joint research endeavour involving Royal Holloway University of London, University College London, and ARM, world-leading designer of multi-core chips. For an informal discussion about the post, please contact Dr. Matteo Sammartino on matteo.sammart...@rhul.ac.uk. # Project Description Digital devices increasingly rely on multi-threaded computation, with sophisticated concurrent behaviour becoming prevalent at any scale. As the complexity of these systems increases, there is a pressing need to automate the assessment of their correctness, especially with respect to concurrency-related aspects. Formal verification provides highly effective techniques to assess the correctness of systems. However, formal models are usually built by humans, and as such can be error-prone and inaccurate. The CLeVer project aims to: - develop a novel verification framework that relies on learning techniques to automatically build and verify models of concurrency, with a particular focus on multi-core systems. - apply the framework to real-world verification tasks, in collaboration with ARM. # The ideal candidate We are looking for candidates with a PhD in one of the following areas: model-based testing and verification, formal methods for concurrency, automated analysis of hardware systems. Experience in multiple areas will be valued. Candidates ideally should also have strong programming skills. # Where to apply https://jobs.royalholloway.ac.uk/vacancy.aspx?ref=0420-101
[TYPES/announce] Multiple postdoc and PhD positions on verification, concurrency and model learning at University College London and Royal Holloway University of London (Deadline Jan 5, 2020)
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] We invite applications for: - *two* Research Fellow/Senior Research Fellow positions (Deadline: January 5, 2020). Positions are 1 year in the first instance, with the possibility of extension until December 2022. One position will be at University College London, and one at Royal Holloway University of London. - *one* PhD studentship at UCL. Successful applicants will be working on the EPSRC-funded "Verification of Hardware Concurrency via Model Learning" (CLeVer) project. This is a joint research endeavour involving the Computer Science Departments of two UK's leading research-intensive universities -- University College London and Royal Holloway University of London -- and ARM, world-leading designer of multi-core chips. We are looking for candidates with experience in one or more of the following areas: model learning techniques, verification, concurrency, and formal methods. Experience in tool implementation will also be valued. # HOW TO APPLY - Applications for *both* the (Senior) Research Fellow positions should be made here before *January 5, 2020*: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041404=fair=1847641_template=965=1 - Applications for the PhD position should be made here: https://www.ucl.ac.uk/prospective-students/graduate/apply Interested applicants are encouraged to contact Prof. Alexandra Silva (alexandra.si...@ucl.ac.uk) and Dr. Matteo Sammartino (m.sammart...@ucl.ac.uk). # ABOUT THE PROJECT Digital devices increasingly rely on multi-threaded computation, with sophisticated concurrent behaviour becoming prevalent at any scale. As the complexity of these systems increases, there is a pressing need to automate the assessment of their correctness, especially with respect to concurrency-related aspects. Formal verification provides highly effective techniques to assess the correctness of systems. However, formal models are usually built by humans, and as such can be error-prone and inaccurate. This project aims to: - develop a verification framework that relies on learning techniques to automatically build and verify models of concurrency, with a particular focus on multi-core systems. - apply the framework to industrial verification tasks, in collaboration with ARM. The project will provide opportunities for both theoretical and applied research in several areas of Computer Science, including model learning techniques, verification, concurrency, and formal methods.
[TYPES/announce] Deadline Extension: Learning and Automata (LearnAut) 2019 -- LICS 2019 Workshop
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] SUBMISSION DEADLINE EXTENDED to April 6th Learning and Automata (LearnAut) -- LICS 2019 workshop June 23rd - Vancouver, Canada Website: https://learnaut19.github.io Learning models defining recursive computations, like automata and formal grammars, are the core of the field called Grammatical Inference (GI). The expressive power of these models and the complexity of the associated computational problems are major research topics within mathematical logic and computer science, spanning the communities that the Logic in Computer Science (LICS) conference brings together. Historically, there has been little interaction between the GI and LICS communities, though recently some important results started to bridge the gap between both worlds, including applications of learning to formal verification and model checking, and (co-)algebraic formulations of automata and grammar learning algorithms. The goal of this workshop is to bring together experts on logic who could benefit from grammatical inference tools, and researchers in grammatical inference who could find in logic and verification new fruitful applications for their methods. We invite submissions of recent work, including preliminary research, related to the theme of the workshop. Similarly to how main machine learning conferences and workshops are organized, all accepted abstracts will be part of a poster session held during the workshop. Additionally, the Program Committee will select a subset of the abstracts for oral presentation. At least one author of each accepted abstract is expected to represent it at the workshop. Note that participation to the poster session is on a voluntary basis for papers selected for oral presentation. High-quality submissions will be strongly encouraged to submit an extended version to an upcoming special issue of the Machine Learning Journal (https://grammarlearning.org/mlj-gi-special-issue). Topics of interest include (but are not limited to): - Computational complexity of learning problems involving automata and formal languages. - Algorithms and frameworks for learning models representing language classes inside and outside the Chomsky hierarchy, including tree and graph grammars. - Learning problems involving models with additional structure, including numeric weights, inputs/outputs such as transducers, register automata, timed automata, Markov reward and decision processes, and semi-hidden Markov models. - Logical and relational aspects of learning and grammatical inference. - Theoretical studies of learnable classes of languages/representations. - Relations between automata and recurrent neural networks. - Active learning of finite state machines and formal languages. - Methods for estimating probability distributions over strings, trees, graphs, or any data used as input for symbolic models. - Applications of learning to formal verification and (statistical) model checking. - Metrics and other error measures between automata or formal languages. ** Invited speakers ** Lise Getoor (UC Santa Cruz) Prakash Panangaden (McGill University) Nils Jansen (Radboud University) Dana Fisman (Ben-Gurion University) ** Submission instructions ** Submissions in the form of extended abstracts must be at most 8 single-column pages long at most (plus at most four for bibliography and possible appendixes) and must be submitted in the JMLR/PMLR format. The LaTeX style file is available here: https://ctan.org/tex-archive/macros/latex/contrib/jmlr We do accept submissions of work recently published or currently under review. - Submission url: https://easychair.org/conferences/?conf=learnaut2019 - Submission deadline: April 6th - Notification of acceptance: April 25th - Early registration: April 22nd ** Program Committee ** Dana Angluin (Yale University) Borja Balle (Amazon Research Cambridge) Leonor Becerra-Bonache (Université de Saint-Etienne) Alexander Clark (King’s College London) François Denis (Aix-Marseille Université) Kousha Etessami (University of Edinburgh) Matthias Gallé (Naver Labs Europe) Colin de la Higuera (Nantes University) Falk Howar (TU Clausthal) Makoto Kanazawa (Hosei University) Ariadna Quattoni (Naver Labs Europe) Alexandra Silva (University College London) Frits Vaandrager (Radboud University) ** Organizers ** Remi Eyraud (Aix-Marseille Université) Tobias Kappé (University College London) Guillaume Rabusseau (Université de Montréal / Mila) Matteo Sammartino (University College London)
[TYPES/announce] Learning and Automata (LearnAut) 2019 Second Call for Papers -- LICS 2019 Workshop
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] Learning and Automata (LearnAut) -- LICS 2019 workshop June 23rd - Vancouver, Canada Website: https://learnaut19.github.io SUBMISSION DEADLINE March 30th Learning models defining recursive computations, like automata and formal grammars, are the core of the field called Grammatical Inference (GI). The expressive power of these models and the complexity of the associated computational problems are major research topics within mathematical logic and computer science, spanning the communities that the Logic in Computer Science (LICS) conference brings together. Historically, there has been little interaction between the GI and LICS communities, though recently some important results started to bridge the gap between both worlds, including applications of learning to formal verification and model checking, and (co-)algebraic formulations of automata and grammar learning algorithms. The goal of this workshop is to bring together experts on logic who could benefit from grammatical inference tools, and researchers in grammatical inference who could find in logic and verification new fruitful applications for their methods. We invite submissions of recent work, including preliminary research, related to the theme of the workshop. Similarly to how main machine learning conferences and workshops are organized, all accepted abstracts will be part of a poster session held during the workshop. Additionally, the Program Committee will select a subset of the abstracts for oral presentation. At least one author of each accepted abstract is expected to represent it at the workshop. Note that participation to the poster session is on a voluntary basis for papers selected for oral presentation. High-quality submissions will be strongly encouraged to submit an extended version to an upcoming special issue of the Machine Learning Journal. Topics of interest include (but are not limited to): - Computational complexity of learning problems involving automata and formal languages. - Algorithms and frameworks for learning models representing language classes inside and outside the Chomsky hierarchy, including tree and graph grammars. - Learning problems involving models with additional structure, including numeric weights, inputs/outputs such as transducers, register automata, timed automata, Markov reward and decision processes, and semi-hidden Markov models. - Logical and relational aspects of learning and grammatical inference. - Theoretical studies of learnable classes of languages/representations. - Relations between automata and recurrent neural networks. - Active learning of finite state machines and formal languages. - Methods for estimating probability distributions over strings, trees, graphs, or any data used as input for symbolic models. - Applications of learning to formal verification and (statistical) model checking. - Metrics and other error measures between automata or formal languages. ** Invited speakers ** Lise Getoor (UC Santa Cruz) Prakash Panangaden (McGill University) Nils Jansen (Radboud University) Dana Fisman (Ben-Gurion University) ** Submission instructions ** Submissions in the form of extended abstracts must be at most 8 single-column pages long at most (plus at most four for bibliography and possible appendixes) and must be submitted in the JMLR/PMLR format. The LaTeX style file is available here: https://ctan.org/tex-archive/macros/latex/contrib/jmlr We do accept submissions of work recently published or currently under review. - Submission url: https://easychair.org/conferences/?conf=learnaut2019 - Submission deadline: March 30th - Notification of acceptance: April 25th - Registration: TBD ** Program Committee ** Dana Angluin (Yale University) Borja Balle (Amazon Research Cambridge) Leonor Becerra-Bonache (Université de Saint-Etienne) Alexander Clark (King’s College London) François Denis (Aix-Marseille Université) Kousha Etessami (University of Edinburgh) Dana Fisman (Ben-Gurion University) Matthias Gallé (Naver Labs Europe) Colin de la Higuera (Nantes University) Falk Howar (TU Clausthal) Makoto Kanazawa (Hosei University) Ariadna Quattoni (Naver Labs Europe) Alexandra Silva (University College London) Frits Vaandrager (Radboud University) ** Organizers ** Remi Eyraud (Aix-Marseille Université) Tobias Kappé (University College London) Guillaume Rabusseau (Université de Montréal / Mila) Matteo Sammartino (University College London)
[TYPES/announce] LearnAut 2019 first Call for Papers -- LICS 2019 Workshop
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] Learning and Automata (LearnAut) -- LICS 2019 workshop June 23rd, Vancouver, Canada Website: https://learnaut19.github.io SUBMISSION DEADLINE March 30th Learning models defining recursive computations, like automata and formal grammars, are the core of the field called Grammatical Inference (GI). The expressive power of these models and the complexity of the associated computational problems are major research topics within mathematical logic and computer science, spanning the communities that the Logic in Computer Science (LICS) conference brings together. Historically, there has been little interaction between the GI and LICS communities, though recently some important results started to bridge the gap between both worlds, including applications of learning to formal verification and model checking, and (co-)algebraic formulations of automata and grammar learning algorithms. The goal of this workshop is to bring together experts on logic who could benefit from grammatical inference tools, and researchers in grammatical inference who could find in logic and verification new fruitful applications for their methods. We invite submissions of recent work, including preliminary research, related to the theme of the workshop. Similarly to how main machine learning conferences and workshops are organized, all accepted abstracts will be part of a poster session held during the workshop. Additionally, the Program Committee will select a subset of the abstracts for oral presentation. At least one author of each accepted abstract is expected to represent it at the workshop. Topics of interest include (but are not limited to): - Computational complexity of learning problems involving automata and formal languages. - Algorithms and frameworks for learning models representing language classes inside and outside the Chomsky hierarchy, including tree and graph grammars. - Learning problems involving models with additional structure, including numeric weights, inputs/outputs such as transducers, register automata, timed automata, Markov reward and decision processes, and semi-hidden Markov models. - Logical and relational aspects of learning and grammatical inference. - Theoretical studies of learnable classes of languages/representations. - Relations between automata and recurrent neural networks. - Active learning of finite state machines and formal languages. - Methods for estimating probability distributions over strings, trees, graphs, or any data used as input for symbolic models. - Applications of learning to formal verification and (statistical) model checking. - Metrics and other error measures between automata or formal languages. ** Invited speakers ** Lise Getoor (UC Santa Cruz) Prakash Panangaden (McGill University) Nils Jansen (Radboud University) (to be confirmed) ** Submission instructions ** Submissions in the form of extended abstracts must be at most 8 single-column pages long at most (plus at most four for bibliography and possible appendixes) and must be submitted in the JMLR/PMLR format. The LaTeX style file is available here: https://ctan.org/tex-archive/macros/latex/contrib/jmlr We do accept submissions of work recently published or currently under review. - Submission url: https://easychair.org/conferences/?conf=learnaut2019 - Submission deadline: March 30th - Notification of acceptance: April 25th - Registration: TBD ** Program Committee ** Dana Angluin (Yale University) Borja Balle (Amazon Research Cambridge) Leonor Becerra-Bonache (Université de Saint-Etienne) François Denis (Aix-Marseille Université) Colin de la Higuera (Nantes University) Falk Howar (TU Clausthal) Ariadna Quattoni (Naver Labs Europe) Alexandra Silva (University College of London) Makoto Kanazawa (Hosei University) Matthias Gallé (Naver Labs Europe) Frits Vaandrager (Radboud University) Alexander Clark (King’s College London) Kousha Etessami (University of Edinburgh) ** Organizers ** Remi Eyraud (Aix-Marseille Université) Tobias Kappé (University College London) Guillaume Rabusseau (Université de Montréal / Mila) Matteo Sammartino (University College London)
[TYPES/announce] PhD studentship in formal methods & verification at University College London
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] Applications are invited for a PhD studentship at University College London, under the supervision of Prof. Alexandra Silva and Dr. Matteo Sammartino. The start date is flexible. It should be in September 2018 at the latest. The studentship is funded by the UK Research Institute in Verified Trustworthy Software Systems, and will be carried out within the Programming Principles, Logic and Verification (PPLV) group (http://pplv.cs.ucl.ac.uk/). The PPLV group offers an exciting research environment, with outstanding connections with cutting-edge industry. Potential applicants are encouraged to contact Prof. Silva (alexandra.si...@ucl.ac.uk) and Dr. Sammartino (m.sammart...@ucl.ac.uk) for further information and expressions of interest. Applications should be made via the UCL evision system: https://evision.ucl.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app=RRDCOMSING01=0025 === PROJECT DESCRIPTION === Our society is increasingly reliant on complex networking systems, consisting of several components that operate in a distributed/concurrent fashion, exchange data that may be highly sensitive, and are implemented with a mix of open and closed-source code. Examples are Software Defined Networks, cloud computing systems, Internet of Things and others. As the complexity of these systems increases, there is a pressing need of methods and tools to automatically verify security and privacy properties. High quality models – able to express all the behaviours of interest – are of paramount importance to this aim. However, it is often the case that the task of building a model is performed by humans and in a short span of time – if it is performed at all – and as such can be error-prone and inaccurate. The goal of the PhD project is to develop techniques and tools to automate the modelling and verification of networking software systems. The novel idea is to rely on the model learning paradigm, originally proposed in artificial intelligence, to automatically build an automaton model of a running system in a black-box fashion -- purely via interactions with the running system.
[TYPES/announce] DEADLINE EXTENSION: Learning and Automata (LearnAut) -- FLoC 2018 Workshop
tony Brook University) Guillaume Rabusseau (McGill University) Matteo Sammartino (University College London)
[TYPES/announce] 2nd CfP: Learning and Automata (LearnAut) -- FLoC 2018 Workshop
[ The Types Forum (announcements only), http://lists.seas.upenn.edu/mailman/listinfo/types-announce ] Call for Papers: Learning and Automata (LearnAut) -- FLoC 2018 Workshop July 13, University of Oxford, United Kingdom Website: https://learnaut2018.wordpress.com/ SUBMISSION DEADLINE: 24 March 2018 Learning models defining recursive computations, like automata and formal grammars, are the core of the field called Grammatical Inference (GI). The expressive power of these models and the complexity of the associated computational problems are major research topics within the mathematical logic and computer science communities, spanning the international conferences that the Federated Logic Conference (FLoC) brings together. Historically, there has been little interaction between the GI and FLoC communities, though recently some important results started to bridge the gap between both worlds, including applications of learning to formal verification and model checking, and (co-)algebraic formulations of automata and grammar learning algorithms. The goal of this workshop is to bring together experts on logic who could benefit from grammatical inference tools, and researchers in grammatical inference who could find in logic and verification new fruitful applications for their methods. We invite submissions of recent work, including preliminary research, related to the theme of the workshop. Similarly to how main machine learning conferences and workshops are organized, all accepted abstracts will be part of a poster session held during the workshop. Additionally, the Program Committee will select a subset of the abstracts for oral presentation. At least one author of each accepted abstract is expected to represent it at the workshop. LearnAut 18 is also coordinating with the International Conference on Grammatical Inference (ICGI, http://icgi2018.pwr.edu.pl/) which publishes its proceedings in the Proceedings of Machine Learning Research (PMLR: http://proceedings.mlr.press/). Selected LearnAut papers will be offered the possibility to have an extended version published in the proceedings of ICGI. Authors of such papers will be expected to submit the extended version by the ICGI deadline, which will then undergo an additional (light) review process by the ICGI program committee. Topics of interest include (but are not limited to): - Computational complexity of learning problems involving automata and formal languages. - Algorithms and frameworks for learning models representing language classes inside and outside the Chomsky hierarchy, including tree and graph grammars. - Learning problems involving models with additional structure, including numeric weights, inputs/outputs such as transducers, register automata, timed automata, Markov reward and decision processes, and semi-hidden Markov models. - Logical and relational aspects of learning and grammatical inference. - Theoretical studies of learnable classes of languages/representations. - Relations between automata and recurrent neural networks. - Active learning of finite state machines and formal languages. - Methods for estimating probability distributions over strings, trees, graphs, or any data used as input for symbolic models. - Applications of learning to formal verification and (statistical) model checking. - Metrics and other error measures between automata or formal languages. ** Invited speakers ** Alexander Clark (King's College London) Kousha Etessami (University of Edinburgh) Doina Precup (McGill University & DeepMind) ** Submission instructions ** Submissions in the form of extended abstracts must be at most 8 single-column pages long (plus at most four for bibliography and possible appendixes) and must be submitted in the JMLR/PMLR format. The LaTeX style file is available from here: https://ctan.org/tex-archive/macros/latex/contrib/jmlr We do accept submissions of work recently published or currently under review; however such submissions do not qualify for publication in the ICGI Proceedings. - Submission url: https://easychair.org/conferences/?conf=learnaut2018 - Submission deadline: 24 March 2018 - Notification of acceptance: 1 May 2018 - Submission deadline for ICGI proceedings: 15 May 2018 - Registration: http://www.floc2018.org/register/ ** Program Committee ** Dana Angluin (Yale University) Borja Balle (Amazon Research Cambridge) Leonor Becerra-Bonache (Université de Saint-Etienne) Jorge Castro (Universitat Politècnica de Catalunya) François Denis (Aix-Marseille Université) Colin de la Higuera (Nantes University) Falk Howar (TU Clausthal) Kim Larsen (Aalborg University) Ariadna Quattoni (Naver Labs Europe) Bernhard Steffen (TU Dortmund) Alexandra Silva (University College London) James Worrell (University of Oxford) ** Organizers ** Remi Eyraud (Aix-Marseille Université) Jeffrey Heinz (Stony Brook University) Guillaume Rabusseau (McGill University) Matteo Sammar
