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Distinguished Lectures

Contact: Prof Christoph Schommer, Prof Leon van der Torre, Prof Raymond Bisdorff, Prof Martin Theobald, Prof Ulrich Sorger, Prof Pascal Bouvry

Distinguished Lectures (2018)

We are honored to host the following speakers:

  • Prof Julia Stoyanovich, Professor of Computer Science at Drexel University.
  • Prof Jan Broersen, Professor of Philosophy at University of Utrecht.

 

DISTINGUISHED LECTURES (2017)

We are honored to host the following speakers:

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DISTINGUISHED LECTURE X

 Joanne Bryson, Professor of Computer Science at the University of Bath, UK, and Princeton University.

AI Ethics: Artificial Intelligence, Robots, and Society

Time and Place: Tuesday, 7 November 2017; 15h00; Campus Belval. Room 4.180, Maison du Savoir, Campus Belval

Abstract
here it comes

Bio
Joanna Bryson is a Reader (tenured Associate Professor) at the University of Bath, and an affiliate of Princeton's Center for Information Technology Policy (CITP). She has broad academic interests in the structure and utility of intelligence, both natural and artificial. Venues for her research range from reddit to Science. She is best known for her work in systems AI and AI ethics, both of which she began during her PhD in the 1990s, but she and her colleagues publish broadly, in biology, anthropology, sociology, philosophy, cognitive science, and politics. Current projects include ``Public Goods and Artificial Intelligence'', with Alin Coman of Princeton Psychology and Mark Riedl of Georgia Tech, funded by Princeton's University Center for Human Values. This project includes both basic research in human sociality and experiments in technological interventions. Other current research include understanding the causality behind the correlation between wealth inequality and political polarization, generating transparency for AI systems, and research on machine prejudice deriving from human semantics. She holds degrees in Psychology from Chicago and Edinburgh, and in Artificial Intelligence from Edinburgh and MIT. At Bath she founded the Intelligent Systems research group (one of four in the Department of Computer Science) and heads their Artificial Models of Natural Intelligence.

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DISTINGUISHED LECTURE IX

 

Kittichai Lavangananda, Professor of Computer Science at KMUTT University, Bangkok, Thailand.

Application of Genetic Algorithm in Spatial Economics : Emergence of Cities

Time and Place: Wednesday, 25 October 2017; 15h00; Room 2.240, Campus Belval. Maison du Savoir, Campus Belval

 

Abstract
The emergent behavior is crucial to the study and planning of cities. Scientists and city planners have proposed different theories on how cities are emerged from trading among individuals and there are several factors which can effect the final outcome. These theories had been transformed into different algorithms on emergence of cities. Changes in location of individuals within a region are usually governed by constrains, which is based on consumers and producers relationship that exist among the population. However, these algorithms are described superficially with high level of abstraction. Not enough attention had been paid on how the effect of different initial setups, and how different evaluation methods in the computation of the algorithm may have on the emergence. Assessing the efficiency of the final emergence from these algorithms is best performed where an ideal or optimal emergence is available for comparison. However, without performing exhaustive search, determination of optimal emergences from an arbitrary setup is almost impossible. From computational and optimization perspectives, there are so many aspects in the simple trading of individuals in this type of Spatial Economics. This talk will focus on just three aspects. Firstly, to illustrate whether different types of initial setups and computations may have an effect on the final emergence. Secondly, to apply Genetic Algorithm in an attempt to determine an optimal emergence from a given setup. Finally, to determine whether global transaction cost at an optimal emergence is likely to subsume individual transaction costs for all individuals too.

Bio
Prof Lavangnanada received his B.Sc. in Computational Science from Hull University, in 1985 and M.Sc. in Computing from Cardiff University in 1987, U.K. He completed his Ph.D. studies in Artificial Intelligence at Mechanical Engineering Centre (MEC) at Cardiff University, U.K. in 1995. He has been a faculty member at the School of Information Technology (SIT), King Mongkut’s University of Technology Thonburi (KMUTT), Thailand since 1996. At present, he is an Associate Professor and an Assistant Dean for Special Activities. His administrative experience includes the Associate Dean for Research and International Affairs from 2000 to 2009. He was the Project Leader of the Thailand partner in 2 EU-Asia IT&C projects (APoST - ASI/B7-301/97/0126-15 and EAPSTRA - ASI B7-301/71 548(3152-094) during 2000 to 2004. Prof Lavangnananda is an active research member of the Data and Knowledge Engineering Laboratory (D-Lab) at SIT. His research interest is in the Computational Intelligence related areas (Data Mining, Evolutionary Computation, Machine Learning, Neural Networks) and their applications. His latest research and development was the Prototype of Signature Verification program for the Department of Special Investigation (DSI), Thailand. He is a Senior Member of IEEE Association and a member of the Editorial Board for Cogent Engineering Journal.

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DISTINGUISHED LECTURE VIII

 Luis Moniz Pereira, Professor at Universidade Nova de Lisboa.

Programming Machine Ethics

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Time and Place: 14 September 2017; 11h00; Campus Belval. Maison du Savoir, Room 04.020

see press release here

Abstract (listen to the talk / audio file):
We stand at the crossroads of Artificial Intelligence, Machine Ethics and their impact on society. Recently, I co-authored a monograph titled "Programming Machine Ethics," where we explore inroads into the terra incognita of machine ethics, by employing Logic Programming and Evolutionary Game Theory. In it we consider both the cognitive realm of the individual and the realm of population morality. My lecture will overview the book's ethics background, scientific and philosophical motivation, theoretical and experimental results, and ongoing research. Beyond that, the roles and impacts of machine ethics for society will be discussed, namely in what regards moral philosophy, jurisprudence and regulations; design of moral autonomous agents; teaching and learning of morality; ethically safe software; and applications.

Bio:

Luís Moniz Pereira, born in Lisbon in 1947, is a Professor of Computer Science (retired) at Universidade Nova de Lisboa, and founder and director of CENTRIA (1993-2008), the Centre for Artificial Intelligence at the same University. He was elected a Fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI) in 2001, received a doctor honoris causa degree from the TU Dresden in 2006 and has been part of the Board of Trustees and the Scientific Advisory Board of IMDEA, the Madrid Advanced Studies Software Institute, since 2006. He is the founding president of the Portuguese Artificial Intelligence Association (APPIA), and serves on the editorial boards of various scientific journals. His research, which he has presented in hundreds of publications, focuses on knowledge representation and reasoning, logic programming, and the cognitive sciences. Currently, he is affiliated with the NOVA Laboratory for Computer Science and Informatics (NOVALINCS). More detailed information, including his awards, teaching and publications, can be found at http://centria.di.fct.unl.pt/~lmp/

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DISTINGUISHED LECTURE VII

 Manolis KOUBARAKIS, Professor of the Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens.

Big Linked Geospatial Data and its Application to Earth Observation

Time and Place: Wednesday, 6 September 2017; Campus Belval. Maison du Savoir, Campus Belval (Room 4.020 ; 15h00 s.t.)

Abstract: Terabytes of geospatial data have been made freely available recently on the Web. For example, data from gazetteers such as Geonames, maps from geospatial search engines like Google Maps and OpenStreetMap, and user-contributed content form social networks such as Foursquare.

Some particularly important rich sources of open and free geospatial data are the satellite programs of various countries such as the Landsat program of the US and the Copernicus programme of the European Union. Satellite images can be utilized in many applications with financial and environmental impact in areas such as emergency management, climate change, agriculture and security. This potential has not been fully realized up to now, because satellite data ``is hidden'' in various archives operated by NASA, ESA and national space agencies. Therefore, a user that would like to develop an application needs to search in these archives, discover the needed data and integrate it in his application. In this talk we show how to ``break these silos open'' by publishing their data as RDF, interlink it with other relevant data, and make it freely available on the Web to enable the easy development of geospatial applications. This work has been funded by EU projects Copernicus App Lab, Melodies, Optique, LEO and TELEIOS.
More information can be found in the following magazine article  http://cgi.di.uoa.gr/~koubarak/publications/2016/grsm.pdf

 Bio:
Manolis Koubarakis is a Professor in the Dept. of Informatics and Telecommunications, National and Kapodistrian University of Athens. He is also an Adjunct Researcher at the Institute of the Management of Information Systems (IMIS) of the “Athena” Research and Innovation Center. He is a Fellow of EurAI (European Association for Artificial Intelligence). He has published more than 170 papers that have been widely cited in the areas of Artificial Intelligence (especially Knowledge Representation), Databases, Semantic Web and Linked Data. His research has been financially supported by the European Commission (projects CHOROCHRONOS, DIET, BRIDGEMAP, Evergrow, OntoGrid, SemsorGrid4Env, TELEIOS, Optique, LEO, MELODIES, WDAqua and BigDataEurope), the Greek General Secretariat for Research and Technology (more recently through the Research Excellence Grant SCARE), the European Space Agency (project Prod-Trees) and industry sources (Microsoft Research and British Telecommunications). He recently co-chaired the European Data Forum 2014 (http://2014.data-forum.eu/), the top European event aiming towards the development of a strong data economy in Europe. He has co-ordinated the well-known projects TELEIOS (http://www.earthobservatory.eu/) and LEO (http://www.linkedeodata.eu/) which developed tools for linked Earth Observation data and linked geospatial data, and applied them to the development of environmental and commercial applications.

    
Manolis’ team has also developed the linked data infrastructure of project MELODIES (http://www.melodiesproject.eu/) which studied how to exploit linked open data in a variety of environmental applications. Manolis currently participates in the project BigDataEurope (http://www.big-data-europe.eu/), a European effort in the area of Big Data with application scenarios in all societal challenges of the Horizon 2020. He also participates in the project WDAqua (http://wdaqua.eu/, Answering Questions using Web Data), a Marie Skłodowska-Curie Innovative Training Network. Finally, he also participates in the project Copernicus App Lab (http://www.app-lab.eu/ ) which will make Copernicus services data available as linked data to aid the development of applications by mobile developers.

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DISTINGUISHED LECTURE VI

 Daniel KUDENKO, Professor of the Dept of Computer Science, University of York, UK.

Abstract Markov Decision Processes for Reinforcement Learning

Time and Place: Wednesday, 5 July 2017, 15h00; Campus Belval. Maison du Savoir, Room 04-4.020, Campus Belval

Abstract:

While reinforcement learning (RL) had recent great successes in game AI and other decision making tasks, there are still two major challenges:

  • Scaling up RL to complex tasks
  • Assuring properties such as safety of the learning process and the learning result.

In this talk, I will show how abstract Markov Decision Processes, reward shaping, and quantitative verification can be used to tackle these challenges.
 

 

  

    

Bio:

Daniel Kudenko is a member of the Computer Science faculty at the University of York. He got a Ph.D. from Rutgers University and a Masters degree from University of the Saarland, Germany. His research interests include machine (reinforcement) learning, multi-agent systems, user modeling, and artificial intelligence for games and interactive entertainment. Within these areas, he published more than 80 peer-reviewed papers, and has been a member of numerous program committees. Dr. Kudenko is currently heading the Reinforcement Learning Group, is carrying out work in Games, Interactive Entertainment and Drama, and is a member of the Artificial Intelligence Research Group.

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DISTINGUISHED LECTURE V

 Dov Gabbay, Emeritus Professor, Augustus de Morgan Professor of Logic, King's College London, UK, and Professor, Bar-Ilan University, Israel.

Weaponizing the Fallacies: Human Effective Argumentation - The Next Step in the Evolution of Logic

Time and Place: Tuesday, 9 May, 16h00s.t.; Maison du Savoir, Room 04-4.310, Campus Belval

Abstract:

This lecture is about weaponizing the Fallacies, and offering them as the new evolutionary logic for the 21st Century. Logicians since Aristotle considered the fallacies as wrong arguments which look correct but are not. They classified them into groups, discussed them and left them by the side-lines of logic as failures. Modern society, with the rise of the internet, Twitter, Facebook and YouTube showed the fallacies as most used and most effective in argumentation and debate. If this is the way humans reason and think then we need to develop the logical theory of the fallacies and legitimise them. This manifesto outlines our approach to the new logic of the 21st century- The systematic use of the fallacies in argumentation and debate as practiced by people in the mass media.

 

Bio:

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DISTINGUISHED LECTURE IV

 Raymond BISDORFF, Full Professor of Computer Science, Dept of Computer Science, University of Luxembourg.

Algorithmic decision theory for solving complex decision problems

Time and Place: Wednesday, 3 May 2017, 16h00s.t.; Maison du Savoir, Room 04-4.020, Campus Belval

Abstract:

 

The objective of Algorithmic Decision Theory (ADT) is to improve the ability of decision makers to perform well when facing these new challenges and problems through the use of methods from theoretical computer science, in particular algorithmic methods. The primary goal of ADT is hence to explore and develop algorithmic approaches for solving decision problems arising in a variety of applications areas. Examples include, but are not limited to:

  • Computational tractability/intractability of social consensus and multiple criteria compromise functions;
  • Improvement of decision support and recommender systems;
  • Development of automatic decision devices including on-line decision procedures;
  • Robust decision making;
  • Learning for multi-agent systems and other on-line decision devices.

This presentation will focus more specifically on multiple criteria decision aiding methodology, the actual research field of the author.

 

Bio:

Raymond Bisdorff holds an LBA Degree in Business Administration from the University of Liège, Belgium (1975), a MScBA (NATO Graduate Degree Apprenticeship in Systems Sciences grant, 1975-1978) and a PhD in Operations Research (OR), supervisor Prof. B. Roy, from the University Paris-Dauphine (1981). He holds, furthermore, a PhD in Management Sciences from the University of Liège, Belgium (2002). He is since 2003 full professor of Applied Mathematics and Computer Science at the University of Luxembourg, where he teaches courses on algorithmic decision theory, multiple criteria decision aiding, computational statistics and discrete mathematics.
He served the international OR community as president of ORBEL - the Belgian OR society (2008-2010), vice-president of EURO - the Association of European OR Societies (1997-2000) and vice-president of IFORS -the International Federation of OR Societies (2005-2007). He was an honourable collaborator of the Institute of Mathematics at the University of Liège (1996-2005), and of the Polytechnical Faculty of Mons (2010-2017). In 2004, he received an honour diploma from HELLORS -the Hellenic Operational Research Society- for chairing the international Programme Committee of the XXth EURO'2004 Conference, Island of Rhodes. His main research interest is focused on outranking based decision aiding algorithms for selecting, ranking, sorting or rating, and clustering with multiple incommensurable performance criteria of uncertain significance and/or missing data ( see http://sma.uni.lu/bisdorff/research.html ). His major articles appeared in EJOR, Computers & OR, 4OR and in JMCDA ( see http://sma.uni.lu/bisdorff/publications.html).

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DISTINGUISHED LECTURE III

 CHRISTOPH BENZMüLLER, PD, Dr. habil, Dept of Mathematics and Computer Science, FU Berlin, Germany

Computational Metaphysics: The Virtues of Formal Computer Proofs Beyond Maths

Time and Place: Monday, 27 March 2017, 16h00 s.t.; Maison du Savoir, Room 04-4.020, Campus Belval

Abstract:

Formal computer proofs - irrespective of being developed interactively with modern proof assistants, fully automatically by automated theorem provers, or in a combination of both - are still rather unpopular amongst many mathematicians. Benzmüller will challenge this stance and point to recent success stories of computer-assisted proofs in maths and beyond. In particular, he will demonstrate how the rigorous assessment of rational arguments in philosophy can be fruitfully supported by modern theorem proving technology. A prominent example includes the “Ontological Argument for the Existence of God“ for which even relevant new insights were recently revealed by automated theorem provers. The latter research activities have inspired the conception of a new, awarded lecture course on “Computational Metaphysics“ at Freie Universität Berlin which brings together students from computer science, maths and philosophy.

Bio:

Christoph Benzmüller is affiliated as Privatdozent for Computer Science and Mathematics with Freie Universität Berlin and Saarland University, Saarbrücken. Currently, he is visiting University of Luxemburg. Previous research stations of Christoph include Stanford University, USA (visiting scholar), Articulate Software, USA (senior researcher), Intl. University of Germany, Bruchsal (full professor), University of Cambridge, UK (senior researcher), Saarland University (associate professor), University of Birmingham, UK and the University of Edinburgh, UK (postdoc). Christoph received his PhD (1999) and his Habilitation (2007) in computer science from Saarland University. His PhD was partly conducted at Carnegie Mellon University, USA. In 2012, Christoph had been awarded with a Heisenberg Research Fellowship of the German National Research Foundation (DFG). Christoph is an expert in higher-order automated and interactive theorem proving, which he utilises as a basis for an approach towards universal logic reasoning. His broader interests concern all aspects of knowledge representation and reasoning. Moreover, Christoph is well known for his interdisciplinary applications. Most recently, for example, he has pioneered, together with colleagues, the area of computational metaphysics. Christoph is trustee and vice-president of CADE (Conference on Automated Deduction), board member of AAR (Association of Automated Reasoning) and spokesman of the section Deduction Systems of the Gesellschaft für Informatik. He serves in various further functions (chair, editorial board, steering committee, trustee, etc.) for various conferences and organisations.

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DISTINGUISHED LECTURE II

 MADY DELVAUX-STEHRES, European Parliament

Civil Law Rules on Robotics

Time and Place: Monday, 20 March 2017, 10h00 s.t.; Campus Belval, Maison du Savoir, Room MSA-E04-4.020

Abstract

Social assistive robots, cyber-physical systems in Industry or Artificial Intelligence (AI) are no longer a concepts in science fiction. We are living through a new Industrial Revolution and it is changing our society. In this context the new agents surpass current laws and now it is necessary to adapt civil rules and to create robot regulations to face the new scenario.

 

Bio

Mady Delvaux-Stehres est députée européenne luxembourgeoise depuis mai 2014. Membre du Groupe des Socialistes & Démocrates au Parlement européen, elle est élue Vice-présidente de la commission des affaires juridiques et suppléante de la commission des affaires économiques et monétaires. Elle fait également partie du comité consultatif sur le code de conduite des députés européens. Entre 1989 et 2014, Mady occupe plusieurs postes ministérielles. Entre 2004 et 2014, elle est Ministre de l’Éducation nationale et de la Formation professionnelle. En tant que Ministre de la Sécurité sociale, des Transports et des Communications de 1994 à 1999, elle s’occupe entre autres de la mise en place de la nouvelle assurance dépendance, de la réorganisation des chemins de fer d’après les directives européennes et de la libéralisation des services téléphoniques. Nommée en 1989 secrétaire d’État à la Santé, à la Sécurité sociale, à la Jeunesse et à l’Éducation physique et aux Sports, elle y engage notamment la réforme de l’assurance maladie. De 1999 à 2004, Mady est membre de la Chambre des députés. En octobre 1987, elle est élue pour la première fois conseillère communale de la Ville de Luxembourg, mandat que les électeurs lui confient à nouveau en 1999. Pendant toutes ces années, Mady est active au sein des Femmes socialistes. Après ses études de lettres classiques à la Sorbonne, Mady est professeur au Lycée Michel Rodange à Luxembourg-Ville jusqu’en 1989, lorsqu’elle est nommée au gouvernement. Mady est née le 11 octobre 1950 à Luxembourg-Ville.

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DISTINGUISHED LECTURE I

 James Cochran, Professor of Statistics, Department of Computer Science, University of Alabama, USA

The importance of Collective Science

Time and Place: Monday, 30 January 2017, 15h00 s.t.; Room E.112 (Campus Kirchberg)

Abstract

The scientific method, which is embodied by statistical inference, is the heart of who we are and what we do as an academic community (which is why some, including me, argue that statistics is the purest of the sciences). Unfortunately, although we may individually think and act scientifically, collectively we often fail to do so. This has led in numerous instances to nonscientific collective behavior. In addition to dramatically retarding the progress of science, this collective behavior has led to misunderstanding of science by the non-scientific community, co-opting of science by the business community, and poor decision making by policy makers those who have relied on the results of our research efforts. In this talk I will address the lack of collective scientific behavior in research on the relative age effect and the ramifications that have resulted. Specifically, I will discuss the i) lack of appreciation for results that are not statistically significant, ii) disregard for conditions that are necessary for establishing a relationship between an antecedent event and a consequent event, and iii) failure to consider, establish, and test appropriate null and alternative hypotheses. I will also present what I believe are appropriate corrective measures.

Bio

James J. Cochran is Professor of Statistics, Rogers-Spivey Faculty Fellow, and Head of the Department of Information Systems, Statistics and Management Science at The University of Alabama. He earned a PhD in Statistics from the University of Cincinnati in 1997, and he has been a Visiting Scholar with Stanford University, the University of South Africa, the Universidad de Talca, and Pôle Universitaire Léonard De Vinci. Professor Cochran was a founding co-chair of Statistics Without Borders and a member of the founding committee for INFORMS Pro Bono Analytics initiative. He established INFORMS’ Teaching Effectiveness Colloquium series and annual case competition. In 2005 Professor Cochran established the International Education Workshop series; through this series colloquia have been held in Uruguay, South Africa, Colombia, Tanzania, Argentina, Kenya, India, Fiji, Croatia, Nepal, Cuba, and Mongolia (with plans for upcoming colloquia in Moldova, Madagascar, and Romania). In 2008 he organized the 2008 ORPA Conference on Using Operations Research to Address Urban Transport and Water Resource Management Issues in Africa. Professor Cochran is founding Editor-in-Chief of the Wiley Encyclopedia of Operations Research and the Management Sciences and the Wiley Series in Operations Research and Management Science as well as the forthcoming Guide to the Analytics Body of Knowledge. He has published over forty research articles and a dozen book chapters, and he is coauthor of seven textbooks in statistics, operations research, and analytics. He has served as a consultant to a wide variety of corporations, government agencies, and not-for-profit organizations around the world. He served as Editor-in-Chief of INFORMS Transactions on Education and serves on the boards of several journals. In 2006 Professor Cochran was elected to the International Statistics Institute, in 2008 he received the INFORMS Prize for the Teaching of OR/MS Practice, in 2010 he received the Mu Sigma Rho Statistical Education Award, and in 2011 he was named a Fellow of the American Statistical Association. In 2014 he became the 86th recipient of the American Statistical Association’s Founders Award, and in 2015 he received the Karl E. Peace Award for outstanding statistical contributions for the betterment of society.