New Keynote Speaker: Prof. Michael I. Jordan, University of California, Berkeley, USA

Prof. Michael I. Jordan, University of California, Berkeley, USA

Pehong Chen Distinguished Professor
Department of EECS
Department of Statistics
AMP Lab
Berkeley AI Research Lab
University of California, Berkeley, USA

Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. He received his Masters in Mathematics from Arizona State University, and earned his PhD in Cognitive Science in 1985 from the University of California, San Diego. He was a professor at MIT from 1988 to 1998. His research interests bridge the computational, statistical, cognitive and biological sciences. Prof. Jordan is a member of the National Academy of Sciences, a member of the National Academy of Engineering and a member of the American Academy of Arts and Sciences. He is a Fellow of the American Association for the Advancement of Science. He has been named a Neyman Lecturer and a Medallion Lecturer by the Institute of Mathematical Statistics. He was a Plenary Lecturer at the International Congress of Mathematicians in 2018. He received the Ulf Grenander Prize from the American Mathematical Society in 2021, the IEEE John von Neumann Medal in 2020, the IJCAI Research Excellence Award in 2016, the David E. Rumelhart Prize in 2015 and the ACM/AAAI Allen Newell Award in 2009. He is a Fellow of the AAAI, ACM, ASA, CSS, IEEE, IMS, ISBA and SIAM. In 2016, Professor Jordan was named the “most influential computer scientist” worldwide in an article in Science, based on rankings from the Semantic Scholar search engine.

https://people.eecs.berkeley.edu/~jordan/

https://en.wikipedia.org/wiki/Michael_I._Jordan

https://scholar.google.com/citations?user=yxUduqMAAAAJ&hl=en

Biographical highlights

  • Professor, University of California, Berkeley, 1998-present
  • Professor, MIT, 1988-1998
  • Honorary Doctorate, Yale University, 2020
  • Honorary Professor, Peking University, 2018-present
  • Distinguished Visiting Professor, Tsinghua University, 2017-2019
  • Chaire d’Excellence, Fondation Sciences Mathématiques de Paris, 2012
  • Member, National Academy of Sciences
  • Member, National Academy of Engineering
  • Member, American Academy of Arts and Sciences
  • Fellow, American Association for the Advancement of Science
  • Fellow of the AAAI, ACM, ASA, CSS, IEEE, IMS, ISBA and SIAM
  • Elected Member, International Statistical Institute
  • AMS Ulf Grenander Prize in Stochastic Theory and Modeling, 2021
  • IEEE John von Neumann Medal, 2020
  • Plenary Speaker, International Congress of Mathematicians, 2018
  • IJCAI Research Excellence Award, 2016
  • David E. Rumelhart Prize, 2015
  • IMS Neyman Lecture, 2011
  • ACM/AAAI Allen Newell Award, 2009
  • SIAM Activity Group on Optimization Prize, 2008
  • IEEE Neural Networks Pioneer Award, 2006
  • IMS Medallion Lecture, 2004

 

New Keynote Speaker: Naftali Tishby, Hebrew University, Israel

Professor of Computer Science and Computational Neuroscientist at the Hebrew University of Jerusalem.

Ruth & Stan Flinkman Family Endowment Fund Chair in Brain Research.

Awards: Israel Defense Prize, Landau Prize in Computer Science, The 2019 IBT Award in Mathematical Neuroscience.

He is one of the leaders in machine learning research and computational neuroscience, and his numerous former students serve in key academic and industrial research positions all over the world. Tishby was the founding chair of the new computer-engineering program, and a director of the Leibnitz Center for Research in Computer Science at Hebrew University. Tishby received his PhD in theoretical physics from Hebrew University in 1985, and was a research staff member at MIT and Bell Labs from 1985 to 1991. Tishby has been a visiting professor at Princeton NECI, the University of Pennsylvania, UCSB, and IBM Research.

He works at the interfaces between computer science, physics, and biology which provide some of the most challenging problems in today’s science and technology. We focus on organizing computational principles that govern information processing in biology, at all levels. To this end, we employ and develop methods that stem from statistical physics, information theory and computational learning theory, to analyze biological data and develop biologically inspired algorithms that can account for the observed performance of biological systems. We hope to find simple yet powerful computational mechanisms that may characterize evolved and adaptive systems, from the molecular level to the whole computational brain and interacting populations.

New Keynote Speaker: Marta Kwiatkowska, Computer Science Dept., University of Oxford, UK

Marta Kwiatkowska, Computer Science Dept., University of Oxford, UK

Marta Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College, University of Oxford, and Associate Head of MPLS. Prior to this she was Professor in the School of Computer Science at the University of Birmingham, Lecturer at the University of Leicester and Assistant Professor at the Jagiellonian University in Cracow, Poland. She holds a BSc/MSc in Computer Science from the Jagiellonian University, MA from Oxford and a PhD from the University of Leicester. In 2014 she was awarded an honorary doctorate from KTH Royal Institute of Technology in Stockholm.

Marta Kwiatkowska spearheaded the development of probabilistic and quantitative methods in verification on the international scene and is currently working on safety and robustness for machine learning and AI. She led the development of the PRISM model checker, the leading software tool in the area and widely used for research and teaching and winner of the HVC 2016 Award. Applications of probabilistic model checking have spanned communication and security protocols, nanotechnology designs, power management, game theory, planning and systems biology, with genuine flaws found and corrected in real-world protocols. Kwiatkowska gave the Milner Lecture in 2012 in recognition of “excellent and original theoretical work which has a perceived significance for practical computing”. She is the first female winner of the 2018 Royal Society Milner Award and Lecture, see her lecture here, and won the BCS Lovelace Medal in 2019. Marta Kwiatkowska was invited to give keynotes at the LICS 2003, ESEC/FSE 2007 and 2019, ETAPS/FASE 2011, ATVA 2013, ICALP 2016, CAV 2017, CONCUR 2019 and UbiComp 2019 conferences.

She is a Fellow of the Royal Society, Fellow of ACM, member of Academia Europea, Fellow of EATCS, Fellow of the BCS and Fellow of Polish Society of Arts & Sciences Abroad. She serves on editorial boards of several journals, including Information and Computation, Formal Methods in System Design, Logical Methods in Computer Science, Science of Computer Programming and Royal Society Open Science journal. Kwiatkowska’s research has been supported by grant funding from EPSRC, ERC, EU, DARPA and Microsoft Research Cambridge, including two prestigious ERC Advanced Grants, VERIWARE (“From software verification to everyware verification”) and FUN2MODEL (“From FUNction-based TO MOdel-based automated probabilistic reasoning for DEep Learning”), and the EPSRC Programme Grant on Mobile Autonomy.

New Keynote Speaker: Georg Gottlob F.R.S., Computer Science Dept, University of Oxford, UK

Georg Gottlob F.R.S., Computer Science Dept, University of Oxford, UK

Georg Gottlob is a Royal Society Research Professor and  a Professor of Informatics at Oxford University. and at TU  Wien.  At Oxford he is a Fellow of St John’s College.  His interests include knowledge representation, logic and complexity, and database and Web querying. He has received various awards, among which the Wittgenstein Award (Austria) and the Ada Lovelace Medal (UK). He is a Fellow of the Royal Society, of the Austrian Academy of Science, the Leopoldina National  Academyof Sciences (Germany), and of the Academia Europaea. He was a founder of Lixto, a company specialised in semi-automatic web data extraction which was acquired by McKinsey in 2013. Gottlob was awarded an ERC Advanced Investigator’s Grant for the project “DIADEM: Domain-centric Intelligent Automated Data Extraction Methodology”. Based on the results of this project, he co-founded Wrapidity Ltd, a company that specialised in fully automated web data extraction, which was acquired in 2016 by Meltwater.  He recently co-founded DeepReason.ai, which puts the logic-based VADALOG system into practice and applies it with banks and other corporate customers.

New Keynote Speaker: Marco Gori, University of Siena, Italy

Marco Gori, University of Siena, Italy

Marco Gori received the Ph.D. degree in 1990 from Università di Bologna, Italy, while working partly as a visiting student at the School of Computer Science, McGill University – Montréal. In 1992, he became an associate professor of Computer Science at Università di Firenze and, in November 1995, he joint the Università di Siena, where he is currently full professor of computer science.  His main interests are in machine learning, computer vision, and natural language processing. He was the leader of the WebCrow project supported by Google for automatic solving of crosswords, that  outperformed human competitors in an official competition within the ECAI-06 conference.  He has just published the book “Machine Learning: A Constrained-Based Approach,” where you can find his view on the field.

He has been an Associated Editor of a number of journals in his area of expertise, including The IEEE Transactions on Neural Networks and Neural Networks, and he has been the Chairman of the Italian Chapter of the IEEE Computational Intelligence Society and the President of the Italian Association for Artificial Intelligence. He is a fellow of the ECCAI (EurAI) (European Coordinating Committee for Artificial Intelligence), a fellow of the IEEE, and of IAPR.  He is in the list of top Italian scientists kept by  VIA-Academy.