Lecturers

Each Lecturer will hold three lessons on a specific topic.
The Lecturers below are confirmed.


Ioannis Antonoglou
Google DeepMind, UK

Topics

General Reinforcement Learning Algorithms


Sanjeev Arora
Princeton University, USA (TBC)

Topics

Theory of Machine Learning, Generative Adversarial Networks & Theoretical Deep Learning


Giuseppe Di Fatta
University of Reading, UK

Topics

Data Science & Knime


Marco Gori
University of Siena, Italy

Topics

Constraint-Based Approaches to Machine Learning

Biography

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.



Phillip Isola
MIT, USA

Topics

Generative Adversarial Networks


Ilias S. Kotsireas
Wilfrid Laurier University, Canada

Topics

Data Mining and High-Performance Computing


Panos Pardalos
University of Florida, USA
 

Topics

Optimization, Networks & Data Science

Biography

Panos M. Pardalos serves as distinguished professor of industrial and systems engineering at the University of Florida. Additionally, he is the Paul and Heidi Brown Preeminent Professor of industrial and systems engineering. He is also an affiliated faculty member of the computer and information science Department, the Hellenic Studies Center, and the biomedical engineering program. He is also the director of the Center for Applied Optimization. Pardalos is a world leading expert in global and combinatorial optimization. His recent research interests include network design problems, optimization in telecommunications, e-commerce, data mining, biomedical applications, and massive computing.



Dolores Romero Morales
Copenhagen Business School, Denmark

Topics

Big Data


Ruslan Salakhutdinov
Carnegie Mellon University
AI Research at Apple, USA

Topics

Deep Learning


Josh Tenenbaum
MIT, USA

Topics

Computational Cognitive Science, probabilistic generative models, and probabilistic programming


Naftali Tishby
Hebrew University, Israel

Topics

Theory of Deep Learning – Information Bottleneck


Topics

Machine Learning, Computational Neuroscience, Artificial Intelligence, Theory of Computation


Joaquin Vanschoren
Eindhoven University of Technology, The Netherlands

Topics

Automatic machine learning


Oriol Vinyals
Google DeepMind, UK

Topics

Deep Learning & Reinforcement Learning




Past Lecturers

The Lecturers of the previous editions:

  • Roman Belavkin, Middlesex University London, UK
  • Yoshua Bengio, Head of the Montreal Institute for Learning Algorithms (MILA) & University of Montreal, Canada
  • Sergiy Butenko, Texas A&M University, USA
  • Marco Gori, University of Siena, Italy
  • Yi-Ke Guo, Imperial College London, UK & Founding Director of Data Science Institute
  • Peter Norvig, Director of Research, Google
  • Panos Pardalos, University of Florida, USA
  • Alex 'Sandy' Pentland, MIT & Director of MIT’s Human Dynamics Laboratory, USA
  • Marc'Aurelio Ranzato, Facebook AI Research Lab, New York, USA
  • Aleskerov Z. Fuad, National Research University Higher School of Economics, Russia