Keynote Speakers

Tomaso A. Poggio

Tomaso A. Poggio is a physicist whose research has always been between brains and computers. He is now focused on the mathematics of deep learning and on the computational neuroscience of the visual cortex.

He is the Eugene McDermott Professor in the Dept. of Brain & Cognitive Sciences at MIT and the director of the NSF Center for Brains, Minds, and Machines at MIT. Among other awards, he received the 2014 Swartz Prize for Theoretical and Computational Neuroscience and the IEEE 2017 Azriel Rosenfeld Lifetime Achievement Award.

A former Corporate Fellow of Thinking Machines Corporation, a former director of PHZ Capital Partners, Inc. and of Mobileye, he was involved in starting, or investing in, several other high tech companies including Arris Pharmaceutical, nFX, Imagen, Digital Persona, Deep Mind, and Orcam.


César A. Hidalgo

César A. Hidalgo is a Chilean-Spanish-American scholar known for his contributions to economic complexity, data visualization, and applied artificial intelligence.

Hidalgo currently holds a Chair at the Artificial and Natural Intelligence Institute (ANITI) at the University of Toulouse. He is also an Honorary Professor at the University of Manchester and a Visiting Professor at Harvard’s School of Engineering and Applied Sciences. Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group, climbing through the ranks from Assistant to Associate Professor. Prior to working at MIT, Hidalgo was a research fellow at Harvard’s Kennedy School of Government. Hidalgo is also a founder of Datawheel, an award-winning company specialized in the creation of data distribution and visualization systems. He holds a Ph.D. in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile.

Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. Hidalgo is also the author of three books: Why Information Grows (Basic Books, 2015), The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021).


Marianne Huchard

Marianne Huchard is a Full Professor of Computer Science at the University of Montpellier since 2004, where she teaches courses in knowledge engineering and software engineering. She develops her research at LIRMM (Laboratory of Informatics, Robotics, and Microelectronics at Montpellier). She obtained a Ph.D. in Computer Science in 1992, during which she investigated algorithmic questions connected to the management of multiple inheritances in various object-oriented programming languages.

She is leading research work in Formal Concept Analysis (FCA) for more than 25 years. She is recognized by the international community being Program Chair of CLA 2016 and she is regularly a member of the program committees of Concept Lattices and their Applications conference  (CLA) and International Conference on Formal Concept Analysis (ICFCA).

She contributed to various aspects of FCA: efficient algorithms; relational concept analysis (RCA), a framework that extends FCA to multi-relational datasets; the connection between RCA and other formalisms, such as propositionalization or description logics; methodology and application of FCA to several domains, including environmental datasets, ontology engineering, and as well software engineering driven by knowledge engineering and FCA.