First VMCAI Winter School – CALL FOR PARTICIPATION
VMCAI Winter School is a winter school on formal methods associated with VMCAI 2019 (VMCAI 2019 – 20th International Conference on Verification, Model Checking, and Abstract Interpretation) that took place in Lisbon, Portugal on January 9-12, 2019. In the vein of VMCAI, the school is meant to facilitate interaction, cross-fertilization, and advancement of hybrid methods that combine Verification, Model Checking, Abstract Interpretation, etc.
The VMCAI Winter School program featured two tutorial lectures per day, presented by distinguished speakers and experts in these fields.
List of tutorial lectures:
* An Introduction to Learning from Programs, by Marc Brockschmidt (Microsoft Research, Cambridge, UK)
* Models and Techniques for Analyzing Security Protocols, by Veronique Cortier (Loria, Nancy, France)
* Neural Network Verification, by M. Pawan Kumar (University of Oxford, UK)
* Computing with SAT Oracles: From CDCL SAT Solving to Ubiquitous Industry Adoption, by João Marques-Silva (University of Lisbon, Portugal)
* Abstract Interpretation, by Patrick Cousot (New York University, USA). This tutorial will be complemented by an invited talk by Sylvie Putot (Ecole Polytechnique, France) on “Zonotopic abstract domains for numerical program analysis”.
* Developing distributed protocols formally with Ivy, by Ken McMillan (Microsoft Research, Redmond, USA)
A more detailed program is available at the school website http://vmcaischool19.tecnico.ulisboa.pt/
Organizers: Constantin Enea (IRIF, University Paris Diderot); Vasco Manquinho (INESC-ID, IST – Universidade de Lisboa); Ruzica Piskac (Yale University)
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series has started on October 2020 and runs until March 2021.
The seminars aim to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goal of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information is available here.
IST /INESC-ID Distinguished Lecture – An Ethical Crisis in Computing?
Computer scientists think often of “Ender’s Game” these days. In this award-winning 1985 science-fiction novel by Orson Scott Card, Ender is being trained at Battle School, an institution designed to make young children into military commanders against an unspecified enemy. Ender’s team engages in a series of computer-simulated battles, eventually destroying the enemy’s planet, only to learn then that the battles were very real and a real planet has been destroyed.
The benefits of computing seemed intuitive to us. We truly believe that computing yields tremendous societal benefits; for example, the life-saving potential of driverless cars is enormous! Like Ender, however, we realized recently that computing is not a game–it is real–and it brings with it not only societal benefits, but also significant societal costs, such as labor polarization, disinformation, and smart-phone addiction.
The real issue is how to deal with technology’s impact on society.
Technology is driving the future, but who is doing the steering?
Moshe Y. Vardi is University Professor and the George Distinguished Service Professor in Computational Engineering at Rice University. He is the recipient of several awards, including the ACM SIGACT Goedel Prize, the ACM Kanellakis Award, the ACM SIGMOD Codd Award, the Blaise Pascal Medal, the IEEE Computer Society Goode Award, and the EATCS Distinguished Achievements Award.
He is the author and co-author of over 650 papers, as well as two books. He is a fellow of several societies, and a member of several academies, including the US National Academy of Engineering and National Academy of Science.
He holds seven honorary doctorates. He is a Senior Editor of the Communications of the ACM, the premier publication in computing.