Abstract speakers
![Prof. dr. Antal van den Bosch](/research/bernoulli/calendar/institute-wide-events/2018/prof.-dr.-antal-van-den-bosch.jpg)
Speaker: Prof. dr. Antal van den Bosch
Title
MC Turing in da house: Getting creative with language models
Abstract
Language models are the working horse technology in automatic translators and speech recognizers; psycholinguists and neurolinguists use them for their robust predictive power. Their implementation allows them to be used not only as analysers, but also as language generators. This ability allows to run creative computing experiments. I will describe two studies, one on generating science fiction text, and one on generating hiphop lyrics. Although the underlying method is the same (e.g. character-based LSTMs), the two genres impose different demands on the quality of the output. The science fiction experiment involved a co-creating writer who had to steer the computer along the path of coherence; the hiphop experiment involved mixing several types of control involving the hard-to-grasp concept of flow. Neither of the experiments had a predictable outcome, and were performed in public. Did the experiments work? What did we learn so far?
Bio
Antal van den Bosch is director of the Meertens Institute of the Royal Netherlands Academy for Arts and Sciences, Amsterdam, and Professor of Language and Speech Technology in the Faculty of Arts at Radboud University Nijmegen. His work is in the crossâsection of machine learning, language technology, and the humanities, with a focus on digital humanities, social media mining, and applications of text mining in a range of academic and societal fields. He is guest professor at the Computational Linguistics and Psycholinguistics Research Centre at the University of Antwerp, Belgium, a member of the Netherlands Royal Academy of Arts and Sciences, and fellow of the European Association for Artificial Intelligence.
![Daniel Gebler](/research/bernoulli/calendar/institute-wide-events/2018/daniel-gebler-2(cto).jpg)
Speaker: Daniel Gebler
Title: The next wave of machine learning - from data science to full stack ML platforms
Abstract: Picnic is the world’s fastest growing online supermarket that makes grocery shopping simple, fun, and affordable for everyone.
In this keynote we will make a deep-dive into the main challenge of e-commerce fulfillment: deliver under uncertainty (real-world physical
operation) with ultra-high accuracy (99% on-time) in narrow time windows (20 min). We will demonstrate how our fleet of real-time
connected vehicles, smart planning algorithms, precise monitoring tools and predictive distribution models form a ML-driven logistical
platform that has the potential to become the logistical backbone for all E-commerce in Europe. Then we provide a look behind the scenes of
our smart planning algorithm that broke world records of the famous traveling salesman problem (TSP). Finally, we deliver insights into
the architecture and design of our distribution eco-system (planning, monitoring, execution, control components) and explain how we made
them ready for autonomous distribution and self-driving vehicles.
Biography: Daniel Gebler is CTO of Picnic, the world’s fastest growing online supermarket that makes grocery shopping simple, fun, and
affordable for everyone. Previously, he was Director R&D of Fredhopper, responsible for the product and technology roadmap, and
led engineering teams located in Amsterdam and Sofia. Daniel holds a PhD in Computer Science and an MBA.
![Catuscia Palamidessi](/research/bernoulli/calendar/institute-wide-events/2018/catuscia-palamidessi.jpg)
Speaker: Catuscia Palamidessi
Title: New Trends in Security and Privacy
Abstract:
With the ever-increasing use of internet-connected devices, such as computers, smart grids, IoT appliances and GPS-enabled equipments, personal data are collected in larger and larger amounts, and then stored and manipulated for the most diverse purposes. Undeniably, the big-data technology provides enormous benefits to industry, individuals and society, ranging from improving business strategies and boosting quality of service to enhancing scientific progress. On the other hand, however, the collection and manipulation of personal data raises alarming privacy and security issues In this talk, I will delineate some of the modern approaches to privacy protection and secure information flow, and show how new achievements in other fields, in particular Machine Learning, can help in this endeavour.
Biography:
Catuscia Palamidessi is Director of Research at INRIA Saclay (since 2002), where she leads the team COMETE. She got her PhD from the University of Pisa in 1988. She held Full Professor positions at the University of Genova, Italy (1994-1997) and at the Pennsylvania State University, USA (1998-2002). Catuscia Palamidessi's research interests include Privacy, Secure Information Flow, and Concurrency. Her past achievements include the proof of expressiveness gaps between various concurrent calculi, and the development of a probabilistic version of the asynchronous pi-calculus. More recently, she has contributed to establish the foundations of probabilistic secure information flow, she has proposed an extension of differential privacy, and geo-indistinguishability, an approach to location privacy. Catuscia Palamidessi has been appointed Program Committee chair of several conferences, including CONCUR 2000, ICLP 2003, ICALP 2005, SOFSEM 2009, QEST 2011, FORTE 2014, and LICS 2015, and she has served as PC member in more than 90 conferences. She is in the Editorial board of MSCS (CUP), Acta Informatica (Springer) and LIPIcs. She is serving in the Executive Committee of SIGLOG, EATCS, ETAPS, and CSL.
![Mark Roberts](/research/bernoulli/calendar/institute-wide-events/2018/mark-roberts.jpg)
Speaker: Mark Roberts
Title: Between Mathematics and Science
Abstract:
Much, perhaps most, mathematics research is driven by a desire to improve our intrinsic understanding of mathematical ideas and structures. However mathematical techniques also provide essential tools across the sciences. Occasionally these two perspectives come together: new mathematical understanding impacts on science, and scientific problems stimulate the generation of new mathematics. I will illustrate this with three examples of collaborative research at interfaces between mathematics and physics (molecular spectroscopy), mathematics and engineering (spacecraft control) and mathematics and biology (population genetics). In addition to giving brief outlines of both the science and the mathematics I will describe how the collaborations developed and some of the outcomes of the research. Emphasis will be placed on the importance of two-way flows of ideas across interfaces and on the need for strong interdisciplinary engagement.
Biography:
Mark obtained his PhD from the University of Liverpool in 1984. Postdoctoral positions in France, the USA and UK led to permanent positions at the University of Warwick and then the University of Surrey, where he is now an Emeritus Professor. Leave from these institutions enabled him to spend two years at the University of Zimbabwe and three years as the founding Rector of the African Institute for Mathematical Sciences (AIMS) centre in Tanzania. Mark’s research interests have included topics in geometry, dynamical systems and astrodynamics. He is currently re-inventing himself as a population geneticist.
Last modified: | 10 February 2021 1.27 p.m. |