Scientific Keynote
 | Haus der Universität, Schlösslistrasse 5, 3008 Bern, Switzerland |
 | 8 February 2024, 9:00 CET |
 | Maxime Cordy, Université du Luxembourg |
Abstract
Variability modeling has long been a crucial component of software engineering, providing a systematic approach to managing and understanding the diverse requirements of complex software-intensive systems. Meanwhile, the field of machine learning has witnessed remarkable growth, catalyzing the development of intelligent systems that adapt to changing contexts and data. In this keynote, we embark on a journey that traverses the intersection of these two domains, exploring the ways in which variability modeling and analysis can support the development of machine learning systems. Drawing from our past (and sometimes failed) experiences and personal thoughts, this presentation will delve into the opportunities and challenges of integrating variability modeling techniques with the complex and uncertain nature of machine learning. We will focus particularly on how variability modeling can help to improve robustness, adaptability, and scalability of machine learning models and systems.
Bio
Maxime Cordy is a Research Scientist at SnT — the Interdisciplinary Research Centre on Security, Reliability, and Trust at the University of Luxembourg. He works on software engineering, artificial intelligence, and their intersection, with a focus on software verification & testing, trustworthiness of machine learning, MLOps and variability-intensive systems. He has published 100+ peer-reviewed papers and has served in the review committees of flagship venues in these areas. The key vision that drives his research is to empower Industry and Society with the capability to develop and deploy complex software solutions effectively and reliably. To achieve this, he develops and evaluates theories, methods, and tools across multiple application domains and technology readiness levels. His research is inspired by and applies to several industry partners in various sectors such as finance, energy, and automotive. He is deeply engaged in technology transfer and collaborative research with the industry, e.g., through the creation of spin-off companies and the leadership of private-public partnership projects at SnT. He is also scientific coordinator for the new National Center of Excellence in Research for Financial Technologies, whose primary role is to support Luxembourg’s financial institutions in their innovation activities.
