MCML Delegation Visit: Research Breakfast

Jeannette M. Wing is Executive Vice President for Research and Professor of Computer Science at Columbia University. She previously served as Avanessians Director of the Data Science Institute. Her current research interests are in trustworthy AI. Her areas of research expertise include security and privacy, formal methods, programming languages, and distributed and concurrent systems. She is widely recognized for her intellectual leadership in computer science, and more recently in data science. Wing’s seminal essay, titled “Computational Thinking,” was published more than a fifteen years ago and is credited with helping to establish the centrality of computer science to problem-solving in all other disciplines.

Eleonore Fournier-Tombs is the Head of Anticipatory Action and Innovation at UNU-CPR, previously at UNU Macau, with an interest in data and technologies for sustainable development. During her career, Eleonore Fournier-Tombs has worked as a data scientist throughout the United Nations system and conducted research at the intersection of technology and gender, migration, democracy and health. In 2012, she was awarded the UN21 Award by Secretary General Ban Ki Moon for her work at UN-OICT on the Rio+20 Conference. She then worked for the Human Development Report Office from 2012 to 2015, where she managed human development data and online communications. Between 2015 and 2018, she obtained her PhD from the university of Geneva, during which she developed a machine learning method to measure the quality of political deliberations online. She was then awarded a post-doctoral fellowship at McGill University, where she worked on using this tool to analyse parliamentary debates in the Canadian territories of Nunavut, Yukon, and the Northwest Territories.

Daniel Cremers holds the Chair for Computer Vision and Artificial Intelligence at TUM. He conducts research in the fields of image processing, machine learning and robotics. The aim of this research is to teach machines how to analyze and interpret image data. The methodological focus of his research is on convex optimization, statistical learning and neural networks. He was awarded the Gottfried Wilhelm Leibniz Prize in 2016 — Germany’s highest academic honor.

Stefan Feuerriegel holds a dual appointment at the LMU Munich School of Management and the Faculty of Mathematics, Informatics, and Statistics. His research focuses on developing AI algorithms to support data-driven decision-making for businesses and public organizations. He is also dedicated to advancing ‘AI for good’, aiming to create positive social impact through responsible and ethical AI applications.

Reinhard Heckel holds the Chair for Machine Learning at TUM. He focuses on developing algorithms and theoretical foundations for deep learning: particularly in medical imaging application and on the utilization of DNA as a digital information technology. He was named to Capital’s "40 under 40" in 2022.