Prof. Dietmar Jannach
University of Klagenfurt, Austria
Bio: Dietmar Jannach is a full professor of Information Systems at the University of Klagenfurt, Austria. Before joining this university in 2017, he was a professor of Computer Science at TU Dortmund, Germany. In his research, he focuses on the application of intelligent system technology to practical problems and the development of methods for building knowledge-intensive software applications. In the last years, Dietmar Jannach worked on various practical aspects of recommender systems. He is the main author of the first textbook on the topic published by Cambridge University Press in 2010 and was the co-founder of a tech startup that created an award-winning product for interactive advisory solutions
Title: Session-based Recommendation: Challenges and Recent Advances
Abstract: In many applications of recommender systems, a larger fraction of the user population are first-time users or are not logged in when they use the service. In these cases, the item suggestions by the recommender cannot be based on individual long-term preference profiles. Instead, the recommendations have to be determined based on the observed short-term behavior of the users. Due to the high practical relevance of session-based recommendation, different proposals were made in recent years to deal with the particular challenges of the problem setting. In this talk we will review some of these challenges and provide a survey on recent advances in the field. A specific focus on the talk will be on the particularities of the e-commerce domain.
Infineon Technologies AG, Germany
Bio: Reiner John received a diploma degree in Electrical Engineering from the University of Metz/Perpignan, France, in 1984. He started his career at the Siemens Semiconductor Group in Munich in the test system development. From 1989 to 1991 he was responsible for the training of customers in the Siemens Automation Group. From 1991 to 1996 he joined the Siemens Automotive Division in Regensburg, and was responsible for software development processes of μ-controllers. In 1996 he joined the Siemens Semiconductors Division and has been working in several quality- and production management positions. From 2000 to 2006 he was responsible for the Infineon Silicon Foundry Taiwan office. Currently he is responsible for the coordination of public funded projects at Infineon’s R&D Funding Department, including several large projects related to automated and assisted driving.
Title: The 2nd wave of AI – Thesis for success of AI in trustworthy, safety critical mobility systems
Abstract: In the era of digital transformation, when flexibility and deep understanding in the operation of complex products becomes the key competitive advantage, Artificial Intelligence (AI) is the accepted method to drive the digitalization for the transformation of the industry and their industrial products. These products with highest complexity are based on multi-dimensional requirements as well as novel components, e.g. dedicated CPUs which support AI operations in the cloud and at the edge, as well as dedicated sensors with specialized AI capabilities. One of the most prominent examples is the automotive industry and the products based on high semiconductor content for functional integration, such as highly automated cars including the related industrial and manufacturing itself. The change towards more AI driven applications is present and it is faster and faster emerging in nearly all areas of the industry and will enable new innovative industrial and manufacturing models. The key enabler to the certification and uses of the 3rd Generation of AI methods in safety critical systems is the understanding and the transparence of the decision-making process. The key hurdle to implement this is the certification process which is mandatory for safety critical systems in mobility.
Centre National de la Recherche Scientifique(LAAS-CNRS)
Bio: Louise Travé-Massuyès (http://homepages.laas.fr/louise) holds a position of Directrice de Rechercheat Laboratoire d’Analyse et d’Architecture des Systèmes, Centre National de la Recherche Scientifique(LAAS-CNRS, https://www.laas.fr), Toulouse, France; head of the Diagnosis and Supervisory Control Team (https://www.laas.fr/public/en/disco) from 1994 to 2015. Her research interests are all related to diagnosis reasoning, tackled by model-based and data-driven approaches. This theme, which she developed throughout her career, led her to consider various formalisms to address the family of problems covered by the diagnosis field. She has been particularly active in establishing bridges between the diagnosis communities of Artificial Intelligence and Automatic Control.She is among the coordinators of the “USER” Strategic Field, assigned to diagnosis and health monitoring topics,within the French Aerospace Valley World Competitiveness Cluster (http://www.aerospace-valley.com/en), and serves as the contact evaluator for the French Research Funding Agency. She serves as Associate Editor for the well-known Artificial Intelligence Journal (https://www.journals.elsevier.com/artificial-intelligence). She is member of the International Federation of Automatic Control IFAC (https://www.ifac-control.org/)Safeprocess Technical Committee.
Title: Contributions of diagnostic reasoning to the general demand for AI in the industry
Abstract: AI applications have never been as popular as today. The enthusiasm of all branches of the industry is in tune and agrees to say that AI technologies can lift many industrial locks for customer value creation, productivity improvement, and insight discovery. Huge business opportunities are expected in this process. Numerous applications are also foreseen in medicine and heath care, agriculture and environment, transport/mobility, and energy domains. Faced with this expectation, where do we situate ourselves? In this talk, I will focus on engineering and process applications and will identify the main requests and the needs in these domains. I will then focus on my area of expertise, which is diagnostic reasoning, and explain how existing diagnosis theories can bring their contribution based on the presentation of some applications that address specific needs in these domains. I will conclude my talk by drawing my picture of what is still missing to satisfy the current expectation.