Keynotes

The Power of Visual Analytics:
Combining Data Analytics and Visualization for Exploring Big Data

Never before in history data is generated and collected at such high volumes as it is today. For the analysis of large data sets to be effective, it is important to include the human in the data exploration process and combine the flexibility, creativity, and general knowledge of humans with the enormous storage capacity and the computational power of today’s computers. Visual Analytics helps to deal with the flood of information by integrating the human in the data analysis process, applying its perceptual abilities to the large data sets. Presenting data in an interactive, graphical form provides effective ways to understand and analyze large data sets, allowing novel discoveries and empowering individuals to take control of the analytical process.

The talk presents the potential of visual analytics and discusses the role of automated versus interactive visual techniques in dealing with big data. A variety of application examples ranging from customer feedback analysis over network security to sports analytics illustrate the exciting potential of visual analysis techniques but also their current limitations.

Biography

Daniel A. Keim is professor and head of the Information Visualization and Data Analysis Research Group in the Computer and Information Science Department of the University of Konstanz, Germany. He has been actively involved in data analysis and information visualization research for more than 25 years and developed a number of novel visual analysis techniques for large data sets. He has been program co-chair of the IEEE InfoVis and IEEE VAST as well as the ACM SIGKDD conference.

Dr. Keim got his Ph.D. and habilitation degrees in computer science from the University of Munich. Before joining the University of Konstanz, Dr. Keim was associate professor at the University of Halle, Germany and Senior Technology Consultant at AT&T Shannon Research Labs, NJ, USA.

Open LLMs: The comeback of open models and current trends in the LLM landscape

In this talk Leandro will give an overview of the driving forces behind the accelerated progress of LLMs, share some of the challenges and opportunities of open large language models and discuss what it means to be truly open. He will then dive into recent developments in the LLMs space and discuss what to expect in the coming months.

Biography

Leandro von Werra is a research lead at Hugging Face and also co-leads the BigCode open-science project that aims at developing large language models for code in an open and responsible way with models such as StarCoder2. He is the creator of a popular Python library called TRL, which combines transformers with reinforcement learning and other effective fine-tuning methods.