Collaborative Research Center

SFB-TRR 161

Quantitative Methods for Visual Computing

We are living in a data society in which data is generated at amazing speed; individuals, companies, organizations, and governments are on the brink of being drawn into a massive deluge of data. The great challenge is to extract the relevant information from vast amounts of data and communicate it effectively.

Typical scenarios include decision and policy making for urban and environmental planning or understanding relationships and dependencies in complex networks, e.g., social networks or networks from the field of bioinformatics. These scenarios are not only of interest to specialized experts; in fact, there is a trend toward including the broad public, which requires the information to be presented in a reliable, faithful, and easy-to-understand fashion.

Visual computing can play a key role in extracting and presenting the relevant information.

In visual computing research the aspect of quantification is often neglected. The SFB-TRR 161 seeks to close this gap.

The long-term goal is to strengthen the research field by establishing the paradigm of quantitative science in visual computing.

About the SFB-TRR 161

News

All SFB-TRR 161 News

SFB-TRR 161 Events

Jan 20th, 2025, 4 pm - 6 pm

LMU Munich

Lecture | AI in Research: Speeding Ahead or Losing Ground on Scientific Integrity?

Held by:

Thomas Kosch, HU Berlin

Abstract:

Artificial Intelligence (AI) promises to enhance the speed and efficiency of scientific discoveries. However, the use of AI presents challenges related to the validity and reproducibility of its generated findings. In my talk, I will explore the impact of AI on human-computer interaction research, showing how expectations of AI influence user behavior and addressing the reproducibility challenges associated with generative AI. These challenges show the risk of AI generating inaccurate or misleading content, raising concerns about AI-supported research processes' reliability, transparency, and accountability. I will outline research directions to develop methodologies to integrate AI responsibly into research workflows. My talk will conclude with a discussion of future research directions and the importance of transparency and reproducibility for AI tools to align with the principles of open science.

Bio:

Thomas Kosch is a professor of Human-Computer Interaction at the Humboldt University of Berlin. His research centers on advancing collaborative interactions between humans and AI systems through computational modeling and design. He studies user behavior and context to create intelligent interfaces that foster mutual understanding and improve the synergy between humans and interactive AI systems. His research includes prototyping and evaluating novel AI-based interfaces that support intuitiveness and efficiency. Furthermore, he examines how AI impacts research practices and methodologies for correct scientific applicability, validity, reproducibility, and transparency.

Location:

LMU Munich, Room: third floor, room 357

The lecture will be transmitted to the University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012. and to the University of Konstanz, Room: ZT 702.

All doctoral researchers are asked to take part in the events of the lecture series.

Jan 24th, 2025, 2.15 pm -3.15 pm

University of Stuttgart

Talk | Learning with Music Signals: Technology Meets Education

Held by:

Meinard Müller, International Audio Laboratories Erlangen

Abstract:

Music information retrieval (MIR) is a dynamic research field at the intersection of engineering and the humanities, connecting disciplines such as signal processing, machine learning, musicology, and digital humanities. In this presentation, we explore learning in MIR from both technological and educational perspectives, using music as a tangible application domain. Our focus is on integrating deep learning with traditional engineering approaches to develop explainable hybrid models. By collaborating with domain experts and utilizing specialized music corpora, we demonstrate how computational tools can advance musicological research while uncovering data biases and confounding factors in modern technologies. Furthermore, we emphasize how music can facilitate interactive learning in technical disciplines, promoting innovation at the crossroads of technology and education.

Bio:

Meinard Müller received the Diploma degree (1997) in mathematics and the Ph.D. degree (2001) in computer science from the University of Bonn, Germany. After his postdoctoral studies (2001-2003) in Japan and his habilitation (2003-2007) in multimedia retrieval in Bonn, he worked as a senior researcher at Saarland University and the Max-Planck Institut für Informatik (2007-2012). Since 2012, he has held a professorship for Semantic Audio Signal Processing at the International Audio Laboratories Erlangen, a joint institute of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and the Fraunhofer Institute for Integrated Circuits IIS. His research interests include music processing, music information retrieval, audio signal processing, and motion processing. He wrote a monograph titled "Information Retrieval for Music and Motion" (Springer 2007) and a textbook titled "Fundamentals of Music Processing" (Springer 2015). In 2020, he was elevated to IEEE Fellow for contributions to music signal processing.

Location:

University of Stuttgart, VISUS,  Room 00.012

The talk will be available via WebEx.

Jan 27th, 2025, 4 pm - 6 pm

LMU Munich

Lecture | tbd

Held by:

Felix Putze, Universität Bremen

Location:

LMU Munich, Room: tbd

The lecture will be transmitted to the University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012. and to the University of Konstanz, Room: ZT 702.

All doctoral researchers are asked to take part in the events of the lecture series.

Jan 30th, 2025, 10.30 am - 12 pm

University of Stuttgart

Talk | tbd

Held by:

Michael Burch, FH Graubünden, CH

Location:

University of Stuttgart, VISUS,  Room 00.012

The talk will be available via WebEx.

Feb 3rd, 2025, 4 pm - 6 pm

University of Stuttgart

Lecture | tbd

Held by:

Jürgen Bernard, Universität Zürich

Location:

University of Stuttgart, Visualization Research Center (VISUS), Room: 00.012University of Konstanz, Room: ZT 702

The lecture will be transmitted to the University of Konstanz, Room: ZT 702

All doctoral researchers are asked to take part in the events of the lecture series.

May 26th - 28th, 2025, full days

Humboldt Haus, Aichberg bei Lindau am Bodensee

Doctoral Retreat of the SFB-TRR 161

Oct 6th - 7th, 2025, full days

HdbL Herrsching

Internal Status Seminar of the SFB-TRR 161

Past Events