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

May 16th, 2025, 10 am - 12 pm

University of Stuttgart

1st Talk | Towards Responsible Visual Analytics: Fostering Inclusivity, Accessibility and Trustworthiness in the AI Era  

Held by: Ali Sarvghad, University of Massachusetts, Amherst

Abstract:

As data visualizations play an increasingly pivotal role in shaping decisions across personal, public, and scientific domains, ensuring their ethical, inclusive, and accessible design has become more crucial than ever. My work, driven by the growing role of visualizations in decision-making and the integration of AI in the data analysis pipeline, delves into the ethical and responsible dimensions of data visualization. In this talk, I explore the convergence of theory and emerging technologies in advancing responsible visual analytics. Through examples from my research, I will illustrate how understanding graphical perception across diverse audiences, such as older adults, utilizing conversational agents to enhance data collection, and applying differential privacy to safeguard individual privacy fosters inclusion and trust throughout the data lifecycle—from collection and analysis to insight discovery and decision-making. Through real-world applications and empirical research insights, this talk invites a critical rethinking of the ethical responsibilities of visual analytics and proposes a future where applied AI can catalyze ethical and equitable advancements in visual analytics.

Bio:

Ali Sarvghad is a senior visualization researcher and co-director of the HCI-VIS Research Lab in the Manning College of Computer and Information Sciences at the University of Massachusetts Amherst. He is currently a visiting researcher at INRIA with the AVIZ team. His research spans Information Visualization and Responsible Visual Analytics, with a focus on designing, developing, and evaluating novel visualization techniques and frameworks that promote ethical, inclusive, and accessible data analysis. Over the past decade, Ali’s work has bridged theoretical advancements and practical applications, providing empirically grounded guidelines and innovative tools to advance the field of responsible visual analytics. Ali holds a Ph.D. in Computer Science from the University of Victoria, Canada, an M.S. in Software Engineering, and an Honors B.S. in Computer Science from the University Science Malaysia. He was a postdoctoral fellow in the Design Lab at the University of California, San Diego. His research has been recognized with several accolades, including Best Paper Awards at CSCW 2021 and EuroVIS 2022, and Honorable Mention Awards at CHI 2024, CHI 2022, DIS 2021, and VIS 2012.

2nd Talk | Community-Centered Computing for Collective Action and Societal Impact 

Held by: Narges Mahyar, University of Massachusetts, Amherst

Abstract:

Today’s world faces several complex problems, such as climate change, transportation, infrastructure, education, and healthcare. Technology, if designed right, can play an essential role in informing people, raising awareness, sharing data, and connecting communities and decision-makers to make data-informed decisions. In this talk, I present examples of my work on building and studying community-centered tools to empower the general public to engage in real-world sociotechnical problems such as urban planning and climate change. These examples demonstrate my multidisciplinary approach in combining HCI, social computing, information visualization, and human-centered AI to design and build innovative tools and visualization technologies to address complex sociotechnical problems. I will also briefly discuss my work on critical data visualization, which seeks to empower individuals and communities to better understand the data shaping their personal and collective lives. Finally, I will outline my vision for expanding my research to advance democracy, equity, well-being, and sustainability by fostering the inclusion and empowerment of the general public.

Bio:

Narges Mahyar is an Associate Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. She was a 2024–2025 Radcliffe Fellow at Harvard University. Narges’s research intersects Human-Computer Interaction, Information Visualization, Social Computing, and Design. She designs, develops, and evaluates novel social computing and visualization techniques that help people explore, understand, and make data-informed decisions. Over the past decade, she has focused on the emerging interdisciplinary area of “Digital Civics,” which explores new strategies for scaling and diversifying public engagement in massive decision-making processes related to civic issues such as sustainable urban design and climate change mitigation. She holds a Ph.D. in Computer Science from the University of Victoria, an M.S. in Information Technology from the University of Malaya, and a B.S. in Electrical Engineering from Tehran Azad University. She was a postdoctoral fellow in the Department of Computer Science at the University of British Columbia from 2014 to 2016 and in the Design Lab at the University of California San Diego from 2016 to 2018. Her recognition in the field has been repeatedly confirmed through many accolades for her research, including five Best Paper Awards from CHI 2023, Eurovis 2022, CSCW 2020, the Council of Educators in Landscape Architecture 2017, and VAST 2014, as well as three Best Paper Honorable Mention Awards from TiiS 2022, DIS 2021, and ISS 2016.

Location:

University of Stuttgart, VISUS,  Room 00.012

The talk is available via WebEx.

Meeting-ID (access code): 2784 288 7690
Meeting password: PFy69wsmxw8

For participants via WebEx: The transmission will kindly be managed by Patrick Gralka.  He will be on site and monitor/manage the WebEx-Session incl. Q&A during and after the talk as well. Please don´t hesitate to get in touch with Patrick in case of questions or problems regarding the transmission/your online participation: Patrick.Gralka@visus.uni-stuttgart.de

May 22nd, 2025, 2 pm - 4 pm

University of Stuttgart

Human-Centred Machine Learning: Sensemaking, Provenance, and Human-AI Collaboration

Held by: Kai Xu, University of Nottingham

Abstract:

The performance of machine learning models, particularly large language models and generative AI, has dramatically improved in recent years, often matching or even surpassing human capabilities. Despite these advancements, many tasks requiring specialised knowledge and analytical reasoning remain beyond the reach of full automation. These tasks, which I refer to as sensemaking tasks, benefit significantly from a collaborative approach that combines human expertise with machine intelligence. This approach, known as human-in-the-loop or mixed-initiative, leverages interactive data visualisation to foster symbiotic collaboration between humans and AI. In this talk, I will showcase some of my past and current projects, illustrating how this method can tackle complex problems across various application domains by utilising 'provenance' information.

Bio:

Dr. Kai Xu is an Associate Professor in the School of Computer Science at the University of Nottingham, where he serves as the co-director of its Visualisation Group. The University of Nottingham is a member of the prestigious Russell Group, which comprises leading UK universities such as Cambridge and Oxford. Dr. Xu holds the position of chair of the UK Branch of Eurographics, the largest professional body for computer graphics in Europe. Additionally, he is a co-organiser of the Visualisation Group at the Alan Turing Institute, the UK’s national centre for data science and AI. With over two decades of experience in data science research, particularly in data visualisation, sensemaking, and provenance, Dr. Xu has collaborated on numerous research projects, securing funding exceeding £10 million. These projects involve partnerships with domain experts from diverse sectors, including government and industry, to develop innovative human-AI collaboration tools that address critical challenges. Dr. Xu’s extensive publications have been featured in leading visualisation and human-computer interaction (HCI) journals and conferences. His work has garnered international recognition such as the best paper at EuroVis and the VAST challenge award.

Location:

University of Stuttgart, VISUS,  Room 00.012

The talk is available via WebEx.

Meeting-ID (access code): 2733 166 0937
Meeting password: HdyGuqdK223

For participants via WebEx: The transmission will kindly be managed by Patrick Gralka.  He will be on site and monitor/manage the WebEx-Session incl. Q&A during and after the talk as well. Please don´t hesitate to get in touch with Patrick in case of questions or problems regarding the transmission/your online participation: Patrick.Gralka@visus.uni-stuttgart.de

May 24th, 2025, 1 pm to 7 pm

Visualization Research Center, University of Stuttgart

Participation in 'Tag der Wissenschaft' - 'Science Day'

The University of Stuttgart's Science Day takes place on May 24, 2025. At the Visualization Research Center (Allmandring 19, 70569 Stuttgart), the SFB-TRR 161 will give insights into the world of visualization research. Visitors are invited to discover how visualizations can help to extract the relevant information from data and how they make visible what would otherwise remain hidden.

The full program can be viewed int the event app provided by the University of Stuttgart: https://universitaet-stuttgart.lineupr.com/tdw/schedule/venue/visualisierungsinstitut-visus 

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