AG Keim - Datenanalyse und Visualisierung

THERESA

In the THERESA project, the research team is developing an AI-based system that analyzes videos of physiotherapy exercises. The AI recognizes movements and small training devices such as bands or dumbbells, calculates the forces involved, and determines the training intensity. The system also supports patients outside the clinic and promotes sustainable rehabilitation through precise exercise analysis and gamification approaches.

Finding Correlations in functionally equavalent Proteins

In recent years, protein sequence data has grown rapidly, holding valuable scientific and medical insights. This project investigates restrictions in protein sequences by analyzing alignments of functionally equivalent proteins to identify regularities such as correlated positions or residue patterns. These patterns are essential for proper folding and cellular functions. The visual analytics tool VisAlign supports this analysis by combining automated correlation detection with interactive visualization.

Visual Analytics of Movement and Event Data

Advances in positioning technologies have led to vast amounts of movement data, creating a need for scalable analysis methods. While existing tools in data mining and visualization often ignore spatiotemporal context, this project develops theoretical foundations and scalable methods to analyze movement in relation to contextual information from datasets and human expertise.

CURRENT RESEARCH PROJECTS

SFB 1760: SiNoiSi - Silence, Noise and Signal in Language

The Collaborative Research Center SFB 1760 investigates how silence and noise as fundamental components of linguistic signals shape the interpretation of meaning and how humans successfully communicate despite incomplete or distorted information.

Smart Green City: Economic Assistance System for Lake Constance Shipping

The project develops an AI-based assistance system built on a digital twin to support the energy-efficient operation of electric vessels on Lake Constance.

REGAiT

Traceable AI-based gait-analysis for suspect reidentification

SFB-TRR 161: Quantitative Methods for Visual Computing

The Collaborative Research Center SFB-TRR 161 develops data-driven methods in visual computing to efficiently analyze, visually represent, and make large-scale and complex data accessible and understandable for humans.

THERESA

AI-based, Interactive Exercise Feedback from Smartphone Video Recordings for Promotion and Maintenance of Health in Training with Therapeutic Small Devices

COMPLETED RESEARCH PROJECTS

VIKING

Federal Ministry of Education and Research (BMBF, Germany) in the VIKING project.

PEGASUS

PEGASUS: Analysis of Heterogeneous Mass Data for Crime Prevention.

Data Analysis & Visualization

Data Analysis & Visualization

THERESA

Knowledge Generation in Visual Analytics

VASA

Finding Correlations in functionally equavalent Proteins

Visual Analytics of Movement and Event Data

SFB 1760: SiNoiSi - Silence, Noise and Signal in Language

Smart Green City: Economic Assistance System for Lake Constance Shipping

REGAiT

SFB-TRR 161: Quantitative Methods for Visual Computing

THERESA

VIKING

PEGASUS

DAYDREAMS

PRIMAGE

Matching Tracking Data with VGI

SPARTA

Smart Data Lake

Knowledge Generation in Visual Analytics

ASGARD

VICTORIA

Questions at the Interfaces

IN2DREAMS

FLORIDA

Visual Analysis of Movement and Event Data

MoveBank Virtual Research Environment

Finding New Overlapping Genes and Their Theory (FOG Theory)

Finding Correlations in Functionally Equivalent Proteins