Research in the field of "Data Science"
The Data Science +X Research Center at the BHT conducts use-inspired basic research.
Our use-inspired basic research is often based on public funding with industrial or health care partners. This basic research has a horizon of about 36-60 months and looks at fundamental and often risky research questions. Few projects also investigate to focus on very narrow and rather applied research questions. The typical project duration for these projects is about 12-18 months.
AR/VR supported orientation and memory training for Post-Acute Neurorehabilitation
Monitoring: Peace & Security (DSF)
Citizen-based Monitoring for Peace & Security in Era of Synthetic Media and Deepfakes
Reduction of the impact of untreated wastewater on the environment in case of torrential rain
KI basiertes Insektenmonitoring mit Citizen Science
A mobile VR/AR laboratory for case and field studies as well as clinical trials to evaluate novel forms of virtual therapies and scientific research.
Green Consumption Assistant (BMUV)
Artificial Intelligence (AI) based Assistant that will support consumers to make more sustainable shopping decisions
Personalized online-tracking of spatial memory consolidation in a virtual environment
with focus on the interfaces between the life sciences, robotics, mechanical engineering and computer science
A solution approach consisting of synthetically generating all required comparison images from a real-world industry grade 3D CAD data and using them for object identification.
Based on sensor data acquired from the patients during training sessions the system adapts to patients individual training needs and thereby serves as a non-drug therapy for people with hypertension.
Energy Cost Savings (EU-EFRE: BENE)
Forecasting Energy Cost Savings in Weather-Guided Heating Control
A novel method for the therapy of school anxiety in children and adolescents using a VR application as part of a pilot study.
Transparency in Machine Learning
A collaboration with Philipp Schmidt, Amazon Research, and Prof. Timm Teubner, TU Berlin, to investigate whether and when transparency in AI actually increases trust in AI systems.
Maschinelles Lernen für Biodiversität (BMUV)
Entwicklung von Verfahren des Maschinellen Lernens (ML) zur automatisierten Erkennung von Insekten
RDW utilizes imperfections of human perception to introduce small changes like rotations or translations to steer the user away from the tracking boundaries.
Our work highly encourages the development of clinically applicable segmentation tools based on deep learning.
Computational models for patient stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care
Pervasive Touch (DFG)
Methods for designing robust microgestures for touch-based interaction
Virtual body exposure therapy for adolescent anorexia nervosa patients
Machine Reading im Supply Chain Management für KMUs
With the help of the generic controller, haptic feedback can be generated for users even over distances...
Efficient language models for SMEs
Artificial intelligence (AI) based cross-company service platform for the german industry
Platform for AI-based decision support for supply chain management
Digitale Studiengänge - Analyse von Erfolgs- und Abbruchfaktoren
Illusionary Surface Interfaces (DFG)
We aim to create novel interactive experiences, that exploit multisensory illusions in order to extend the range of interface properties that can be displayed, using only everyday object surfaces as interfaces.
WINK _ Gestensteuerung (BMBF)
Die Hände und Finger als primäre Werkzeuge in der physischen Welt sollen für die Interaktion mit digitalen Geräten nutzbar werden.
Examining hate communication in social media, online forums and commentary areas
to exploit the data that universities have about the academic achievements of their current and past students
Research platform "Literary field GDR": authors, works, networks – Pilot study
Mediatorplattform für interoperable Bildungstechnologien (mEDUator)
Enableing integrated mobility services for medium-sized enterprises.
Datenintegrations- und Datenanalysemethoden sowie darauf aufbauende KI-Anwendungen für Sturzprävention – Beispielanwendung für alternative relevante Fragestellungen
Outcome Prediction from Patient Letters
AI-based outcome prediction from clinical texts
A prediction model for permanent graft loss in renal transplant patients
Clinical Assertion Classification
Evaluation of state-of-the-art medical language models
Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Automatic extraction of clinical conditions from patient records
A Quantitative Force Map of the Mitotic Spindle (DFG)
Understanding the way in which cells engineer micrometer-scale structures.
Mittels 3D-Druck zelluläre Strukturen zu simulieren und Beziehungen zwischen Materialeigenschaften und Geometrie etablieren
Developing the prototype of a novel patient-centered Smart Health Service platform
Converting medical case data from clinics into legally secure data products.
Data Quality in Machine Learning Systems
developing methods for better automation of monitoring of data quality, improvement of data quality and prediction of data quality problems in ML production systems
Optimizing Online Customer Interaction by Advanced Data Analytics (OCIDA)
Smart Web Data (BMWi)
Bringing together Web 3.0, Big Data and Industry 4.0
Berlin Big Data Center (BMBF)
Re-Launching research into big data and IT security in Germany
Anwendungsmöglichkeiten der Blockchaintechnologie in KMU identifizieren und Wissenstransfer zu leisten.
Smart Learning (BMBF)
Part of the funding program "Digital Media in Vocational Education and Training"
Strengthen the positions of European fashion retailers among their world-wide competitors.