Technische Universität Berlin (TU Berlin) is a member of the Berlin University Alliance, making it one of Germany’s Universities of Excellence. With approximately 33,000 students and more than 7,000 members of staff, it is one of the largest universities of technology in Germany. TU Berlin is also a highly international university: 29% of its students are from abroad, and it enjoys many successful research and teaching cooperations with countries all over the world. The areas covered by its seven faculties are unique for a university of technology, bringing together natural sciences and technology, planning sciences, economics and management, social sciences, and humanities under one roof. This wide range of disciplines enables TU Berlin to adopt a holistic approach in its work on important issues impacting the future such as digitalization, sustainability, climate protection, and artificial intelligence. Technische Universität Berlin seeks to develop science and technology for the benefit of society, and
TU Berlin is significantly involved in three approved Clusters of Excellence in the Excellence Strategy of the federal and state governments.
Faculty of Electrical Engineering and Computer Science
Electrical engineering and computer science are of key importance to many areas of modern everyday life, including health, energy, mobility, communication, and security. To benefit from the synergies that exist between them and the interdisciplinary opportunities they offer, electrical engineering and computer science are combined in a single faculty at TU Berlin. This combined approach is essential today for digitalization, artificial intelligence, and robotics. This is reflected in the broad range of research and teaching at the faculty.
An extensive publication output, regular external funding grants of 10 million euros and above, and outstanding research awards such as three Gottfried Wilhelm Leibniz Prizes and two Alexander von Humboldt Professorships all contribute to the faculty’s reputation worldwide. There are more than 6,000 students studying at the faculty, who benefit from a modern, wide range of courses. In recent years, the faculty has developed unique degree programs around the core disciplines of electrical engineering and computer science. These include Computer Engineering, Media Technology, Digital Media & Technology, Business Informatics, and Information Systems Management, as well as the international and specialized master’s programs Computational Neuroscience, Automotive Systems, and ICT Innovation.
© Philipp Arnoldt
So far, the following projects have been realised in cooperation with TU Berlin
NEXT-G: Explainable and Trustworthy AI/ML for 6G and Beyond
LLM-SumCheck: Investigating Advanced Evaluation Techniques for LLM-Generated Summaries of German News Articles
TOUCAN: Transparency in Cloud-Native Architecture and Engineering
FDaaS – A System for Collaborative and Decentralized Federated Learning
OCIS: Optimal Control of Interconnected Systems
DISCO: Distributed Ledger Communication for Smart Contracts
FRUN: A Data-Driven Framework for Optimal Decision-Making Under Uncertainty
SYNERGY: Synergies of distributed artificial intelligence and renewable energy generation
SecCloud – Secure Processing of confidential Data in untrusted Environments
Cheetah – Hardware specialisation for efficient data stream processing in Fog Computing scenarios
QUASIKO – Quality measurement through simulation of conversations
ALMA – Automated fault detection and root cause analysis for a cloud computing infrastructure
DORIAN – Reproducibility, Inspection, and AutomatioN of Data-Oriented experiments
SMILE – Supporting MIgration to serverLess Environments
ADAM – Approximate analysis of massive data streams through modern hardware
DYNAMIC – Dynamic social graphs in distributed social networks
SONIC – Social Network InterConnect
3D-Telko – Implementierung eines abwärtskompatiblen Telefonkonferenzdienstes mit 3D-Audio-Funktion
EEinIR – Balancing exploration and exploitation (multi armed bandit) in information retrieval systems
Curcuma – Persönlicher Datenschutz durch selbstbestimmtes Cloud-Computing
ENtRANCe – ExteNsible and geneRic AuthorizatioN for Cloud resources and personal files
UFESQ – User-Friendly Estimation of Speech Quality for Telecommunications and Network Carriers
SDWN – Software-Defined Wireless Networking (SDWN) für den Einsatz in Enterprise- und Internet-Service-Provider (ISP)-Netzwerken
CloudME – CloudNet Market Enabler
sBlended Prototyping – Entwicklung neuer Prototyping-Ansätze zur verbesserten nutzerzentrierten Entwicklung von mobiler Software in allen Phasen des Usability-Engineering Lifecycles
Gaming-QoE-Model – Mobiler-Campus-Charlottenburg (App): Plattform zur Untersuchung von QoE of Mobile Gaming
ASSEMS – Adaptive Software-Sicherheitsmechanismen für Echtzeit Many-Core Systeme
ModSched – Domänen-Unabhängiges Modulares Scheduler-Framework für Heterogene Multi- und Many-Core Architekturen
EHAC – Erkennung Hardware-basierter Angriffe auf Computerhauptspeicher
GaaS – Gamification as a Service
CV_TTS – Entwicklung einer synthetischen Stimme einer Corporate Voice auf Basis eines vorliegenden Sprachkorpus und deren Optimierung mittels instrumenteller Schätzer
RADAR – Skalierbare Analyse von unstrukturierten Daten zur Ableitung von entscheidungsunterstützenden Informationen
SMeC – Secure Media Cloud
CrowdMAQA – Motivation and Automatic Quality Assessment in Paid Crowdsourcing Online Labor Markets
IUPD – Immediate Usability für Interaktive Public Displays
CDC – Context Data Cloud
AUNUMAP – Automatische Nutzercharakterisierung für Marktforschung und Prototypenentwicklung anhand psychographischer Daten aus Social Media und Sprachanwendungen
