Oliver Bringmann

Oliver Bringmann is a full Professor and head of the Chair of Embedded Systems at the University of Tübingen, Germany, and a member of the board of directors at the FZI Research Center for Information Technology. His research integrates embedded-system design, energy-efficient AI accelerators, dependable automotive perception, and medical AI for capsule endoscopy.

Education & Career

• Ph.D. in Computer Science, University of Tübingen, 2001
• Diploma in Computer Science, University of Karlsruhe (KIT)
• Head, Chair of Embedded Systems, University of Tübingen (since 2012)
• Deputy spokesperson & spokesperson, Dept. of Computer Science, University of Tübingen (2014-2022)
• Board of Directors, FZI Research Center for Information Technology

Research Interests

Bringmann’s group pioneers hardware/software co-design for ultra-low-power Edge-AI, developing RISC-V based accelerators, compiler-aware neural-architecture search, and real-time perception systems for autonomous driving and medical devices. Key topics include:

• Energy-efficient AI architectures (“Edge AI”) and custom accelerator generation
• Robust collective perception under adverse weather (LiDAR, camera, V2X fusion)
• Timing/power-predictable embedded software and system-on-chip design automation
• Hardware-assisted security and safety for automotive & IoT systems
• AI-driven capsule endoscopy localization and anomaly detection

Recent Publication Trends

His 2024-2025 articles reveal a strong shift toward robust multimodal perception for automated driving (snow, fog, collective LiDAR fusion) and Edge-AI medical devices (capsule endoscopy with multi-task CNNs). Core contributions span dataset generation (SCOPE, SnowyLane), safety metrics (LSM), and fast performance modeling for DNN accelerators.

Professional Service & Projects

• Executive/Steering Committees: IEEE/ACM DATE, CODES+ISSS, CASES, ITSS conferences
• EU CATRENE EDA roadmap chapter lead (Embedded Software & ESL-to-RTL)
• Principal investigator in Scale4Edge, OCEAN12, enerDAG and other national projects on energy-efficient sensorics and secure energy trading.

His group maintains extensive collaborations with automotive and semiconductor industry, focusing on dependable, energy-aware embedded intelligence.