BB-KI Chips

Brandenburg and Bayern Action for AI Hardware

About

Artificial Intelligence (AI) is a key research field in digitalization and holds the potential to drive growth and prosperity in a disruptive way. However, the role of specialized hardware for AI is still underdeveloped: while corporations such as Xilinx, NVIDIA, ARM, and Intel are increasingly integrating AI elements into their platforms, aspects of AI hardware are barely covered in university education. Dedicated AI-capable hardware is particularly relevant in Germany, as—unlike cloud processing—it does not rely on the collection of data in the cloud, which is problematic from a data protection standpoint.

To align our sociopolitical values—such as the right to privacy, informational self-determination, and data federalism—with data-driven innovation (Industry 4.0, 6G, smart cities, autonomous driving, IoT, monitoring via remote sensing and geodata), edge computing is required. In edge computing, the processing of sometimes highly sensitive information takes place where it originates (“network edge”), and only necessary information is transmitted.

Current university teaching touches only minimally on AI hardware topics due to disciplinary separation. This is where our project aims to make a difference. We seek to address a multidisciplinary target audience (from hardware, AI, and application domains) in an integrative way (through open courses, practice-oriented teaching, and teamwork) and in a realistic context (chip production in Germany, including by students as part of the curriculum). Specifically, we are planning a hybrid, cross-university educational program that combines theoretical foundations, design, and exemplary applications.

Our consortium, with the affiliated Leibniz Institute IHP in Frankfurt (Oder), offers a unique opportunity in Germany for chip manufacturing, allowing students to practically implement AI hardware during their studies.

Funding: 4 million euros from BMFTR (2021-2025).

Consortium members:

  • University of Potsdam:
    • Prof. Dr. Benno Stabernack, Institute of Computer Science
    • Prof. Dr. Milos Krstic, Institute of Computer Science (overall project lead)
    • Prof. Dr. Oliver Korup, Institute of Environmental Science and Geography
    • Prof. Dr. Ulrike Lucke, Institute of Computer Science
  • Technical University of Munich:
    • Prof. Dr. Carsten Trinitis, School of Computation, Information and Technology
    • Prof. Dr. Daniel Cremers, School of Computation, Information and Technology
    • Prof. Dr. Martin Schulz, School of Computation, Information and Technology
    • Prof. Dr. Martin Werner, School of Engineering and Design

Funder

BMFTR Logo

Partnership

University of Potsdam Logo Technical University of Munich Logo

People

(List ordered alphabetically by last name)

Maria Isabel Arango

Maria Isabel Arango

University of Potsdam

Research interests: Hydro-meteorological hazard modelling, including physically-based, statistical, empirical and heuristic models, and multi-hazard analysis and understanding.

Prof. Dr. Daniel Cremers

Prof. Dr. Daniel Cremers

Technical University of Munich

Research interests: Computer vision, machine learning and deep networks, mathematical image analysis (segmentation, motion estimation, multiview reconstruction, visual SLAM), shape analysis, autonomous systems and self-driving cars, variational methods and partial differential equations, convex and combinatorial optimization and statistical inference.

Alejandra Camelo Cruz

Alejandra Camelo Cruz

University of Potsdam

Research interests: Spiking neural networks.

Dr. Vladimir Golkov

Dr. Vladimir Golkov

Technical University of Munich

Research interests: Data structures such as high-dimensional and geometric data, data-processing goals beyond supervised learning, for example clustering or anomaly detection and areas of application such as biomedicine and physics.

Xiaorang Guo

Xiaorang Guo

Technical University of Munich

Research interests: Computer architecture, quantum computing, FPGA programming and digital circuit design.

Ann-Marie Gursch

Ann-Marie Gursch

University of Potsdam

Research interests: Development, implementation and evaluation of a hybrid, cross-university educational offer (especially AI hardware aspects in the university curriculum).

Lilian Hasse

Lilian Hasse

University of Potsdam

Research interests: Development, implementation and evaluation of a cross-university hybrid educational programme to anchor AI hardware topics in the university curriculum.

Dr. Hao Li

Dr. Hao Li

Technical University of Munich

Research interests: Volunteered geographic information, geospatial machine learning, multi-sensor data fusion, geo-semantics, intelligent urban mobility, remote sensing.

Prof. Dr. Ulrike Lucke

Prof. Dr. Ulrike Lucke

University of Potsdam

Research interests: E-learning, technology enhanced learning, online learning, online education, blended learning, learning, eLearning, teaching and learning, pedagogy and education, distance education.

Xuanshu Luo

Xuanshu Luo

Technical University of Munich

Research interests: Edge computing, deep learning, FPGA.

Wejdene Mansour

Wejdene Mansour

Technical University of Munich

Research interests: Indoor localization, 3D indoor scene reconstruction, dynamic human-object interactions in 3D environments.

Max Nowaczyk

Max Nowaczyk

Technical University of Berlin

Research interests: Spiking neural networks and neuromorphic hardware.

Prof. Dr. Oliver Korup

Prof. Dr. Oliver Korup

University of Potsdam

Research interests: Climate change, geology, remote sensing, tectonics, risk analysis, spatial analysis, sedimentology, physical geography, environment, R programming.

Philipp Kreowsky

Philipp Kreowsky

University of Potsdam

Research interests: VLSI architectures for computer-vision, machine-learning applications and higl level hardware desription languages.

Prof. Dr. Milos Krstic

Prof. Dr. Milos Krstic

University of Potsdam

Research interests: Fault tolerant design, design- and test of integrated circuits, asynchronous design, embedded system design.

Kun Qin

Kun Qin

Technical University of Munich

Research interests: Hardware/software codesign, RISC-V and open-source architectures, FPGA/ASIC design and implementations, quantum computing and quantum-based systems.

Jessica Scharrenberg

Jessica Scharrenberg

University of Potsdam

Research interests: Artificial intelligence in hardware for the field of educational technology.

Prof. Dr. Martin Schulz

Prof. Dr. Martin Schulz

Technical University of Munich

Research interests: Parallel and distributed architectures and applications; performance monitoring, modeling and analysis; memory system optimization; parallel programming paradigms; tool support for parallel programming; power-aware parallel computing; and fault tolerance at the application and system level, as well as quantum computing and quantum computing architectures and programming, with a special focus on HPC and QC integration.

Prof. Dr. Benno Stabernack

Prof. Dr. Benno Stabernack

University of Potsdam

Research interests: VLSI architectures for video signal processing and machine learning, energy efficient application specific processor architectures and System-on-Chip (SOC) design.

Dr. Zoran Stamenkovic

Dr. Zoran Stamenkovic

University of Potsdam

Research interests: hardware and software for artificial intelligence applications, system-on-chip design, fault-tolerant circuits and systems, and integrated circuit yield and reliability modeling.

Dirk Stober

Dirk Stober

Technical University of Munich

Research interests: Low-level programming, heterogeneous computing, machine learning accelerators, FPGA programming, novel computer architectures.

Prof. Dr. Carsten Trinitis

Prof. Dr. Carsten Trinitis

Technical University of Munich

Research interests: high performance computer architectures (with a focus on microprocessor architectures), co-design and hardware oriented optimisations as well as computer architectures for spaceflight.

Prof. Dr. Martin Werner

Prof. Dr. Martin Werner

Technical University of Munich

Research interests: Methodological research around topics of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales.

Zhouyi Xiong

Zhouyi Xiong

Technical University of Munich

Research interests: Deep learning, Object detection in remote sensing, onboard AI algorithm.

Yicheng Zhang

Yicheng Zhang

Technical University of Munich

Research interests: Parallel computer architecture, hardware/software codesign, edge learning of neural networks.

Dedong Zhao

Dedong Zhao

University of Potsdam

Research interests: Neuromorphic algorithms, architecture and VLSI; Spiking Neural Networks (SNNs); Networks-on-aChip (NoCs); Globally Asynchronous Locally Synchronous (GALS) Systems.

Teaching Activities

University of Potsdam

  • Chair of Professor Benno Stabernack:
    • System on Chip Architectures
    • Computer Vision Hardware Architecture
  • Chair of Professor Milos Krstic:
  • Chair of Professor Oliver Korup:
    • Data Analysis and Management in Earth System Sciences
  • Chair of Professor Ulrike Lucke:
    • Ethics for Nerds

Technical University of Munich

Joint Curriculum “Edge AI”

The list of courses for 5-ECTS/6-ECTS systems.
CourseEmphasisECTS
Fundamentals    min: 20/24 ECTS
Artificial Intelligence Fundamentals5/6
Computer Science Fundamentals5/6
Digital Hardware Fundamentals5/6
Embedded System Design Fundamentals5/6
Ethics Fundamentals5/6
Research Data Management5/6
Architecture and methodology    min: 15/18 ECTS
Hardware-Software Co-Design5/6
Introduction to HDL and Tools5/6
Development and Integration of HW Accelerators5/6
Reliable Hardware: From Logic Gates to Processors5/6
Hardware Architectures for AI5/6
Implementation    min: 20/18 ECTS
Accelerating CNNs using PL5/6
Electronic Design Automation5/6
Chip Design5/6
Engineering Project5/6
Lab Course Mobile Computer Vision5/6
Deep dives    min: 15/12 ECTS
Ethics Advanced5/6
Lab Course Photogrammetric Data Acquisition5/6
HDL Projects5/6
Neuromorphic Chip Design5/6
Applied Machine Learning for Natural Hazards and Environmental Changes5/6
Free electivesmax: 20/18 ECTS
Master Thesis30 ECTS
4c_id
Methodological Approach in BB-KI Chips.
5 ECTS Schedule
An example schedule for 5-ECTS systems.
6 ECTS Schedule
An example schedule for 6-ECTS systems.
📄 Download Detailed Curriculum (PDF)

Publications

  1. Arango-Carmona, Maria Isabel, Paul Voit, Marcel Hürlimann, Edier Aristizábal, and Oliver Korup. "Hillslope-Torrential Hazard Cascades in Tropical Mountains." EGUsphere 2025 (2025): 1-30. https://doi.org/10.5194/egusphere-2025-1698.
  2. Luo, Xuanshu, and Martin Werner. "One-dimensional Path Convolution." In Forty-second International Conference on Machine Learning.
  3. Sidhaarth, Tarran, Pranay Anandbabu Obla, Nikhil Naganagouda Patil, Zoran Stamenkovic, and S. P. Raja. "Enhanced Miss Forest and Multivariate Time Series Prediction of Wind Speed Using Deep Learning." Journal of Circuits, Systems and Computers 34, no. 12 (2025): 2530006. https://doi.org/10.1142/s0218126625300065.
  4. Gundla, Sri Charan, M. Praveen Karthik, Middi Jashwanth Kumar Reddy, Gourav, Ashutosh Pankaj, Z. Stamenkovic, and S. P. Raja. "A feature extraction approach for the detection of phishing websites using machine learning." Journal of Circuits, Systems and Computers 33, no. 02 (2024): 2450031. https://doi.org/10.1142/s0218126624500312.
  5. Kreowsky, Philipp, Justin Knapheide, and Benno Stabernack. "An Approach Towards Distributed DNN Training on FPGA Clusters." In International Conference on Architecture of Computing Systems, pp. 18-32. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-66146-4_2.
  6. Luna, Lisa Victoria, Maria Isabel Arango-Carmona, Georg Veh, Elizabeth Lewis, Ugur Ozturk, and Oliver Korup. "Urban landslides triggered under similar rainfall intensities in cities globally." Authorea Preprints (2024). https://doi.org/10.22541/essoar.172745685.54713106/v1.
  7. Mariammal, G., A. Suruliandi, Z. Stamenkovic, and S. P. Raja. "A Novel Ensemble Machine Learning Algorithm for Predicting the Suitable Crop to Cultivate Based on Soil and Environment Characteristics Un nouvel algorithme d’apprentissage automatique d’ensemble pour Prédire la culture appropriée à cultiver en fonction des Caractéristiques du sol et de l’environnement." IEEE Canadian Journal of Electrical and Computer Engineering (2024). https://doi.org/10.1109/icjece.2024.3400048.
  8. Nikhil, Uppugunduri Vijay, Athiya M. Pandiyan, S. P. Raja, and Zoran Stamenkovic. "Machine learning-based crop yield prediction in south india: performance analysis of various models." Computers 13, no. 6 (2024): 137. https://doi.org/10.3390/computers13060137.
  9. Vijay Nikhil, U., Z. Stamenkovic, and S. P. Raja. "A study of elliptic curve cryptography and its applications." International Journal of Image and Graphics (2024): 2550062. https://doi.org/10.1142/s0219467825500627.
  10. Zhao, Dedong, Oliver Schrape, Zoran Stamenkovic, and Milos Krstic. "ImSTDP: Implicit Timing On-Chip STDP Learning." IEEE Transactions on Circuits and Systems I: Regular Papers (2024). https://doi.org/10.1109/tcsi.2024.3450958.
  11. Carmona, Maria Isabel Arango, Cassiano Bastos Moroz, Joaquin Vicente Ferrer, Luke Oberhagemann, Guilherme Samprogna Mohor, Amalie Skålevåg, Nazaré Suziane Soares, Andreas Trojand, Fiorella Vega Jacome, and Annegret Thieken. "XXV SIMPÓSIO BRASILEIRO DE RECURSOS HIDRÍCOS."
  12. Knapheide, Justin, Philipp Kreowsky, and Benno Stabernack. "Demonstrating nada: A workflow for distributed cnn training on fpga clusters." In 2023 33rd International Conference on Field-Programmable Logic and Applications (FPL), pp. 363-363. IEEE, 2023. https://doi.org/10.1109/fpl60245.2023.00068.
  13. Kreowsky, Philipp, Justin Knapheide, and Benno Stabernack. "Challenges using fpga clusters for distributed cnn training." In 2023 33rd International Conference on Field-Programmable Logic and Applications (FPL), pp. 347-348. IEEE, 2023. https://doi.org/10.1109/fpl60245.2023.00060.
  14. Poudel, Utsav, Aayush Man Regmi, Zoran Stamenkovic, and S. P. Raja. "Applicability of ocr engines for text recognition in vehicle number plates, receipts and handwriting." Journal of Circuits, Systems and Computers 32, no. 18 (2023): 2350321. https://doi.org/10.1142/s0218126623503218.
  15. Sudhir, A., L. E. Joseph, N. Ahmad, S. Awasthi, V. Agarwal, S.P. Raja, and Z. Stamenkovic. “A Machine Learning Approach to Spam Detection in Social Media Feeds.” 2023 IEEE 33rd International Conference on Microelectronics (MIEL), October 16, 2023, 1–6. https://doi.org/10.1109/miel58498.2023.10315788.
  16. Xiong, Zhouyi, Dirk Stober, Miloš Krstić, Oliver Korup, Maria Isabel Arango, H. Li, and M. Werner. "Integrating AI Hardware in Academic Teaching: Experiences and Scope from Brandenburg and Bavaria." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 10 (2023): 75-81. https://doi.org/10.5194/isprs-annals-x-5-w1-2023-75-2023.
  17. Raja, S. áP, Barbara Sawicka, Zoran Stamenkovic, and G. Mariammal. "Crop prediction based on characteristics of the agricultural environment using various feature selection techniques and classifiers." IEEe Access 10 (2022): 23625-23641. https://doi.org/10.1109/access.2022.3154350.

Demonstrations

HARASS Demonstrator Chip

The AI Demonstrator Chip HARASS (Florian & Erik)

HARASS Chip Layout

The AI Demonstrator Chip HARASS (Layout View)

FPGA-Accelerated Bird Detector at Airport Oberpfaffenhofen for Bird Strike Prevention

FPGA-Accelerated Bird Detector at Airport Oberpfaffenhofen for Bird Strike Prevention

Aerial Building Detection Result

Aerial-View Building Detection on FPGAs

FPGA-Accelerated Bird Detector at Airport Oberpfaffenhofen for Bird Strike Prevention

Real-Time Sign Language Recognition on FPGAs

Point Cloud Classification on FPGAs using LiDAR Cameras

SLAM Demonstration at AI.BAY 2023

Events

MCML-Exhibition 2024 (SLAM)

MCML-Exhibition 2024 (SLAM)

Potsdam Science Day 2023

Potsdam Science Day 2024

Potsdam Science Day 2024

Potsdam Science Day 2024

BB-KI Summerschool 2022 at UP and IHP

BB-KI Summerschool 2022 at UP and IHP

BB-KI Summerschool 2022 at UP and IHP

BB-KI Summerschool 2023 at Heilbronn

BB-KI Summerschool 2023 at Heilbronn

BB-KI Summerschool 2024 at IHP

State Teaching Award 2024

State Teaching Award 2024

Lab Course Mobile Computer Vision

Lab Course Mobile Computer Vision