Academic Collaborations
We believe that we can achieve more together. In the spirit of open collaboration, we are committed to foster scientific exchange and promote publication.
Open collaboration with academia has been an integral part of our identity for a long time. By collaborating with a number of international universities as well as partners from politics, business, and science, we, together with our partners, work to solve today's most challenging AI problems.
More information below
AutoML Lab - University of Freiburg
The AutoML Lab led by Prof. Frank Hutter is a joint research lab established by the University of Freiburg and Bosch in order to strenghten joint research and information exchange in fundamentals of Machine Learning. The partnership focuses on the development of Bosch-relevant methods to support the application of AutoML-based solutions in Bosch manufacturing.
- Start: December 2018
- Location: Freiburg, Germany
- Business applications: AutoML
- Research topics: Multifidelity Optimization, Neural Architecture Search, Meta-learning, AutoML for classical ML and AutoML for Reinforcement Learning.
Collaboration partner
Prof. Frank Hutter is the Head of the Machine Learning Lab at the University of Freiburg. He is also a consultant at the Bosch Center for AI (BCAI) as Chief Expert for AutoML.
His research focuses on various problems in the fields of AutoML and Deep Learning, including Meta-learning, learning to learn, neural architecture search, efficient hyperparameter optimization, and Bayesian optimization.
TU Wien
Researchers at TU Wien and BCAI researchers work together on declarative problem solving for combinatorial problems, as well as combinations of symbolic and machine learning-driven AI. The partnership aims at joint research and information exchange as well as the transfer of applications in existing projects at Bosch.
- Start: January 2020
- Location: Vienna, Austria
- Business applications: Scheduling and planning in manufacturing
- Research topics: Advanced context-based reasoning for knowledge-enhanced combinatorial problems in Bosch manufacturing
Collaboration partner
Ass. Prof. Dr. Nysret Musliu is the Head of the Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling at the TU Wien.
His research interest include problem solving and search in Artificial Intelligence, exact and heuristic methods, Machine Learning and optimization, constraint satisfaction, automated scheduling and timetabling.
Collaboration partner
Prof. Dr. Thomas Eiter is a Professor of Computer Science at TU Wien, Austria, where he leads the Knowledge-Based Systems Group. He is also the Head of the Institute of Logic and Computation.
In 2020, he was named an ACM Fellow for contributions to knowledge representation and reasoning, logic programming, and declarative problem solving.
Carnegie Mellon University
Researchers of CMU and Bosch work together in order to conduct cutting-edge research in the field of robust Deep Learning. The goal is to provide better understanding and performance complementing the Bosch research portfolio in robust, safe, and explainable AI.
- Start: April 2018
- Location: Pittsburgh, USA
- Business applications: Automated driving, optical inspection, manufacturing
- Research topics: Robust Deep Learning, fundamentals of Deep Learning, Hybrid Modelling
Collaboration partner
Zico Kolter is a an Associate Professor at Carnegie Mellon University, where he leads a research group studying robust machine learning, implicit deep models, and generalization of deep learning. In addition, at Bosch he is Senior Chief Expert in Robust Deep Learning and Scientific Lead for BCAI Research.
Bosch Industry on Campus at University of Tübingen
The collaboration with the University of Tübingen is established via the Bosch Industry-on-Campus (IoC) Lab, which is located in the campus of the University of Tübingen and is a part of the Cyber Valley ecosystem. Within the Bosch IoC Lab, the aim is to create new cooperation projects with the research talent of the University of Tübingen and BCAI at the interface between basic academia research and application-oriented research. This provides an excellent opportunity for both Bosch and the University of Tübingen to break new ground in establishing academia-industrial partnerships and opens up promising prospects for application-inspired research.
Currently, the Bosch IoC Lab targets two research fields of Data-Efficient Deep Learning and Safe Deep Learning, with applications to automated driving and driver assistance systems, robotics, and manufacturing.
- Start: November 2018
- Location: Tübingen, Germany
- Business applications: automated driving, driver assistance systems, robotics, manufacturing
- Research topics: synthetic data generation and augmentation, few-shot learning, generative modeling, out-of-distribution detection, uncertainty estimation, domain adaptation and generalization
SIRIUS Research Center
SIRIUS is a Norwegian center of research excellence and a hub for academic-industrial collaboration with the focus on AI for industrial digitalization and automation. As a SIRIUS member, BCAI strengthens its research and industrial network and participates in mutually beneficial information exchange.
- Start: January 2020
- Location: Oslo, Norway
- Business applications: Factory automation, knowledge analytics
- Research topics: KRR, Semantic Technologies, Digital Twins, Knowledge Graphs, Ontologies
Collaboration partners
University of Oslo, University of Oxford, NTNU, SINTEF, SIMULA
Industrial partners
IBM, SAP, OSIsoft, Aibel, Aker Solutions, Schlumberger, Equinor, etc.
Cyber Valley
Cyber Valley is Europe‘s largest AI consortium including partners from science and industry for research and industrial collaboration in the fundamentals of AI for Automotive, Industry 4.0 and E-commerce. The main goal is to bring together key players from science and industry to advance AI and strengthen the knowledge transfer between collaboration partners.
- Start: January 2018
- Location: Tübingen, Germany
- Business applications: Manufacturing, automated driving, engineering development process
- Research topics: Fundamental research covering all aspects of Machine Learning, Computer Vision and Robotics
Collaboration partners
Max-Planck-Gesellschaft, Uni Tübingen, Uni Stuttgart, Land BW, Fraunhofer
Industrial Partners
Bosch, BMW, Daimler, IAV, Porsche, ZF, Amazon
Tsinghua-Bosch Joint Research Center for ML
The Tsinghua-Bosch Joint Research Center on Machine Learning is a joint lab established by the University of Tsinghua and Bosch in order to strengthen joint research and information exchange in fundamentals of Machine Learning for manufacturing at Bosch.
- Start: March 2020
- Location: Peking, China
- Business applications: Optimization in manufacturing, highly automated driving
- Research topics: Probabilistic Deep Learning, Explainable Machine Learning, Meta-learning, Neuro-Symbolic AI, NLP (Natural Language Processing)
Collaboration partner
Jie Tang is a Professor and the Associate Chair of the Department of Computer Science at Tsinghua University. His interests include Artificial Intelligence, Data mining, social networks, and Machine Learning.
He served as PC Co-Chair and Associate General Chair of different conferences on Big Data and Open J, and was honored with several research awards. He leads the project AMiner.org, an AI-enabled research network analysis system, which has attracted more than 20 million users from 220 countries/regions in the world.
Collaboration partner
Prof. Jun Zhu is the Director of the Tsinghua-Bosch Joint Center on Machine Learning. He is also the Director of the Basic Theory Research Center at Tsinghua Institute for AI.
His research focuses on developing statistical Machine Learning methods to understand complex scientific and engineering data, including Bayesian methods, adversarial Machine Learning, and decision-making under uncertainty.
UvA-Bosch Delta Lab 2 – University of Amsterdam
Since the end of 2016, the University of Amsterdam and the Bosch Center for Artificial Intelligence have been working and researching on deep learning in the jointly established UvA-Bosch Delta Lab. The aim of the research alliance is regular professional exchange and knowledge transfer between science and industry. Beginning 2022, the long-standing cooperation was successfully extended. Delta Lab 2 will focus on research in the area of machine learning for applications in computer vision, generative models and casual learning.
- Start: November 2016, extension in March 2022
- Location: Amsterdam, Netherlands
- Team: Ten PhD students, one postdoc, one lab manager
- Research topics: Artificial intelligence and machine learning for applications in computer vision, generative models and causal learning
- Business applications: Automated driving, computer vision, embedded AI
Collaboration partners
The lab is headed by the UvA’s Dr. Jan-Willem van de Meent and Prof. Theo Gevers. Dr. Eric Nalisnick is the daily lab manager.