AIP Network Lab

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Trilateral AI Research
Research projects in the field of Artificial Intelligence coordinated by Japan, Germany and France

JST has decided to start the new projects coordinated by JST, German Research Foundation (DFG, Germany) and The French National Research Agency (ANR, France). Based on agreements, JST, DFG and ANR proceed research projects among the three countries in the field of Artificial Intelligence. The research period is scheduled from FY2020 to FY2023.

Research Projects

AI for Aging societies: From Basic Concepts to Practical Tools for AI-Facilitated Cognitive Training (AI-Cog)

Japanese PI Mihoko Otake Center for Advanced Intelligence Project, RIKEN
German PI Tonio Ball Department of Neurosurgery, University of Freiburg
French PI Alexandre Gramfort INRIA Saclay Ile de France Research Centre

Affiliation when selected.

Description

This collaborative research aims to optimize the decodable information about the functional state of the brain, to identify biomarkers that indicate the risk for cognitive impairments and different forms of dementia, and use these improved methods to guide AI facilitated cognitive training. We will develop novel, dedicated machine learning (ML) methods and adapt them to human brain signals, will make our methods in an open source software, focusing on unsupervised learning, data augmentation, domain adaptation, and interpretable machine unsupervised learning, data augmentation, domain adaptation, and interpretable machine learning models.

Artificial Intelligence for Human-Robot Interaction (AI4HRI)

Japanese PI Takayuki Kanda Graduate School of Informatics, Kyoto University
German PI Michael Beetz Institute of Artificial Intelligence, Bremen University
French PI Aurélie Clodic LAAS, CNRS

Affiliation when selected.

Description

Europe and Japan both face problems of shrinking and aging population, and using social robots is seen as a possible way of alleviating demographic issues. Robots need to be able to interact with people and this is studied in the field of Human-Robot Interaction (HRI). But dealing with humans is difficult, and HRI is still not making enough use of AI technologies. The goal of the AI4HRI project will be to both develop and integrate several AI methods which will allow social robots to appropriately deal with humans around them. This includes 3 abilities that we believe are currently missing in HRI: knowledge management and reasoning, learning of social skills, and planning and executing joint human-robot actions. Each partner in the project is a leading expert in one of these fields and the project will benefit from their synergy. Importantly, the above abilities will be combined into a single open-source architecture and shared with other researchers.

Learning Cyclotron (LeCycl)

Japanese PI Koichi Kise Graduate School of Engineering, Osaka Prefecture University
German PI Andreas Dengel German Research Center for Artificial Intelligence
French PI Laurence Devillers Sorbonne University / LIMSI, CNRS

Affiliation when selected.

Description

This collaborative research is about "Learning Augmentation". Its goal is to propose and exprimentally validate a new model called "Learning Cyclotron", which covers not only the self-learning with advance sensing technologies but also nudging knowledge transfer between learners to make the model disruptively innovative.

Research on Real Time Compliance Mechanism for AI (RECOMP)

Japanese PI Ken Satoh Principles of Informatics Research Division, National Institute of Informatics
German PI Adrian Paschke The Institute of Applied Informatics
French PI Jean-Gabriel Ganascia LIP6, Sorbonne University

Affiliation when selected.

Description

This collaborative research aims to enhance reliability of AI in society to realize real time compliance mechanism such as legal and ethical norms using logic programming technology.

Enhanced Data Stream Analysis: combining the signature method and machine learning algorithms (EDDA)

Japanese PI Nozomi Sugiura Global Ocean Observation Research Center, Japan Agency for Marine-Earth Science and Technology
German PI Joscha Diehl Institute for mathematics and computer science, University of Greifswald
French PI Marianne Clausel Institut Élie Cartan de Lorraine, University of Lorraine

Affiliation when selected.

Description

By introducing the concept of iterated integrals (signature) in rough path theory to machine learning algorithms, this project aims to develop a highly interpretable framework of time-series analysis that can deal with nonlinear effect properly and to find a new direction of applications to environmental sciences. Because the new framework of statistical analysis is based on rough path theory and machine learning, it is indispensable for the development to gather the experts in rough path theory from German and French side, the experts in machine learning from French side, and the experts in applied data analysis from Japanese side.

Adaptive Artificial Intelligence for Human Computer Interaction (PANORAMA)

Japanese PI Yukiko Nakano Department of Computer and Information Science, Seikei University
German PI Elisabeth André Faculty of Applied Informatics, University of Augsburg
French PI Jean-Claude Martin LIMSI, CNRS / Université Paris Saclay

Affiliation when selected.

Description

This collaborative research aims at proposing a new research methodology for Machine-Learning-based Human-Computer Interaction by focusing on the concept of user adaptivity.

Understanding and Creating Dynamic 3D Worlds towards Safer AI (TOSAI)

Japanese PI Ko Nishino Graduate School of Informatics, Kyoto University
German PI Carsten Rother IWR, University Heidelberg
French PI David Picard IMAGINE, Ecole des Ponts ParisTech

Affiliation when selected.

Description

This collaborative research aims to enable the generation of photorealistic, critical and rare scenes of dynamic environments. To achieve this, the technical goal is to push the state-of-the-art for rich 3D representations, including appearance, geometry, and dynamics, as well as semantic aspects.

AI empowered general purpose assistive robotic system for dexterous object manipulation through embodied teleoperation and shared control (CHIRON)

Japanese PI Yasuhisa Hasegawa Graduate School of Engineering, Nagoya University
German PI Jan Reinhard Peters Computer Science Department, Technical University of Darmstadt
French PI Liming Chen Department of Mathematics and Informatics, Ecole Centrale de Lyon

Affiliation when selected.

Description

This collaborative research investigates challenges in tele-operation of robots such as delay and lack of feedback sensation through combination of embodiment and smart AI. The research will enable elderly and patients to operate robots intuitively and would lead to reconstruct social welfare system to improve their independent life.

Knowledge-enhanced information extraction across languages for pharmacovigilance (KEEPHA)

Japanese PI Yuji Matsumoto Center for Advanced Intelligence Project, RIKEN
German PI Sebastian Möller German Research Center for Artificial Intelligence
French PI Pierre Zweigenbaum LIMSI, CNRS

Affiliation when selected.

Description

This collaborative research aims to develop Artificial Intelligence methods that digest scientific knowledge from various text sources in multiple languages, and integrate them into knowledge bases. Adverse Drug Reactions are taken up as an application for extracting relations between drug and medical problems.