Supported projects since January 2022

Understanding the role of alkali-metal ions in perovskite thin films using robotic synthesis and in situ characterization methods

Prof. Dr. Christoph J. Brabec
Friedrich-Alexander-University of Erlangen-Nuremberg
Institute Materials for Electronics and Energy Technology

Dr. Carolin M Sutter-Fella
Lawrence Berkeley National Laboratory
Molecular Foundry

Fusion of InSAR and altimeter satellite data to enhance the monitoring of global glacier mass changes

Prof. Dr. Matthias Braun
Friedrich-Alexander-University of Erlangen-Nuremberg
Institute of Geography

Dr. Alex Gardner
Sea level and Ice Group

Learning to See the Physical World

Prof. Dr. Bernhard Egger
Friedrich-Alexander-University of Erlangen-Nuremberg
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)

Prof. Jiajun Wu
Stanford University
Computer Science Department

Therapeutically targeting AKAP6 in heart and bone disease

Prof. Dr. Felix B. Engel
Friedrich-Alexander-University of Erlangen-Nuremberg
Nephropathology

Prof. Michael S. Kapiloff
Stanford University
Ophthalmology

Personalized Artificial Intelligence Methods for Heterogeneous Sequential Data.

Prof. Dr. Björn Eskofier
Friedrich-Alexander-University of Erlangen-Nuremberg
Machine Learning and Data Analytics Lab

Prof. Stephan Mandt
University of California, Irvine
Bren School of Information and Computer Science

Cosmological Insights from Artificial Intelligence

Prof. Dr. Daniel Grün
Ludwig-Maximilians-University of Munich
Institut für Astronomie und Astrophysik, Universitäts-Sternwarte München

Prof. Aaron Roodmann
Stanford University
SLAC National Accelerator Laboratory

Thin and flexible sulfide based electrolyte layers with integrated polymer binder for high energy all-solid-state lithium metal batteries

Prof. Dr.-Ing. Kai-Olaf Hinrichsen
Technische Universität München
Chair of Chemical Technology

Prof. Ping Liu
University of California, San Diego
Department of Nanoengineering

New materials with kagome-structures as candidates for entangled quantum states

Prof. Dr. Dirk Johrendt
Ludwig-Maximilians-University of Munich
Faculty for chemistry and pharmacy

Prof. Ram Seshadri
University of California, Santa Barbara
Materials Research Laboratory

DeepCast: Time-Series Forecasting and Classification using interpretable and scalable Deep Learning Methods

Prof. Dr. Wolfgang Kellerer
Technische Universität München
Chair of Communication Network

Prof. Ram Rajagopal
Stanford University
Department of Civil and Environmental Engineering

Data rights for the users of artificial intelligence

Prof. Dr. Jan Krämer
University of Passau
School of Business, Economics and Information Systems

Dr. Georgios Petropoulous
Stanford University
Stanford Institute for Human-Artificial Intelligence

Microbial control of soil carbon cycling under climate change: nano-scale imaging and machine-learning analysis of spatial patterns of microbe-mineral-organic matter interactions

Prof. Dr. Dr. h.c. Ingrid Kögel-Knabner
Technische Universität München
Chair of Soil Science

Dr. Noah Sokol
Lawrence Livermore National Laboratory (LLNL)
Physical & Life Sciences Directorate

Artificial intelligence and machine learning for image analysis of internet enabled miniaturised ophthalmic hand-held instruments

Dr. Franz Irlinger
Technische Universität München
Institute for Micro Technology and Medical Device Technology

Prof. Dr. Tim Lüth
Technische Universität München
Institute for Micro Technology and Medical Device Technology

Dr. Gerrit R. J. Melles
University of California, San Diego
Center for Memory and Recording Research

Prof. Frank Talke
University of California, San Diego
Center for Memory and Recording Research

Machine learning-based optimization for personalized brain stimulation therapy

Prof. Dr. med. Frank Padberg
Ludwig-Maximilians-University of Munich
Department of Psychiatry and Psychotherapy

Ph.D. Martin Tik
Stanford University
Brain Stimulation Lab

Supramolecular Trapping of Reactive Nuclear Waste Components

PD Dr. Alexander Pöthig
Technische Universität München
Chemistry & CRC

Prof. Polly L. Arnold
University of California, Berkeley
NChemistry & LBNL

Patient-specific visualization of (vascular) anatomy in mixed reality for interventional and surgical planning

Prof. Dr. Michael Scholz
Friedrich-Alexander-University of Erlangen-Nuremberg
Institute of Functional and Clinical Anatomy

Prof. Dr. Bruce Daniel
Stanford University
Department of Radiology, Mixed reality Incubator

Prediction of the risk and disease progression of Parkinson disease using patient-derived neurons by application of artificial intelligence-based machine learning

PD Dr. Wei Xiang
Friedrich-Alexander-University of Erlangen-Nuremberg
Department of Molecular Neurology

Dr. Johannes Schlachetzki
University of California, San Diego
Department of Cellular und Molecular Medicine