Grants for access to the Gefion AI Supercomputer
The Novo Nordisk Foundation has granted 37 vouchers to use Gefion the AI Supercomputer for research projects. The recipients are affiliated to six Danish universities and four hospitals. The funded projects span a wide range of fields, including medical science (e.g. image analysis, vaccine development, women’s health), DNA sequencing and protein engineering, quantum simulation and sustainability, ecology, and material science.
Project: Large-scale distributed simulation of quantum algorithms for quantum time evolution
Marek Miller – Postdoc, Department of Mathematical Sciences, Københavns Universitet
Project: Inference of Transcriptional Networks governing Storage Compound Deposition in Legume Seeds using Deep Learning
Guillaume Ramstein – Assistant Professor, Center for Quantitative Genetics and Genomics, Aarhus Universitet
Project: DNA Sequence Models for Inferring Stem Cell Gene Regulatory Landscapes
Ana Cvejic – Professor, Biotech Research and Innovation Center, Københavns Universitet
Project: Self-Supervised Foundation Models for Image Data in Three Dimensions
Anders Dahl – Professor, Department of Applied Mathematics and Computer Science, Danmarks Tekniske Universitet
Project: Danish Foundation Models for Precision Medicine
Mads Nielsen – Professor, Department of Computer Science, Københavns Universitet
Project: Predicting immunological age from single-cell data
Nicolai Birkbak – Professor, Department of Clinical Medicine, Aarhus Universitet
Project: Large-Scale Structural Modeling of Adaptive Immune Specificity Guided by immunological domain-specific restraints
Morten Nielsen – Professor, Department of Health Technology, Danmarks Tekniske Universitet
Project: Simulation of Large-Scale Quantum Photonic Neural Networks – LaSQuP
Mikkel Heuck, Senior Researcher, Department of Electrical and Photonics Engineering, Danmarks Tekniske Universitet
Project: All-atom Transformer – Chemistry Foundational Model
Mikkel Schmidt, Associate Professor, Department of Applied Mathematics and Computer Science, Danmarks Tekniske Universitet
Project: Large scale atomistic simulation of sustainable energy materials using machine learning force fields
Tejs Vegge – Professor, Department of Energy Conversion and Storage, Danmarks Tekniske Universitet
Project: General Pretrained EEG Model
Lars Kai Hansen – Professor, Department of Applied Mathematics and Computer Science, Danmarks Tekniske Universitet
Project: Deep Learning for Enhanced Adenomyosis Diagnosis and Beyond: A Novel Framework for 3D Ultrasound Uterus Analysis
David Westergaard – Senior Researcher, Department of Gynecology and Obstetrics, Hvidovre Hospital
Project: Uncovering the Material Origins of Noise in Oxides for Quantum Devices via AI-Enhanced Computational Quantum Chemistry
Mark Kamper Svendsen – Assistant Professor, Novo Nordisk Foundation Quantum Computing Programme, Niels Bohr Institute, Københavns Universitet
Project: Extending 2 atmospheric models with GPU usage within a NNF funded RECRUIT project on airborne pollen and spores
Carsten Ambelas Skjøth – Professor, Department of Environmental Science, Aarhus Universitet
Project: Preference-Guided Design of Protein Binders Using Direct Optimization and Structured Generative Models
Timothy Jenkins, Associate Professor, Department of Biotechnology and Biomedicine
Project: Bidirectional Representation Learning from Generative Protein Models
Ratish Surenan Puduppully – Assistant Professor, Department of Computer Science, IT Universitetet i København
Project: Pushing the Limits of Neural Network Quantum States with Self-Attention for Strongly Correlated Molecules
Nina Glaser – Assistant Professor, Novo Nordisk Foundation Quantum Computing Programme, Department of Chemistry & Niels Bohr Institute, Københavns Universitet
Project: An Open-Source DNA Language Model for Full-Dimension PacBio HiFi Sequencing Data
Mikkel Heide Schierup – Professor, Bioinformatics Research Centre, Department of Molecular Biology and Genetics, Aarhus Universitet
Project: AI-accelerated whole genome sequencing analysis on real patient data
Elsebet Oestergaard – Professor, Department of Clinical Genetics, Rigshospitalet
Project: Scaling Protein Language Model Knowledge Distillation: Resource-Efficient Protein Engineering and Design
Carlos Acevedo-Rocha – Senior Researcher, Novo Nordisk Foundation Center for Biosustainability, Danmarks Tekniske Universitet
Project: Jointly modelling protein structure and dynamics with generative deep learning
Ole Winther – Professor, Department of Biology, Københavns Universitet
Project: Multi-modal Generative AI models for the single cell, cancer genomics, and liquid biopsy settings
Jakob Skou Pedersen – Professor, Department of Clinical Medicine, Aarhus Universitet
Project: Deep Learning-based analysis of longitudinal electronic health records from hypothyroidism patients
Tugce Karaderi – Associate Professor, Center for Health Data Science, Department of Public Health, Københavns Universitet
Project: Artificial intelligence for precision diagnostics of hematologic cancers
Anders Møller Greve – Department of Clinical Biochemistry, Rigshospitalet
Project: REACT-Q: Quantum boson-sampling enhanced deep learning for cardiovascular and atherosclerosis screening
Henning Bundgaard – Professor, Department of Cardiology, Rigshospitalet
Project: Interpreting Single-Cell Transcriptomics in Infectious Disease Immunology by Context-Aware AI Agents
Tu Hu – Senior Researcher, Department of Infectious Disease Immunology, Statens Serum Institut
Project: NPlastick: Engineering bacterial pili to remove plastic nanoparticles from water
Himanshu Khandelia – Associate Professor, Department of Physics Chemistry and Pharmacy, Syddansk Universitet Odense
Project: Semantic Guidance for Monocular Depth Estimation
Theodora Kontogianni – Assistant Professor, Department of Applied Mathematics and Computer Science, DTU Compute
Project: Artificial intelligence based approaches to develop novel synthetic lethality iven treatment strategies in cancer
Zoltan Szallasi – Professor, Department of Translational Cancer Genomics, Kræftens Bekæmpelse
Project: Foundation-scale Bayesian Uncertainty Quantification
Søren Hauberg – Professor, Department of Applied Mathematics and Computer Science, Danmarks Tekniske Universitet
Project: Generative Arctic Sea Ice Forecasting combining Super-Resolution priors and neural Data Assimilation
Maxime Beauchamp – Researcher, Department of National Center for Climate Research, Danmarks Meteorologiske Institut
Project: Artificial Intelligence-driven Approach to Protein Degradation in Brain Synapses
Chao Sun – Associate Professor, Department of Molecular Biology and Genetics, Aarhus Universitet
Project: GPU-Accelerated Clustering of Maternal Medication Patterns and Congenital Heart Disease Risk in a Nationwide Cohort of 1.5 Million Pregnancies
Kasper Karmark Iversen – Professor, Department of Cardiology, Herlev and Gentofte Hospital
Project: Foundation Models for Tree Ecosystems
Ankit Kariryaa – Assistant Professor, Department of Geosciences and Natural Resource Management, Københavns Universitet
Project: Computational discovery and characterization of novel sweet-tasting proteins
Alexander Hauser – Associate Professor, Department of ug Design and Pharmacology, Københavns Universitet
Project: Multimodal genomic foundation model
Wouter Boomsma – Professor, Department of Computer Science, Københavns Universitet
Project: Statistically Robust Sampling of Cyclodextrin Host-Guest Thermodynamics
Casper Steinmann – Associate Professor, Department of Chemistry and Bioscience, Aalborg Universitet