SNIC SUPR
Current SNIC AI/ML Projects

This page lists current SNIC AI/ML projects. Use the left-side menu to view other types.

Research Areas

The area is based on the three-digit level (forskningsämnesgrupp) from Standard för svensk indelning av forskningsämnen applied to the primary classification.

Mathematics (4)

AI For Science Bootcamp – NVIDIA/ENCCS

Kjartan Thor Wikfeldt, Uppsala universitet
2021-02-20 – 2021-04-01

Microstructures and mass transport - a machine learning approach

Magnus Röding, Chalmers tekniska högskola
2020-10-02 – 2021-11-01

Probabilistic Word Embeddings using Tensorflow

Måns Magnusson, Uppsala universitet
2020-11-09 – 2021-07-01

Scalable optimization for machine-learning

Mikael Johansson, Kungliga Tekniska högskolan
2020-10-27 – 2021-11-01

Computer and Information Sciences (26)

(e)PREDICT: (electrified) PREDIctive Consolidated Transportation

Gyözö Gidofalvi, Kungliga Tekniska högskolan
2021-02-19 – 2022-03-01

AI for improved decision making in healthcare

Fredrik Johansson, Chalmers tekniska högskola
2020-09-01 – 2021-09-01

BioIntegration: Biomedical data integration with AI

Benjamin Ulfenborg, Högskolan i Skövde
2020-09-24 – 2021-10-01

Computational Experiments for Automatic Program Repair, Projet SELFHEALING, Prof Monperrus

Martin Monperrus, Kungliga Tekniska högskolan
2020-12-14 – 2022-01-01

Contextualised word embeddings for current and historical Swedish

Simon Hengchen, Göteborgs universitet
2021-03-04 – 2022-04-01

Deep Learning for Robot Vision

Michael Felsberg, Linköpings universitet
2020-09-04 – 2021-10-01

Deep learning models for modelling genetic variation

Carl Nettelblad, Uppsala universitet
2020-09-04 – 2021-09-01

Detecting Bias in Audio-Visual Spoken Interaction

Giampiero Salvi, Kungliga Tekniska högskolan
2021-02-01 – 2022-02-01

Efficient communication with Deep reinforcement learning

Emil Carlsson, Chalmers tekniska högskola
2020-09-04 – 2021-09-01

Evaluation of Convolutional and Graph Neural Networks for Digital Pathology on High Performance GPUs

Karl Meinke, Kungliga Tekniska högskolan
2020-12-22 – 2022-01-01

Federated Learning for NLP

Addi Ait-Mlouk, Uppsala universitet
2021-03-10 – 2022-04-01

Generative models for reinforcement learning

Emilio Jorge, Chalmers tekniska högskola
2020-09-04 – 2021-09-01

Geometry of Linear Regions for Deep ReLU Networks

Mårten Björkman, Kungliga Tekniska högskolan
2020-10-29 – 2021-11-01

HASTE: Hierarchical Analysis of Spatial and Temporal Data

Ankit Gupta, Uppsala universitet
2020-12-11 – 2021-12-01

ML for Alzheimer

Lena Stempfle, Chalmers tekniska högskola
2020-09-15 – 2021-10-01

Machine Learning for Causal Inference

Anton Matsson, Chalmers tekniska högskola
2020-09-25 – 2021-04-01

Machine learning for improved decision making

Newton Mwai Kinyanjui, Chalmers tekniska högskola
2020-09-04 – 2021-09-01

Natural Language Processing Research (year 1)

Lovisa Hagström, Chalmers tekniska högskola
2020-10-27 – 2021-11-01

Privacy-preserving learning for vehicle networks: applications and tools

Shiliang Zhang, Chalmers tekniska högskola
2020-09-30 – 2021-10-01

Proof of concept: Generative models of categorical data for rare disease classification.

Simon Olsson, Chalmers tekniska högskola
2021-02-01 – 2021-10-01

Real-time end-to-end Federated Learning

Hongyi Zhang, Chalmers tekniska högskola
2020-09-01 – 2021-09-01

Research in Natural Language Processing

Tobias Norlund, Chalmers tekniska högskola
2020-11-26 – 2021-12-01

Robust Loss Functions for Learning with Noisy Labels

Erik Englesson, Kungliga Tekniska högskolan
2020-11-09 – 2021-06-01

Structured multilinguality for natural language processing

Robert Östling, Stockholms universitet
2020-09-30 – 2021-10-01

Transferable concepts

Adam Breitholtz, Chalmers tekniska högskola
2020-09-01 – 2021-09-01

ml@e2-sp-cv

Lars Hammarstrand, Chalmers tekniska högskola
2020-11-09 – 2021-06-01

Physical Sciences (3)

AI for Single Particle Catalysis

Henrik Klein Moberg, Chalmers tekniska högskola
2021-03-04 – 2022-04-01

Machine Learning for Nanophotonics

Philippe Tassin, Chalmers tekniska högskola
2021-03-04 – 2022-04-01

Machine learning for topological codes and topological matter

Mats Granath, Göteborgs universitet
2020-08-28 – 2021-09-01

Chemical Sciences (2)

GPU to develop FFs by GAs, simulate electrolytes and do ML on battery electrodes.

Patrik Johansson, Chalmers tekniska högskola
2020-12-09 – 2022-01-01

Modelling inorganic crystalline electrolytes with atomistic machine learning

Chao Zhang, Uppsala universitet
2020-12-15 – 2021-07-01

Earth and Related Environmental Sciences (1)

AI for Wildfire Using Optical and Radar Time Series

Puzhao Zhang, Kungliga Tekniska högskolan
2020-11-04 – 2021-11-01

Biological Sciences (2)

A system for automated analysis of subsea movies using citizen science and machine learning

Matthias Obst, Göteborgs universitet
2020-12-20 – 2022-01-01

Determining protein backbone structures and sequences from occupied volumes using a Transformer

Jasmine Gardner, Uppsala universitet
2020-09-30 – 2021-10-01

Other Natural Sciences (1)

Gauge Equivariant Convolutional Neural Networks

Daniel Persson, Chalmers tekniska högskola
2020-10-27 – 2021-11-01

Electrical Engineering, Electronic Engineering, Information Engineering (2)

Deep learning for rigorous SW testing and verification

Dhasarathy Parthasarathy, Chalmers tekniska högskola
2020-08-27 – 2021-09-01

Motions and voice

Andreas Jakobsson, Lunds universitet
2020-09-18 – 2021-10-01

Mechanical Engineering (2)

Data-driven modelling of short fibre composites

Martin Fagerström, Chalmers tekniska högskola
2020-11-26 – 2021-12-01

Physics-informed neural networks for turbulence simulations

Philipp Schlatter, Kungliga Tekniska högskolan
2020-12-30 – 2022-01-01

Medical Engineering (2)

Implementation of innovative image analysis tools in the radiological workflow

Rolf A Heckemann, Göteborgs universitet
2020-12-17 – 2022-01-01

In Silico Traction Force Microscopy

Nicolas Pielawski, Uppsala universitet
2020-11-09 – 2021-12-01

Health Sciences (1)

Deep learning, Machine learning, and Bayesian computational in epidemiology

Rani Basna, Göteborgs universitet
2020-09-22 – 2021-10-01

Medical Biotechnology (1)

Deep Autoencoder Neural Network for identification of Doxorubicin-induced gene expression profile in stem cell-based cardiomyocytes

Dario Melguizo Sanchis, Högskolan i Skövde
2020-09-14 – 2021-10-01

Veterinary Science (1)

Karakterisering av andningsmissljud

Magnus Karlsteen, Chalmers tekniska högskola
2021-02-17 – 2021-07-01

Political Science (1)

Methods for the analysis of spreading phenomena in networks, with a focus on the online spreading of political ideas through visual content

Matteo Magnani, Uppsala universitet
2020-12-28 – 2022-01-01