Current SNIC AI/ML Projects

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

Mathematics (3)
Computer and Information Sciences (18)
Physical Sciences (1)
Earth and Related Environmental Sciences (1)
Biological Sciences (2)
Other Natural Sciences (1)
Electrical Engineering, Electronic Engineering, Information Engineering (2)
Mechanical Engineering (1)
Medical Engineering (1)
Health Sciences (1)
Medical Biotechnology (1)

Mathematics (3)

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 (18)

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
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
Efficient communication with Deep reinforcement learning: Emil Carlsson, Chalmers tekniska högskola
2020-09-04 – 2021-09-01
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
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
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 (1)

Machine learning for topological codes and topological matter: Mats Granath, Göteborgs universitet
2020-08-28 – 2021-09-01

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 (1)

Data-driven modelling of short fibre composites: Martin Fagerström, Chalmers tekniska högskola
2020-11-26 – 2021-12-01

Medical Engineering (1)

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