People
We at the Deep Learning Research Group at RISE are a team of researchers who work on foundational problems within machine learning, and apply our expertise on problems related to climate change and ecology.
Olof Mogren, PhD
Defended his PhD in computer science at Chalmers University of Technology in 2018 with the thesis Representation Learning for Natural Language. Senior researcher, head of the DL group, and responsible for deep learning research at RISE Research Institutes of Sweden.
Olof develops and investigates machine learning based solutions to problems related to the environment and climate change. This includes stream flow forecasting, soundscape analysis for biodiversity monitoring, and AI for circular business models.
Aleksis Pirinen, PhD
Defended his PhD in computer vision at Lund University in 2021 with the thesis Reinforcement Learning for Active Visual Perception. Senior researcher at RISE Research Institutes of Sweden.
Aleksis’ main research interest is to develop machine learning methods for a broad range of environmental applications (e.g. climate adaptation and humanitarian aid causes).
Maria Bånkestad, MSc
Defended her MSc in enigneering physics from Royal Institute of Technology in 2012. Researcher and PhD candidate at RISE Research Institutes of Sweden. Also afiliated with Uppsala University.
John Martinsson, MSc
Defended his MSc in computer science at Chalmers University of Technology in 2017. Researcher and PhD candidate at RISE Research Institutes of Sweden. Also afiliated with Lund University.
Edvin Listo Zec, MSc
Defended his MSc in engineering mathematics at Chalmers University of Technology in 2017. Researcher and PhD candidate at RISE Research Institutes of Sweden. Also afiliated with Royal Institute of Technology.
Martin Willbo, MSc
Defended his MSc in computer science at Chalmers University of Technology in 2021. Researcher at RISE Research Institutes of Sweden.
Previous members of the lab
- Ebba Ekblom, MSc
- David Vikstrand did an internship at the DL group during the spring of 2024
Master’s Students
The following master’s students have written their master’s theses in the DL group.
- Emma Amnemyr and Daniel Björklund: Active Learning and Annotation Efficiency for Object Detection in Coffee Farming (Lund University)
- Oscar Marklund and Richard Lindholm: Active Learning for Sound Analysis (Lund University)
- Agnes Ericsson and Malte Åhman: Privileged Information for Earth Observation (Lund University)
- Tom Hagander and Eric Ihre-Thomason: Distributed Machine Learning (Lund University)
- Axel Eiman, Nils Eickhoff: Weakly semi-supervised object detection for annotation efficiency: Leveraging a mix of strong bounding box labels and weak point labels for detecting coffee berry disease (Chalmers University of Technology 2023)
- Ennio Rampello: High-altitude navigation to improve the performance of AiRLoc: An RL model for drone navigation (KTH Royal Institute of Technology 2023)
- Vishal Nedungadi: Active street to aerial view geo-localization (KTH Royal Institute of Technology 2023)
- Anton Samuelsson, John Backsund: Aerial View Goal Localization with Reinforcement Learning (Lund University 2022)
- Edvin Lam: Graph neural networks for physics simulations (Chalmers University of Technology 2021)
- Victor Risne, Adele Siitova: Text sumarization using transfer learning (Chalmers University of Technology 2019)
- Soumyadeep Mondal, Vishnu Raveendra Nadhan: Question Answering In Conversational Context (Chalmers University of Technology 2019)
- Marie Korneliusson: Deep Learning for Fashion Analysis (Chalmers University of Technology 2019)
- Christian Meijner, Simon Persson: Blood Glucose Prediction for Type 1 Diabetes using Machine Learning(Chalmers University of Technology 2017)
- Johan Ekdahl and William Axhav Bratt: Development of an intelligent personal assistant (Chalmers University of Technology 2016)
- Jacob Hagstedt P Suorra: Automatic discussion forum assistant using recurrent neural networks (Chalmers University of Technology 2016)
- Sean Pavlov and Simon Almgren: Entity recognition in swedish medical documents (Chalmers University of Technology 2016)
- Hampus Bengtsson and Johannes Jansson: Using Classification Algorithms for Smart Suggestions in Accounting Systems (Chalmers University of Technology 2015)
- Yanling Jin and Albin Bramstång: Constructing a Context-aware Recommender System with Web Sessions (Chalmers University of Technology 2015)