I am a machine learning researcher at RISE Research Institutes of Sweden and a PhD student in federated learning at KTH Royal Institute of Technology. I am part of the RISE AI deep learning group led by Olof Mogren. During the spring of 2023 I visited the NYU Center for Data Science, supervised by Kyunghyun Cho.
My research is focused on representation learning using deep nets in decentralized and federated systems. I’m especially interested in understanding out of distribution generalization. Beyond this, I have an interest in applying ML to solve problems related to sustainability and climate change. I am always open for collaborations in these areas, feel free to reach out. Here is my Google Scholar profile.
If you are a student interested in doing a project or a master thesis I am always open for discussions. Click here for suggestions and previous work I have supervised.
Below follows a list of some industry projects I’ve been part of.
- [2017-2018] Big Automotive Data Analytics: SEnsor Modeling and Performance Analysis. Project partners: Volvo, Zenseact, AFRY, Chalmers University of Technology. GANs, time series, autonomous vehicles, sensor data
- [2019-2020] LOBSTR - Learning On-Board Signals for Timely Reaction.. Project partners: Scania. federated learning, anomaly detection, vehicle control unit
- [2019-2021] Swedish Medical Language Data Lab. Project partners: Region Halland, Peltarion, VGR, AI Sweden, Sahlgrenska University, Folktandvården. federated learning, NLP, medicine
- [2019-2021] AI driven financial risk assessment for circular business models. Project partners: Nordea, SEB. circular economy, computer vision, NLP
- [2020-2023] ANIARA Project partners: Ericsson Research. federated learning, network analysis