Jaakko Suutala, D.Sc. (Tech.) Associate Professor of Artificial Intelligence Biomimetics and Intelligent Systems Group Faculty of Information Technology and Electrical Engineering University of Oulu, Finland Email: firstname.lastname@oulu.fi My official research profile AI @ University of Oulu Google scholar LinkedIn X (Twitter) Sigmoid Social (Mastodon)

 

Biography

I am an Associate Professor (tenure track) of Artificial Intelligence in the Biomimetics and Intelligent Systems Group at the Faculty of Information Technology and Electrical Engineering, University of Oulu, co-leading the DataAI Group. I received M.Sc. degree in information engineering and D.Sc. (Tech.) degree in machine learning (embedded systems and software) from the University of Oulu in 2004 and 2012, respectively. Furthermore, I have co-founded Nelilab and IndoorAtlas Ltd., where the latter is an indoor positioning spin-off company from University of Oulu. I worked there as a chief data scientist 2012-2019 and currently as a technical advisor.

Research

My research interests and experties mainly lie at the intersection between machine learning, probabilistic modelling, and signal processing applied to autonomous and interacting artificial intelligent systems and data science. More specifically, I am interested in Bayesian inference, Gaussian processes, deep neural networks, spatiotemporal models, sensor fusion, multimodal learning, reinforcement learning, and uncertainty quantification, especially in small and limited data scenarios. In the application side, our group is interested in AI and machine learning for Earth observation and remote sensing, healthcare, green energy systems, smart control, robotics, distributed AI and 6G systems, and adversarial ML.

Team

Postdocs

Dr. Henna Tiensuu

Doctoral candidates

Miika Malin
Rajesh Raveendar (with Prof. Juha Röning)

Jarkko Kemppainen (Symbio Oy)

MSc. students

Samuli Paloniemi
Justin Seby

Former team members

Dr. Tuomo Alasalmi (now data scientist at Finnish Tax Administration)

Teaching

Autumn 2024:
Multi-Modal Data Fusion, 521161S

Spring 2025:
Artificial Intelligence, 521495A

Publications

Most recent publications:

Suutala, J., Malin, M., Tiensuu, H., Tamminen, S. (2023): Road conditions analysis and forecasting in Arctic: multi-source machine learning approach , XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023). https://doi.org/10.57757/IUGG23-2849

Malin, M., Okkonen, J., Suutala, J. (2023): Snow water equivalent forecasting in Sub-Arctic and Arctic regions with recurrent neural networks , XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023). https://doi.org/10.57757/IUGG23-2856

Lauri Tuovinen, Jaakko Suutala (2021). Ontology-based Framework for Integration of Time Series Data: Application in Predictive Analytics on Data Center Monitoring Metrics. 13th International Conference on Knowledge Engineering and Ontology Development. pdf

C. De Lima et al. (2021). Convergent Communication, Sensing and Localization in 6G Systems: An Overview of Technologies, Opportunities and Challenges, in IEEE Access. Link.

Andre Bourdoux, Andre Noll Barreto, Barend van Liempd, Carlos de Lima, Davide Dardari, Didier Belot, Elana-Simona Lohan, Gonzalo Seco-Granados, Hadi Sarieddeen, Henk Wymeersch, Jaakko Suutala, Jani Saloranta, Maxime Guillaud, Minna Isomursu, Mikko Valkama, Muhammad Reza Kahar Aziz, Rafael Berkvens, Tachporn Sanguanpuak, Tommy Svensson, Yang Miao(2020). 6G White Paper on Localization and Sensing. arXiv preprint arXiv:2006.01779.

Samad Ali, Walid Saad, Nandana Rajatheva, Kapseok Chang, Daniel Steinbach, Benjamin Sliwa, Christian Wietfeld, Kai Mei, Hamid Shiri, Hans-Jürgen Zepernick, Thi My Chinh Chu, Ijaz Ahmad, Jyrki Huusko, Jaakko Suutala, Shubhangi Bhadauria, Vimal Bhatia, Rangeet Mitra, Saidhiraj Amuru, Robert Abbas, Baohua Shao, Michele Capobianco, Guanghui Yu, Maelick Claes, Teemu Karvonen, Mingzhe Chen, Maksym Girnyk, Hassan Malik (2020). 6G White Paper on Machine Learning in Wireless Communication Networks. arXiv preprint arXiv:2004.13875.

Alasalmi, Tuomo; Suutala, Jaakko; Koskimäki, Heli; Röning, Juha (2020). Better Classifier Calibration for Small Data Sets. ACM Transactions on Knowledge Discovery in Data. Accepted. arXiv preprint arXiv:2002.10199.

Alasalmi, Tuomo; Suutala, Jaakko; Koskimäki, Heli; Röning, Juha (2020). Better Multi-class Probability Estimates for Small Data Sets. arXiv preprint arXiv:2001.11242.

Full list of publications

Talks

Most recent talks:

Jaakko Suutala. AI and Machine Learning for Localization: An Overview and Future Perspectives. An International Symposium (Virtual Mode) on "Role of Localization/Positioning in 5G,IoT and E-Health", Nagpur (virtual symposium), India. Invited talk, 19th Feb 2021. Link to symposium. presentation (pdf)

Jaakko Suutala. Role of Machine Learning in Localization and Sensing. Localization and Sensing: Technologies, Opportunities and Challenges, Oulu, Finland. Invited talk, 18th Nov 2020. Link to webinar.

Resume

Curriculum Vitae: (pdf) (updated 16.04.2024)

 

Updated: 16.04.2024