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Publications

 

Refereed Journal Papers

[6] S.V. Hoseini, J. Suutala, J. Partala, K. Halunen (2024): Threat modeling AI/ML with the Attack Tree, IEEE Access. Link

[5] 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.

[4] 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:2002.10199.

[3] Marko Höyhtyä, Aarne Mämmelä, Marina Eskola, Marja Matinmikko, Juha Kalliovaara, Jaakko Ojaniemi, Jaakko Suutala, Reijo Ekman, Roger Bacchus, and Dennis Roberson (2016). Spectrum occupancy measurements: A survey and use of interference maps . IEEE Communications Surveys & Tutorials, Volume 18 (4), pp. 2386-2414.

[2] K. Fujinami, S. Kagatsume, S. Murata, T. Alasalmi, J. Suutala, J. Röning (2014). An Augmented Refrigerator with the Awareness of Wasteful Electricity Usage. International Journal of Internet, Broadcasting and Communication 6 (1), pp. 1-4.

[1] Suutala J., Röning J. (2008). Methods for Person Identification on a Pressure-sensitive Floor: Experiments with Multiple Classifiers and Reject Option, Information Fusion Journal, Special Issue on Applications of Ensemble Methods, Volume 9, Issue 1, pp. 21-40 (January 2008). bibTex | Available online .

 

Refereed Conference and Workshop Papers

[22] Henna Tiensuu, Virpi Leinonen, Jani Isokääntä and Jaakko Suutala (2024): Machine Learning -based Optimization of Biomass Drying Process: Application of Utilizing Data Center Excess Heat, EUROSIM 2024, Accepted.

[21] Miika Malin and Jaakko Suutala (2024): Data Center Resource Usage Forecasting with Convolutional Recurrent Neural Networks, EUROSIM 2024, Accepted.

[20] Tuutijärvi J., Tamminen, S., Kuittinen M., Ojala M., Suutala J. (2024): AI-Assisted Decision Support for District Heating Demand Response, The 19th IEEE Conference on Industrial Electronics and Applications (ICIEA 2024), Accepted.

[19] 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. full paper (pdf)

[18] Alasalmi, Tuomo; Koskimäki, Heli; Suutala, Jaakko; Röning, Juha (2018). Getting More Out of Small Data Sets : Improving the Calibration Performance of Isotonic Regression by Generating More Data Proceedings of the 10th International Conference on Agents and Artificial Intelligence, Volume 2, ICAART. pp. 379-386.

[17] Alasalmi T, Koskimäki H, Suutala J and Röning J (2016). Instance Level Classification Confidence Estimation . Distributed Computing and Artificial Intelligence, 13th International Conference : Part I. Advances in Intelligent Systems and Computing 474. 275-282.

[16] Alasalmi T, Koskimäki H, Suutala J, Röning J (2015), Classification Uncertainty of Multiply Imputed Data . 2015 IEEE Symposium Series on Computational Intelligence: IEEE Symposium on Computational Intelligence and Data Mining (2015 IEEE CIDM).

[15] Tanim Taher, Ryan Attard, Ali Riaz, Dennis A. Roberson, Jesse Taylor, Kenneth J. Zdunek, Juhani Reijo Ekman, Jarkko Paavola, Jaakko Suutala, Juha Röning, Marja Matinmikko, Marko Höyhtyä and Allen B. MacKenzie (2014), Global Spectrum Observatory Network Setup and Initial Findings. 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), pp. 79-88.

[14] Tuomo Alasalmi, Jaakko Suutala, Juha Röning (2012), Real-time Non-intrusive Appliance Load Monitor - Feedback System for Single-point per Appliance Electricity Usage. SMARTGREENS 2012, pp. 203-208.

[13] Trang Thuy Vu, Akifumi Sokan, Hironori Nakajo, Kaori Fujinami, Jaakko Suutala, Pekka Siirtola, Tuomo Alasalmi, Ari Pitkänen, Juha Röning (2011) Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage . IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2011), pp. 138-141.

[12] Trang Thuy Vu, Akifumi Sokan, Hironori Nakajo, Kaori Fujinami, Jaakko Suutala, Pekka Siirtola, Tuomo Alasalmi, Ari Pitkänen, Juha Röning (2011) Detecting water waste activities for water-efficient living, Ubicomp 2011, pp. 579-580.

[11] Suutala J., Fujinami K., and Röning J. (2010) Persons Tracking with Gaussian Process Joint Particle Filtering, IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010), 29 August - 1 September, Kittil? Finland, pp. 160-165. bibTex | full paper (ps) | full paper (pdf) | presentation (pdf) | demo video (avi) |

[10] Kätevä J., Laurinen P., Rautio T., Suutala J., Tuovinen L., Röning J. (2010) DBSA - A Device-Based Software Architecture for Data Mining , Proceedings of the 2010 ACM symposium on Applied Computing (SAC 2010). bibTex | full paper (pdf) |

[9] Suutala J., Fujinami K., Röning J. (2008) Gaussian Process Person Identifier Based on Simple Floor Sensors, 3rd European Conference on Smart Sensing and Context (EuroSSC 2008), October 29-31, Z?ich, Switzerland, pp. 55-68. bibTex | full paper (ps) | full paper (pdf) |

[8] Suutala J., Pirttikangas S., Röning J. (2007) Discriminative Temporal Smoothing for Activity Recognition from Wearable Sensors, International Symposium on Ubiquitous Computing Systems (USC2007), November 25-28, Tokyo, Japan, pp. 182-195. bibTex | full paper (ps) | full paper (pdf) |

[7] Suutala J., Röning J. (2005) Combining Classifiers with Different Footstep Feature Sets and Multiple Samples for Person Identification, 30th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2005), March 17-23, Philadelphia, PA, USA, Vol. 5, pp. 357-360. bibTex | full paper (ps) | full paper (pdf) | poster (pdf) |

[6] Tikanmäki A., Suutala J., Röning J. (2005) Instrumentation and Software Achitecture for a Smart Room, Smart Systems 2005, May 3-4, Seinäjoki, Finland, pp. 1-8. full paper (pdf)

[5] Koho K., Suutala J., Seppänen T., Röning J. (2004) Footstep Pattern Matching from Pressure Signals Using Segmental Semi-Markov Models, 12th European Signal Processing Conference (EUSIPCO 2004), September 6-10, Vienna, Austria, pp. 1609-1612. bibTex | full paper (pdf)

[4] Suutala J., Pirttikangas S., Riekki J., Röning J. (2004) Reject-Optional LVQ-Based Two-Level Classifier to Improve Reliability in Footstep Identification, Second International Conference on Pervasive Computing (PERVASIVE 2004), April 21-23, Linz / Vienna, Austria, pp. 182-187. bibTex | full paper (ps) | full paper (pdf) | presentation (pdf)

[3] Suutala J., Röning J. (2004) Towards the Adaptive Identification of Walkers: Automated Feature Selection of Footsteps Using Distinction- Sensitive LVQ, International Workshop on Processing Sensory Information for Proactive Systems (PSIPS 2004), June 14-15, Oulu, Finland, pp. 61-67. bibTex | full paper (ps) | full paper (pdf) | presentation (pdf)

[2] Pirttikangas S., Suutala J., Riekki J., Röning J. (2003) Learning Vector Quantization in Footstep Identification, The 3rd IASTED International Conference on Artificial Intelligence and Applications, September 8-10, Benalmadena, Spain (AIA 2003), pp. 413-417. bibTex | full paper (pdf) | presentation (pdf)

[1] Pirttikangas S., Suutala J., Riekki J., Röning J. (2003) Footstep Identification from Pressure Signals Using Hidden Markov Models, Finnish Signal Processing Symposium (FINSIG 2003), May, Tampere, Finland, pp. 124-128. bibTex | full paper (pdf) | presentation (pdf)

 

Refereed Conference and Workshop Abstracts and Presentations

[2] 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 | presentation (pdf)

[1] 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 | poster (pdf)

 

Book Chapters

[2] 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.

[1] 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.

 

Doctoral Thesis

[1] Suutala J. (2012) Learning Discriminative Models from Structured Multi-sensor Data for Human Context Recognition, Doctoral Thesis, University of Oulu, Department of Computer Science and Engineering, 221 pages. Available online . Open datasets collected during my doctoral thesis work here.

 

M.Sc. (Eng.) Thesis

[1] Suutala J. (2004) Methods for Person Identification from Pressure Signal of Walking Steps, M.Sc. Thesis, University of Oulu, Department of Electrical and Information Engineering, Oulu, Finland, 90 p., (in Finnish). bibTex | abstract | full text (ps) | full text (pdf)

 

Unrefereed Talks and Posters

[8] Jaakko Suutala (2024). The Future of AI. 37th congress organised by the Scandinavian Society of Anaesthesiology and Intensive Care Medicine (SSAI), Oulu, Finland, Invited talk, 17th Jun 2024. Link to congress. presentation (pdf)

[7] Jaakko Suutala (2023). Multi-modal machine learning for earth observation. Computational Mathematics and Statistics Seminar, University of Oulu, Finland, Invited talk, 30th Nov 2023. presentation (pdf)

[6] Jaakko Suutala (2023). Multi-modal machine learning and deep learning for earth observations and climate change mitigation in sub-Arctic and Arctic regions. Dublin, Ireland, Insight@DCU Visiting Research Lecture, Invited Talk, 4th Oct 2023. presentation (pdf)

[5] Jaakko Suutala (2021). 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)

[4] Jaakko Suutala (2020). The 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.

[3] Suutala J. (2010) Learning to Track Persons with Gaussian Process Joint Particle Filtering, The 3rd Asia-Europe Workshop on Ubiquitous Computing (AEWUC 2010), May 16, Helsinki, Finland. poster (pdf)

[2] Suutala J. (2008) Machine Learning Approaches to Activity Recognition and Person Identification, The 1st Asia-Europe Workshop on Ubiquitous Computing (AEWUC 2008), June 31 - August 1, Oulu, Finland. presentation (pdf)

[1] Suutala J. (2005) Beacon - Behavioural Modeling in Context-aware Systems, The final presentation of Research Programme on Proactive Computing (PROACT) organised by the Academy of Finland, December 2, Helsinki, Finland.

 

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