Antti Kangasrääsiö

Antti Kangasrääsiö

M.Sc. (Tech.), Researcher / Doctoral student

Email
firstname.lastname@aalto.fi
Postal Address
Aalto University School of Science,
Department of Computer Science,
P.O. Box 15400, FI-00076 Aalto, Finland
Room
A340 in T-building, Otaniemi

Other webpages
Google Scholar
LinkedIn

Research Affiliations
Member of Probabilistic Machine Learning Research Group at Aalto University [research group web page].

Member of Helsinki Doctoral Education Network in Information and Communications Technology (HICT) [doctoral school web page]

Member of EIT Digital Doctoral School at Helsinki [doctoral school web page]

Member in the Finnish Centre of Excellence in Computational Inference Research [centre web page]

Participating in the Revolution of Knowledge Work (Re:Know) project [research project web page]

Submitted / Preprints
Antti Kangasrääsiö, Samuel Kaski. Inverse Reinforcement Learning from Summary Data. 2017. [preprint]

Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Michael Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski. ELFI: Engine for Likelihood Free Inference. 2017. [preprint]

Scientific Publications
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta. Inferring Cognitive Models from Data using Approximate Bayesian Computation. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI'17, pp. 1295-1306. ACM, 2017. [access publication] [slides] [preprint] [reviews] [conference web page]

Antti Kangasrääsiö, Yi Chen, Dorota Glowacka, and Samuel Kaski. Interactive Modeling of Concept Drift and Errors in Relevance Feedback. In Proceedings of the 24th Conference on User Modeling, Adaptation and Personalization, UMAP'16, pp. 185-193. ACM, 2016. [access publication] [PDF] [poster] [preprint] [reviews] [publication info] [conference web page]

Antti Kangasrääsiö, Dorota Głowacka, and Samuel Kaski. Improving Controllability and Predictability of Interactive Recommendation Interfaces for Exploratory Search. In Proceedings of the 20th International Conference on Intelligent User Interfaces, IUI'15, pp. 247-251. ACM, 2015. [access publication] [PDF] [slides] [video] [reviews] [publication info] [conference web page]

Olli Kilkki, Antti Kangasrääsiö, Raimo Nikkilä, Antti Alahäivälä, Ilkka Seilonen. Agent-based Modeling and Simulation of a Smart Grid: A Case Study of Communication Effects on Frequency Control. In Engineering Applications of Artificial Intelligence, vol 33, 2014. pp. 91-98. [access publication] [PDF] [publication info]

Johanna Laaksonen, Antti Kangasrääsiö, Juha Kaila. Forecasting Material Flows by Using Agent Based Modeling and Simulation. Case Study: Biowaste from Finnish Retail Stores. In ISWA BEACON 2nd International Conference on Final Sinks, 2013. pp. 95-104. [PDF] [publication info] [conference web page]

Johanna Laaksonen, Antti Kangasrääsiö, Juha Kaila. Feasibility of Agent Based Simulation for Modeling the Decision Making Processes in Recycling and its Effects on Material Flows and Environmental Impacts. In EcoBalance, Japan, 2012. Electronic publication (CD-ROM). [publication info] [conference web page]

Other Scientific Articles
Antti Kangasrääsiö, Samuel Kaski. Modelling Human Decision-making based on Aggregate Observation Data. In ICML 2017 Workshop on Human in the Loop Machine Learning, 2017. Extended abstract. [PDF] [poster] [reviews] [workshop web page]

Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Michael Gutmann, Aki Vehtari, Jukka Corander and Samuel Kaski. ELFI: Engine for Likelihood-Free Inference. In ICML 2017 Workshop on Implicit Models, 2017. Extended abstract. [GitHub] [workshop web page]

Antti Kangasrääsiö, Jarno Lintusaari, Kusti Skytén, Marko Järvenpää, Henri Vuollekoski, Michael Gutmann, Aki Vehtari, Jukka Corander and Samuel Kaski. ELFI: Engine for Likelihood-Free Inference. In NIPS 2016 Workshop on Advances in Approximate Bayesian Inference, 2016. Extended abstract. [PDF] [poster] [GitHub] [reviews] [workshop web page]

Antti Kangasrääsiö, Dorota Głowacka, and Samuel Kaski. Personalization of Search Results using Interactive Intent Modeling. In ICML 2016 Workshop on Computational Frameworks for Personalization, 2016. Extended abstract. [PDF] [poster] [publication info] [workshop web page]

Antti Kangasrääsiö, Yi Chen, Dorota Glowacka, and Samuel Kaski. Dealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach. IUI'16 Companion. ACM, 2016. Poster. [access publication] [PDF] [video] [poster] [reviews] [publication info] [conference web page]

Antti Kangasrääsiö, Dorota Głowacka, and Samuel Kaski. Improving Controllability and Predictability of an Interactive User Model Driven Search Interface. In NIPS 2014 Workshop on Human Propelled Machine Learning, 2014. Extended abstract. [PDF] [poster] [publication info] [workshop web page]

Antti Kangasrääsiö, Dorota Głowacka, Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Ksenia Konyushkova, Kumaripaba Athukorala, Ilkka Kosunen, Aki Reijonen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. Interactive Visualization of Search Intent for Exploratory Information Retrieval. In ICML 2014 Workshop on Crowdsourcing and Human Computing, 2014. Extended abstract. [PDF] [poster] [publication info] [workshop web page]

Theses
Antti Kangasrääsiö. Feasibility of Agent Based Modeling and Simulation in Modeling Waste Value Chains. Aalto University, 2012. Master's Thesis. [PDF] [publication info]

Antti Kangasrääsiö. Methods of Adaptive Control. Helsinki University of Technology, 2010. Bachelor's Thesis (in Finnish). [PDF] [publication info]
Other Talks and Presentations
Invited lecture: ELFI: Engine for Likelihood Free Inference. European Meeting of Statisticians, Helsinki, 25.7.2017. [slides] [demo]

Guest lecture: Interactive Modelling of Search Intent for Exploratory Search. Four Eyes Lab, UCSB, 18.3.2016.

Seminar: Interactive Modelling of Search Intent for Exploratory Search. Centre for Data-Driven Discovery, Caltech, 17.3.2016. [Event page]

Guest lecture: SciNet -- Scientific Search Engine for Exploratory Search. Sugiyama Laboratory, Tokyo University, 16.12.2015.

Guest lecture: SciNet -- Scientific Search Engine for Exploratory Search. Tanaka Laboratory, University of Kyoto, 1.12.2015.

Aalto Complex Systems Society invited talk: Human Computer Interaction and Machine Learning. Aalto University, 17.9.2015.

HIIT Seminar: Improving Controllability and Predictability of Interactive Search Interfaces. Aalto University, 1.6.2015. [Event page]


In News
Teaching a Machine to Understand Humans, DZone AI, 30.6.2017.

Teaching a Machine to Understand Humans, The Horizons Tracker, 12.6.2016.

Computers can explain behaviour of individuals by tracking their movements, Process & Control Engineering Today, 4.6.2016.


Software
ELFI: Engine for Likelihood-Free Inference [GitHub]


Teaching
T-61.5140 Machine learning: Advanced probabilistic methods (Teaching assistant, 2016)

T-61.3050 Machine learning: Basic principles (Teaching assistant, 2014)

AS-0.3100 Seminar in automation and systems technology (Teaching assistant, 2012)

AS-0.1400 Automation and media technology at work (Teaching assistant, 2012)

AS-0.2230 Laboratory exercises in control and automation engineering (Teaching assistant, 2009, 2010, 2012)

AS-116.1100 Manufacturing automation (Teaching assistant, 2009)

AS-0.1103 Basic course in C-programming (Teaching assistant, 2009)


Instructed Theses
Hai Minh Phan. Dialogue-based Information Retrieval. Aalto University, 2017. Bachelor's Thesis (in Finnish). [publication info]

Shishir Bhattarai. Interactive User Intent Modeling: Usefulness of Session-level Relevance Feedback. Aalto University, 2016. Master's Thesis. [publication info]

Misamatti Koistinen. Collaborative Filtering, Bandit-algorithms and their Applications. Aalto University, 2016. Bachelor's Thesis (in Finnish). [publication info]

Tuure Salonheimo. Use of Machine Learning in User-based Collaborative Filtering. Aalto University, 2016. Bachelor's Thesis (in Finnish). [publication info]

Markus Saukkonen. Contextual Personalization Methods in Information Retrieval. Aalto University, 2016. Bachelor's Thesis (in Finnish). [publication info]