News

March, 2021

Our research on brain-computer interfacing for modeling personal attractiveness was featured in the Independent, the Daily Mail, VICE, RT, and many others.


February, 2021

Our paper titled “Brain-computer interface for generating personally attractive images” has been accepted for publication by IEEE Transactions on Affective Computing. Watch out for a preprint.


January, 2021

Our paper titled “Collaborative Filtering with Preferences Inferred from Brain Signals” has been accepted for publication at The Web Conference (WWW). Watch out for a preprint.


Our paper titled “Spoken Conversational Context Improves Query Auto Completion in Web Search” has been accepted for publication in ACM Transactions on Information Systems. Watch out for a preprint.


December, 2020

Our research was reviewed by the Cognitive Neuroscience Society, see here.


October, 2020

Our research on neuroadaptive generative modeling was featured in the Independent, unite.ai, La Vanguardia, ACM and many others.


September, 2020

The group starts to operate also at University of Copenhagen, Denmark. We are looking forward for new collaborations and exciting research!


Our paper on connecting generative adversarial networks (GANs) with brain-computer interfaces, titled Neuroadaptive modelling for generating images matching perceptual categories is published by Scientific Reports (Nature). The paper is available here.


August, 2020

Our paper titled “Generating Images Instead of Retrieving Them: Relevance Feedback on Generative Adversarial Networks” published at SIGIR 2020

The paper is available here


May, 2020

Our YouTube channel is now available here.

Two of our papers, published in Journal of the Association for Information Science and Technology, receive a high-impact award being in the top 10% most downloaded papers! The papers are: Integrating neurophysiologic relevance feedback in intent modeling for information retrieval and Understanding user behavior in naturalistic information search tasks.


April, 2020

Our paper on interactive GANs accepted for publication at SIGIR 2020. Stay tuned for a preprint.

Our paper on brain responses and information theory, titled "Information gain modulates brain activity evoked by reading" accepted for publication at Scientific Reports (Nature). The paper is available here.


February, 2020

Our paper on brainsourcing, titled "Brainsourcing: Crowdsourcing Recognition Tasks via Collaborative Brain-Computer Interfacing" accepted for publication at CHI 2020. Paper available here.

Research

What if computing systems could sense thoughts and cognitive states in response to perception of our environment? What if computing systems could assist us by augmenting our cognitive capabilities, retrieving and recommending information, and monitoring our well-being? What if we could interact with computing directly via passive observations of our physiology and brain activity? Our research focuses on cognitive computing with a vision of using machine learning to interpret multitude of signals originating from human cognition, and using signals measured from human cognition to augment computation. Our research approach is multidisciplinary and combines methods from several subfields of computer science, electrical engineering and signal processing, and cognitive neuroscience. We apply the developed methods and methodologies in brain-computer interfacing, physiological computing, information retrieval and recommender systems, user modeling, and human-computer interaction. The group operates at University of Helsinki, Finland and University of Copenhagen, Denmark. Our research is funded by the Academy of Finland and supported by the Helsinki Institute for Information Technology HIIT and the Finnish Center for Artificial Intelligence (FCAI).

Research highlights

Brain-computer Interfacing

We conduct fundamental research into developing new types of implicit brain-computer interfaces and applying them in novel, adaptive and interactive systems. Our current interaction with information retrieval systems rely on explicit interaction. Could we mine the relevance to or interest of the user directly from the human mind? Our research shows, for the first time, that with the help of EEG interpreted via machine learning is indeed possible.

Interactive Information Retrieval

We develop interactive machine learning methods for cognitive modeling of information retrieval, visualization, and information generation, and systems implementing these in real-world information seeking applications. We have developed a technique called interactive intent modeling that allows humans to direct exploratory search: the technique has been implemented in a real-world search engine SciNet.

Cognitive Modeling

We develop machine learning models to model, understand, and decode cognitive states of humans interacting with large information spaces, such as texts, images, and video. We have discovered that human information processing of language stimuli when reading follows information theoretic principles and can be explained by information gain.

Publications

Our research is published in top venues for information management, processing, and retrieval (such as SIGIR, TOIS, JASIST and IPM) and human-computer interaction (such as CHI, UIST, and IUI), as well as general science outlets (such as Communications of the ACM and Scientific Reports). Below is a selection of recent publications from our group that represent different research directions, from brain-computer interfacing and cognitive modeling, to interactive information generation and retrieval.

Lauri Kangassalo, Michiel Spapé, Giulio Jacucci, and Tuukka Ruotsalo. 2019. Why do Users Issue Good Queries?: Neural Correlates of Term Specificity. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'19). ACM, New York, NY, USA, 375-384.
Tuukka Ruotsalo, Jaakko Peltonen, Manuel J. A. Eugster, Dorota Głowacka, Patrik Floréen, Petri Myllymäki, Giulio Jacucci, and Samuel Kaski. 2018. Interactive Intent Modeling for Exploratory Search. ACM Trans. Inf. Syst. 36, 4, Article 44 (October 2018), 46 pages.
Carlos de la Torre-Ortiz, Michiel Spapé, Lauri Kangassalo, and Tuukka Ruotsalo. 2020. Brain Relevance Feedback for Interactive Image Generation. Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (UIST'20). ACM, New York, NY, USA, 1060–1070.
Giulio Jacucci, Oswald Barral, Pedram Daee, Michale Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, Jonathan Freeman, Luciano Gamberini, Samuel Kaski, and Benjamin Blankertz. 2019. Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. Journal of the Association for Information Science and Technology, 70: 917-930.
Tuukka Ruotsalo, Giulio Jacucci, Petri Myllymäki, and Samuel Kaski. 2015. Interactive Intent Modeling: Information Discovery Beyond Search. Communications of the ACM, Vol. 58 No. 1, Pages 86-92.
Lauri Kangassalo, Michiel Spapé, Niklas Ravaja, and Tuukka Ruotsalo. Information gain modulates brain activity evoked by reading. Scientific Reports (Nature) 10, 7671 (2020).
Manuel J.A. Eugster, Tuukka Ruotsalo, Michiel M. Spapé, Ilkka Kosunen, Oswald Barral, Niklas Ravaja, Giulio Jacucci, and Samuel Kaski. 2014. Predicting term-relevance from brain signals. In Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval (SIGIR '14). ACM, New York, NY, USA, 425-434.
Antti Ukkonen, Pyry Joona, Tuukka Ruotsalo. 2020. Generating Images Instead of Retrieving Them: Relevance Feedback on Generative Adversarial Networks. Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. Pages 1329-1338
Valeria Orso, Tuukka Ruotsalo, Jukka Leino, Luciano Gamberini, Giulio Jacucci. 2017. Overlaying social information: The effects on users’ search and information-selection behavior. Information Processing & Management, Volume 53, Issue 6, Pages 1269-1286
Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. Spapé, Oswald Barral, Niklas Ravaja, Giulio Jacucci, and Samuel Kaski. 2016. Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals. Nature Scientific Reports volume 6, Article number: 38580.

A good approximation of our publications is also provided by Google Scholar

People

Group members

Tuukka Ruotsalo
Group leader

Michiel Spapé
Senior researcher
(now officially with Niklas Ravaja's group)

Tung Vuong
PhD student
(supervised with G. Jacucci)

Keith Davis
PhD student

Carlos de la Torre Ortiz
PhD student

Jun Ma
PhD student

Zania Sovijärvi-Spapé
Research Assistant
(Interaction laboratory), on leave

Alumni

  • Lauri Kangassalo (moved to FMI)
  • Oswald Barral (co-supervised with G. Jacucci, moved to The University of British Columbia)
  • Khalil Klouche (co-supervised with G. Jacucci, founded wivr.io/)
  • Payel Bandyopadhyay (co-supervised with G. Jacucci, moved to Texas A&M University)
  • Ksenia Konyushkova (moved to EPFL and DeepMind)
  • Miamaria Saastamoinen (moved to National Library of Finland)
  • Antti Lipsanen (moved to Etsimo Healthcare)
  • Sean Weber (moved to Etsimo Healthcare)
  • Jukka Leino (moved to TuTasa)
  • Kseniia Belorustceva (moved to Digital Workforce)

    • Press and media

    Selected media and press appearances:

  • Tuukka and Michiel were interviewed by Tekniikan Maailma (the leading popular technology magazine in Finland) about our work.
  • Our research on neuroadaptive modeling was featured by the ACM.
  • Our research on neuroadaptive modeling was featured by La Vanguardia.
  • Our research on neuroadaptive generative modeling was featured in the Independent.
  • 9/2020 Tuukka was interviewed in Helsingin Sanomat about brain-computer interfaces.
  • 9/2020 Our research on brain sourcing was featured in the National Broadcasting Company YLE news.
  • 6/2020 Our research on brain sourcing was featured in the Digital Trends.
  • 5/2019 Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for typing.
  • 10/2018 Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for gaming.
  • 5/2017 Tuukka was interviewed by Helsingin Sanomat about language processing.
  • 12/2016 Our research on brain-computer interfacing for recommender systems was featured in TechCrunch.
  • 12/2016 Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for information retrieval and recommendation.
  • 2/2015 Our research of intent modeling for information retrieval was featured in TechCrunch.
  • 2/2015 Tuukka was interviewed by Helsingin Sanomat about search engines and language processing.
  • 2/2015 Our work on information retrieval was featured in Economic Times.

    • Work with us

    We are hiring! Open PhD positions in self-supervised learning, brain-computer interfacing and machine learning for neuroimaging data. In case you are a student at University of Helsinki or University of Copenhagen and are looking for Master’s thesis position that could be continued as a PhD, this is also possible. Please contact Tuukka for more information.
    We are also hiring via FCAI/HICT call (project 29)