News

August, 2022

Papers accepted to be published in the highest-ranked computer science publication venue IEEE CVPR, as well as in the Information Processing and Management journal. Videos also available under the videos and demo link.

March, 2022

Tung Vuong successfully defended his PhD thesis: Behavioral Task Modeling for Entity Recommendation. Congratulations!


August, 2021

Three papers accepted to be published in ACM TOIS, ACM TOCHI, and ACM RecSys. Watch out for preprints.


Our new project where we aim to develop crowd-powered brain-computer interfaces for affective representation learning is recommended to be funded under the CHIST-ERA scheme. Looking forward to work with European partners on this.


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

Intelligent systems can already mimic human cognition in understanding the open and complex world, analyzing a variety of data, and making independent decisions. To this end, artificial intelligence can already learn to accomplish many predictive tasks from data provided by humans as examples or solve problems in a well-defined scope. However, scenarios in which machine learning is used to augment human interactions with systems for assisting humans in supporting their information needs, decisions, and tasks in complex contexts have turned out to be much more challenging to design.

The lab's research broadly focuses on understanding, modeling, and augmenting such interactions with intelligent systems and agents that operate over large, complex, unstructured information spaces and in which interactions occur over multiple modalities ranging from conventional interfaces to physiological and brain-computer interfaces.

Interactions with large unstructured information spaces arise in many human-centered communication contexts: search and recommendation systems, visual analytics and information comprehension, and ubiquitous computing. The lab studies novel interaction modalities which can provide information about the users' physical context, but also about the users themselves, such as their cognitive and affective states.

The lab's research approach is multidisciplinary and combines methods from several subfields of computer science, electrical engineering and signal processing, cognitive science, and beyond.

Research highlights

Interactive Information Retrieval

We develop novel information retrieval and interactive visualization methods to assist humans search, perceiving, and comprehending complex information spaces.

Brain-computer Interfacing and Physiological Input

We develop new implicit and reactive interfaces toward information that utilize brain and physiological signals and apply them in adaptive and interactive systems.

Behavioral Monitoring and User Modeling

We develop user models that observe natural man-machine interactions and learn users' goals, intentions, and needs from this passively observed digital behavior.

Publications

Our research is published in top venues for human-computer interaction (such as CHI, UIST, and IUI), information retrieval and access (such as SIGIR, TOIS, JASIST and IPM), pattern recognition and computer vision (such as CVPR), and man-machine interfacing and affective computing (such as IEEE TAFFC), as well as general science outlets (such as Communications of the ACM and Scientific Reports). Below is a selection of 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

The group operates at the University of Copenhagen, Denmark (as part of the IRLab) and the University of Helsinki, Finland. Our research is funded by the European Union and the Academy of Finland and supported by the Finnish Center for Artificial Intelligence (FCAI) and the Danish Pioneer Center for AI.

Tuukka Ruotsalo
Group leader

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

Tung Vuong
Postdoc

Keith Davis
PhD student

Carlos de la Torre Ortiz
PhD student

Jun Ma
PhD student

Kalle Mäkelä
Research Assistant

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 was interviewed by the National Broadcasting Company (YLE) for their Science radio about our work on brain-computer interfaces.
  • 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.
  • Tuukka was interviewed in Helsingin Sanomat about brain-computer interfaces.
  • Our research on brain sourcing was featured in the National Broadcasting Company YLE news.
  • Our research on brain sourcing was featured in the Digital Trends.
  • Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for typing.
  • Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for gaming.
  • Tuukka was interviewed by Helsingin Sanomat about language processing.
  • Our research on brain-computer interfacing for recommender systems was featured in TechCrunch.
  • Tuukka was interviewed by Helsingin Sanomat about brain-computer interfacing for information retrieval and recommendation.
  • Our research of intent modeling for information retrieval was featured in TechCrunch.
  • Tuukka was interviewed by Helsingin Sanomat about search engines and language processing.
  • Our work on information retrieval was featured in Economic Times.

    • Work with us

    We are always interested in hearing about motivated students in human-computer interaction, information retrieval, applied machine learning, affective computing, and brain-computer interfacing.