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Antti Oulasvirta, Associate Professor

Antti Oulasvirta leads the User Interfaces research group at Aalto University and the Interactive AI research program at FCAI (Finnish Center for AI). Prior to joining Aalto, he was a Senior Researcher at the Max Planck Institute for Informatics and the Cluster of Excellence on Multimodal Computing and Interaction at Saarland university. He received his doctorate in Cognitive Science from the University of Helsinki in 2006, after which he was a Fulbright Scholar at the School of Information in University of California-Berkeley in 2007-2008 and a Senior Researcher at Helsinki Institute for Information Technology HIIT in 2008-2011. During his postgraduate studies in 2002-2003, he was an exchange student at UC Berkeley's Neuropsychology Lab. He was awarded the ERC Starting Grant (2015-2020) for research on computational design of user interaces. Dr. Oulasvirta serves as an associate editor for ACM TOCHI and has previously served International Journal of Human-Computer Studies, as well as served as a column editor for IEEE Computer. He frequently participates in the paper committees of HCI conferences, including the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI). His work has been awarded the Best Paper Award and Best Paper Honorable Mention at CHI twelve times between 2008 and 2019. He has held keynote talks on computational user interface design at NordiCHI'14, CoDIT'14, EICS'16, IHCI'17, ICWE'19, and Chinese CHI '19. He is a member of ELLIS (European Laboratory for Learning and Intelligent Systems). In 2019, he was invited to the Finnish Academy of Science and Letters.

Research Group

Computational design and intelligent UIs: Our research looks at computational methods in human-computer interaction. We study principles of model-driven generation and adaptation of user interfaces, where an optimizer utilizes predictive models of human perception, behavior, and experience to anticipate users' responses to computer-generated designs. These models can be learned or parametrized based on user data. Optimization can be used to generate design ideas, solve hard design problems, facilitate creativity in design, and automate design adaptation. Learn more by reading our Cover Feature Article in IEEE Computer 2017 and get a hands-on experience in our CHI2019 course on Bayesian Methods in Computational Interaction.

Interactive AI: As part of the new Finnish Center for AI we work to study methods that can provide AI with the capability to understand the user, which is a prerequisite for making AI understandable. Our goal is AI that is able to augment human capabilities in interactive tasks.

Interface technologies: We study technical principles of novel interface technology, such as freeform gesture input enabled by touchscreen and computer vision sensing. We also model motor control principles of efficient input methods underpinning familiar input methods like buttons, keyboards, and pointing devices.

More information:

Computational Interaction (Oxford University Press 2018)

Computational Interaction Computational interaction applies abstraction, automation, and analysis to inform our understanding of the structure of interaction and also to inform the design of the software that drives new and exciting human-computer interfaces. The methods of computational interaction allow, for example, designers to identify user interfaces that are optimal against some objective criteria. They also allow software engineers to build interactive systems that adapt their behaviour to better suit individual capacities and preferences. This book introduces computational interaction design to the reader by exploring a wide range of computational interaction techniques, strategies and methods. It explains how techniques such as optimisation, economic modelling, machine learning, control theory, formal methods, cognitive models and statistical language processing can be used to model interaction and design more expressive, efficient and versatile interaction.


Full publication list in Scholar

2019 highlights: 2018 highlights: 2017 highlights:
2016 highlights:

Awards and Recognition

Best papers


We organize a Human-Computer Interaction major in the CCIS Master's program and offer a specialization in computational interaction in the EIT HCID programme. Selected courses in 2019-2020: See Aalto MyCourses for details.

We always have several exciting Master's thesis topics. To inquire topics, please email me with your CV, transcript, and letter of interest. We also offer internship possiblities for Aalto and foreign students.

Postdocs and PhD Students

Postdocs (current and former) PhD students (current): PhD students (graduated):

Note! We are always looking for outstanding PhD students interested in modeling, computational approaches, and experimental studies in HCI. Doing a PhD in our group means researching an advanced topic in user interfaces for four years in an intellectually stimulating environment. The applicant should have a Master's degree in computer science, engineering, statistics, cognitive science, psychology, or a related field and show an outstanding academic record. To inquire positions, please contact me per email, sending your CV, transcripts with grades, and letter of interest. Incomplete application packages will be ignored. There are also regular calls for PhD students in HICT.


Computer Science Building, Department of Communications and Networking, Konemiehentie 2, 13000 Aalto University, Finland
Email: firstname dot lastname at aalto dot fi