Institutionen för datateknik

Forskning inom datateknik

Research highlights

Super Stomp. Kuva: Valo Motion.

Multiplayer bouncing exercise brings extra motivation

The game gives players an empowering experience using custom computer vision, movement exaggeration, and game design techniques.

Lightning strikes

Machine learning helps to predict blackouts caused by storms

A collaboration between computer scientists at Aalto University and the Finnish Meteorological Institute applies machine learning to predict how damaging a storm will be

Illustration of neural networks in a hospital environment

Neural network for elderly care could save millions

A deep neural network model helps predict healthcare visits by elderly people, with the potential to save millions

Suomessa kehitettiin tekoäly, joka ymmärtää paremmin ihmisen tavoitteita

Designing AI that understands humans’ goals better

To make a better smart assistant, we need an AI that understands its user and does not constantly need detailed instructions

Ana Triana Hoyos (vasemmalla) ja Talayeh Aledavood tekivät tutkimuskatsauksen mielenterveyspotilaiden unta seuraavista sovelluksista ja laitteista. Kuva Matti Ahlgren / Aalto-yliopisto

Apps and wearable technology help to track sleep of people with mental health disorders

According to the findings of a recent review article, this type of technology could even help to recognize factors that correlate with mental health disorders



Institutionen för datateknik är värd för flera forskningsgrupper. Läs mer nedan (på engelska)

Adaptive Systems of Intelligent Agents

The Adaptive Systems of Intelligent Agents (ASIA) Research Group develops Information Architectures that support the Publication and Discovery of services and information sources, provided by Intelligent Agents that can adapt themselves and their joint system according to changes in themselves or in their environment, including context.

Applications of Machine Learning Group

The AML group is developing or has developed new machine learning techniques and applications.

Applications of Machine Learning Research, Aalto University

Artificial Intelligence and Software Systems

The A.I. and Software Systems (AISS) research group focuses on computing technologies for designing, building and managing intelligent systems.

Computer components, photo: Matti Ahlgren/Aalto Univesity

Combinatorics of Efficient Computations

Our group studies various aspects of efficient computations, including for instance approximation algorithms, online algorithms, exact algorithms, combinatorial optimization, and data structures.

CS Building (T-talo) at Aalto University Campus

Complex Systems

Complex Systems is a transdisciplinary research area that builds on statistical physics, computer science, data science, and applied mathematics.

Complex Systems, Aalto University

Computational Logic

The Computational Logic Group develops automated reasoning techniques for solving challenging computational problems in engineering and science.

CS Building Aalto University

Computational Systems Biology

Our research group focuses on developing methods for high-throughput bioinformatics, computational biomedicine, synthetic biology and probabilistic modeling.

Computational Systems Biology Research group

Content-Based Image and Information Retrieval Group

We develop novel machine learning methods for automatic multimedia analysis and retrieval.

CS defence SCI computer science

Data Mining

The data-mining group focuses on developing novel methods to extract knowledge from data, designing algorithms to summarize large volumes of data efficiently and effectively, and exploring new ways of using the extracted information.

CS Building Aalto University

Digital Content Communities

The Digital Content Communities studies the intersection of groups, technology and society. This includes research aimed to produce novel technical tools for group interaction as well as more social science oriented examination on the implications new communication technology may have to groups and society.

CS Building Aalto University

Distributed Algorithms

Our current research focuses on the foundations of distributed computing, the key research question is related to the concept of locality in the context large computer networks.

Distributed Algorithms Research group

Distributed and Pervasive Systems

The Distributed and Pervasive Systems area spans from mobile networking and communications to distributed computing and Big-data.

Distributed Systems Group

Group studies software technologies for open, loosely-coupled, heterogeneous, and dynamic distributed systems.

Aalto-yliopisto, liput / kuvaaja: Aino Huovio

Game Research

Games are a multidisciplinary field, and our research interests include physics simulation, procedural animation, control optimization, AI, full-body human-computer interaction, virtual and augmented realities, games and learning.

Game Research, Aalto University

Kernel Methods, Pattern Analysis and Computational Metabolomics (KEPACO)

The KEPACO group develops machine learning methods, models and tools for data science, in particular computational metabolomics. The methodological backbone of the group is formed by kernel methods and regularized learning.

KEPACO Research group

LeTech - Learning + Technology

The Learning + Technology Group focuses on computing education, educational technology and software visualization. We adopt a research perspective on learning and teaching that allows us to improve education through better educational technologies and teaching methods

CS Building Aalto University

Natural Computation

The group seeks to understand, model, and program naturally occurring or nature-inspired self-organising processes.

Natural Computation Research group

PREAGO Research Group

The Product Requirements and Architecture Research Group (Preago) is specialized in high quality research of topics related to requirements engineering, software architectures and variability.

Probabilistic Machine Learning Group

We develop new methods for probabilistic modeling, Bayesian inference and machine learning. Our current focuses are in particular learning from multiple data sources, Bayesian model assessment and selection, approximate inference and information visualization.

PML research group, Aalto University Computer Science

Secure Systems Research Group

The goal of the Secure Systems research group is to create new technologies and design and analysis methods for the development of secure computing and communication systems.

CS Building Aalto University

Semantic Computing (SeCo)

Research on semantic technologies, such as the Semantic Web and intelligent web services.

Map screenshot from web service by Semantic Computing Research group at Aalto University

String Algorithms

The group develops and analyzes efficient algorithms for information retrieval. Our perspective is algorithm engineering. We consider both exact and approximate string searching as well as indexing methods. Also algorithms for data compression and computational biology are studied.

CS Building Aalto University

Research outputs

Latest research outputs from Department of Computer Science.

See all research publications:

Tropomyosin Tpm3.1 Is Required to Maintain the Structure and Function of the Axon Initial Segment

Amr Abouelezz, Holly Stefen, Mikael Segerstråle, David Micinski, Rimante Minkeviciene, Lauri Lahti, Edna C. Hardeman, Peter W. Gunning, Casper C. Hoogenraad, Tomi Taira, Thomas Fath, Pirta Hotulainen 2020 iScience

Accounting for environmental variation in co-occurrence modelling reveals the importance of positive interactions in root-associated fungal communities

Nerea Abrego, Tomas Roslin, Tea Huotari, Ayco J.M. Tack, Björn D. Lindahl, Gleb Tikhonov, Panu Somervuo, Niels Martin Schmidt, Otso Ovaskainen 2020 MOLECULAR ECOLOGY

Higher host plant specialization of root-associated endophytes than mycorrhizal fungi along an arctic elevational gradient

Nerea Abrego, Tea Huotari, Ayco J.M. Tack, Björn D. Lindahl, Gleb Tikhonov, Panu Somervuo, Niels Martin Schmidt, Otso Ovaskainen, Tomas Roslin 2020 ECOLOGY AND EVOLUTION

Relaxing the strong triadic closure problem for edge strength inference

Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Antonis Matakos, Polina Rozenshtein 2020 Data Mining and Knowledge Discovery

Transparency of SIM profiles for the consumer remote SIM provisioning protocol

Abu Shohel Ahmed, Mukesh Thakur, Santeri Paavolainen, Tuomas Aura 2020 Annales des Telecommunications/Annals of Telecommunications

Automated structure discovery in atomic force microscopy

Benjamin Alldritt, Hapala Hapala, Niko Oinonen, Fedor Urtev, Ondrej Krejci, Filippo Federici Canova, Juho Kannala, Fabian Schulz, Peter Liljeroth, Adam Foster 2020 Science Advances

Plasmids shaped the recent emergence of the major nosocomial pathogen Enterococcus faecium

Sergio Arredondo-Alonso, Janetta Top, Alan McNally, Santeri Puranen, Maiju Pesonen, Johan Pensar, Pekka Marttinen, Johanna Braat, Malbert Rogers, Willem van Schaik, Samuel Kaski, Rob J L Willems, Jukka Corander, Anita Schürch 2020 MBIO

Enabling successful crowdfunding for entrepreneurs in marginalized communities

Niina Arvila, Heike Winschiers-Theophilus, Pietari Keskinen, Roosa Laurikainen, Marko Nieminen 2020 AcademicMindtrek 2020 - Proceedings of the 23rd International Academic Mindtrek Conference

Cumulative effects of triadic closure and homophily in social networks

Aili Asikainen, Gerardo Iñiguez, Javier Ureña-Carrión, Kimmo Kaski, Mikko Kivelä 2020 Science Advances

Likelihood-Free Inference with Deep Gaussian Processes

Alex Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski 2020
More information on our research in the Research database.
Research database


Forskningen inom institutionen för datateknik är indelad i sju olika forskningsområden. Läs mer nedan (på engelska).


The algorithms research area studies the paradigms and principles of computation.

Aalto University/Aki-Pekka Sinikoski

Data science

The data science research area fuses computer science, statistics and applied mathematics to solve application problems in a data-driven manner.

Aalto University/Aki-Pekka Sinikoski

Machine Learning and Artificial Intelligence

Machine learning, the core technology underlying many recent breakthroughs in Artificial Intelligence (AI), is one of the strengths of Aalto University, with a long history starting from neural network pioneers Teuvo Kohonen and Erkki Oja.

Aalto university / kuva: Aino Huovio

Mobile and Distributed Systems

The mobile and distributed systems research focuses on the challenges brought by the large growth in data volumes through digitalization of society, and the huge increase in connected devices through Internet of Things (IoT).

Aalto University/Aino Huovio

Security and Privacy

Our research aims to provide both a fundamental understanding of security and privacy issues, and practical solutions to enhance the security and privacy of real-world systems.

Human-sized lamp in the shape of the Aalto logo, capital A followed by an exclamation mark, stands in a dark space / photo by Aalto University, Lasse Lecklin

Software Engineering

The software engineering field studies the activities, processes and practices that create software artifacts, as well as the actual artifacts created.

Three students working on laptops in the Design Factory kitchen / photo by Aalto University, Unto Rautio

Visual Computing and Human Computer Interaction

Visual computing and HCI research focuses on computer systems that perceive the world and augment human perception, with the goal of easing life.

Aalto University/Unto Rautio

Research infrastructure

Department of Computer Science has in-house infrastructure for computational research hosted by Aalto Science-IT. In addition, Aalto University collaborate with national super computer facilities CSC.


Science-IT tillhandahåller en infrastruktur för avancerad beräkningsforskning på Aalto-universitetet och samordnas av Högskolan för teknikvetenskaper.

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Piece of code on the computer screen, colourful text

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