Department of Computer Science

Large-scale Computing and Data Analysis

Large-scale distributed/parallel systems and big data analysis and management.
Symbolic big data illustration by Matti Ahlgren

The area focuses on novel methods, techniques, algorithms, and tools both for computing with large-scale distributed/parallel systems, and for big data analysis and management. Another focus is on identifying, optimizing, engineering, and verifying computationally challenging parts of software systems, dealing with huge amounts of data and computing resources, used in various application domains.

Research topics:

  • Programming models, tools and runtime systems for large-scale computing
  • Data intensive computing
  • High performance/extreme-scale computing/quantum computing
  • Performance, reliability, and elasticity for large-scale systems
  • Big data platforms and management
  • Large-scale data analysis and visualization
  • Data science and machine learning in large-scale systems
  • Computational models/algorithms for astrophysics, biophysics, dynamical systems, space plasmas, fusion plasmas, geoscience/earth observation
55-point stencil for astrophysical simulations. Image credit: Johannes Pekkilä

Modern HPC tools course

Modern HPC tools course: new course starting on Period II.

Department of Computer Science
Heli Julkunen seisoo talvisessa maisemassa ja katsoo hymyillen pois kamerasta. Hänellä on päällään valkoinen talvitakki ja taustalla näkyy sumua, puita ja lumihankia.

If you study computer science, you may end up developing better cancer treatments by applying AI

Heli Julkunen developed a machine learning method that predicts how different drug combinations kill cancer cells, and now she helps advance preventive healthcare as a data scientist

An illustration showing how stars consist of a core, a radiation zone and a convection zone. In giant stars, the convection zone is proportionately much larger.

Turbulent convection at the heart of stellar activity

By combining modern data analysis techniques with stellar structure modelling for main-sequence and giant stars, researchers shed new light on stellar dynamos

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

Nainen seisoo ja katsoo sivulle hymyillen kädet puuskassa. Hänellä on päällään musta paita ja sininen huivi ja aurinko värjää taustaa vaaleaksi.

Maarit Käpylä turned her childhood hobbies into a living

As a child, Maarit Käpylä was interested in the stars and coding, and now she researches the activity of the sun, which could not be done without computer science

Linh Nguyen sitting in a room full of Fatboy beanbags

‘Aalto is a safe place for building your skills and confidence’

Linh Nguyen wanted to obtain a degree with good job prospects and that is why she decided to study Data Science at Aalto University



Jorma Laaksonen

Jorma Laaksonen

Senior University Lecturer
T313 Dept. Computer Science
Riku Linna

Riku Linna

Vanhempi yliopistonlehtori
Jukka Suomela

Jukka Suomela

Associate Professor
T313 Dept. Computer Science
Linh Truong

Linh Truong

Associate Professor
T313 Dept. Computer Science

Related research groups

Latest publications

Efficient load-balancing through distributed token dropping

Sebastian Brandt, Barbara Keller, Joel Rybicki, Jukka Suomela, Jara Uitto 2021 SPAA 2021 - Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures

Small-scale Dynamo in Supernova-driven Interstellar Turbulence

Frederick A. Gent, Mordecai-Mark Mac Low, Maarit J. Käpylä, Nishant K. Singh 2021 Astrophysical Journal Letters

The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained

Axel Brandenburg, Anders Johansen, Philippe Bourdin, Wolfgang Dobler, Wladimir Lyra, Matthias Rheinhardt, Sven Bingert, Nils Haugen, Antony Mee, Frederick Gent, Natalia Babkovskaia, Chao-Chin Yang, Tobias Heinemann, Boris Dintrans, Dhrubaditya Mitra, Simon Candelaresi, Jörn Warnecke, Petri Käpylä, Andreas Schreiber, Piyali Chatterjee, Maarit Käpylä, Xiang-Yu Li, Jonas Krüger, Jørgen Aarnes, Graeme Sarson, Jeffrey Oishi, Jennifer Schober, Raphaël Plasson, Christer Sandin, Ewa Karchniwy, Luiz Rodrigues, Alexander Hubbard, Gustavo Guerrero, Andrew Snodin, Illa Losada, Johannes Pekkilä, Chengeng Qian 2021 JOURNAL OF OPEN SOURCE SOFTWARE

Predicting power outages caused by extratropical storms

Roope Tervo, Ilona Láng, Alexander Jung, Antti Mäkelä 2021 NATURAL HAZARDS AND EARTH SYSTEM SCIENCES

Modeling drug combination effects via latent tensor reconstruction

Tianduanyi Wang, Sandor Szedmak, Haishan Wang, Tero Aittokallio, Tapio Pahikkala, Anna Cichonska, Juho Rousu 2021 Bioinformatics

Investigating global convective dynamos with mean-field models: full spectrum of turbulent effects required

Jörn Warnecke, Matthias Rheinhardt, Mariangela Viviani, Frederick Gent, Simo Tuomisto, Maarit J. Käpylä 2021 Astrophysical Journal Letters

Clustering in Partially Labeled Stochastic Block Models via Total Variation Minimization

Alexander Jung 2020 Conference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
More information on our research in the Research database.
Research database

Related units

Helsinki Institute for Information Technology HIIT (external link)

HIIT is a joint research institute of Aalto University and the University of Helsinki for basic and applied research on information technology.


Finnish Center for Artificial Intelligence FCAI (external link)

Nation-wide competence center for Artificial Intelligence in Finland.

Finnish Center for Artificial Intelligence
PML research gropu at department of computer science, photo Matti Ahlgren

Research areas

Research areas in the Department of Computer Science

Department of Computer Science
Aerial photo of Computer Science Building at Aalto University campus

Department of Computer Science

To foster future science and society.

Artistic depiction of a bright light in space / made by Ray Scipak

School of Science

Science for tomorrow’s technology, innovations and businesses

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