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
Guest Talk tapahtumakuva

Guest talk: José R. Herrero "Profiling parallel applications with Paraver"

Professor José R. Herrero from Universitat Politècnica de Catalunya - BarcelonaTech will give a guest talk at the Department of Computer Science.

Kuva myrskytuhoista Kolilla

Machine learning helps to predict blackouts caused by storms

Train delays related to adverse weather can also be predicted with good quality training data, a new thesis shows.

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

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

Maarit Korpi-Lagg turned her childhood hobbies into a living

As a child, Maarit Korpi-Lagg 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


Moloud Abdar, Mohammad Amin Fahami, Leonardo Rundo, Petia Radeva, Alejandro Frangi, U. Rajendra Acharya, Abbas Khosravi, H. K. Lam, Alexander Jung, Saeid Nahavandi 2022 IEEE Transactions on Industrial Informatics

Local Mending

Alkida Balliu, Juho Hirvonen, Darya Melnyk, Dennis Olivetti, Joel Rybicki, Jukka Suomela 2022 Structural Information and Communication Complexity - 29th International Colloquium, SIROCCO 2022, Proceedings

Sparse Matrix Multiplication in the Low-Bandwidth Model

Chetan Gupta, Juho Hirvonen, Janne H. Korhonen, Jan Studený, Jukka Suomela 2022 SPAA 2022 - Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures

Machine Learning

Alex Jung 2022

Systematic review of computational methods for drug combination prediction

Weikaixin Kong, Gianmarco Midena, Yingjia Chen, Paschalis Athanasiadis, Tianduanyi Wang, Juho Rousu, Liye He, Tero Aittokallio 2022 Computational and Structural Biotechnology Journal

Compressible Test-field Method and Its Application to Shear Dynamos

Maarit J. Käpylä, Matthias Rheinhardt, Axel Brandenburg 2022 The Astrophysical Journal

Topological changes in the magnetic field of LQ Hya during an activity minimum

J. J. Lehtinen, M. J. Käpylä, T. Hackman, O. Kochukhov, T. Willamo, S. C. Marsden, S. V. Jeffers, G. W. Henry, L. Jetsu 2022 Astronomy and Astrophysics

Scalable communication for high-order stencil computations using CUDA-aware MPI

Johannes Pekkilä, Miikka S. Väisälä, Maarit J. Käpylä, Matthias Rheinhardt, Oskar Lappi 2022 PARALLEL COMPUTING

Strain design optimization using reinforcement learning

Maryam Sabzevari, Sandor Szedmak, Merja Penttilä, Paula Jouhten, Juho Rousu 2022 PLoS computational biology
More information on our research in the Research database.
Research database

Related units

Helsinki Institute for Information Technology HIIT (external link)

Collaborative institute for research on information technology.


Finnish Center for Artificial Intelligence FCAI (external link)

International research hub for artificial intelligence

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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