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
Research in Computer Science
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
Linh Truong

Linh Truong

Associate Professor
T313 Dept. Computer Science

Related research groups

Latest publications

New methods for drug synergy prediction : A mini-review

Fatemeh Abbasi, Juho Rousu 2024 Current Opinion in Structural Biology

Protein function prediction through multi-view multi-label latent tensor reconstruction

Robert Ebo Armah-Sekum, Sandor Szedmak, Juho Rousu 2024 BMC Bioinformatics

Learning symmetry-aware atom mapping in chemical reactions through deep graph matching

Maryam Astero, Juho Rousu 2024 JOURNAL OF CHEMINFORMATICS

Distributed half-integral matching and beyond

Sameep Dahal, Jukka Suomela 2024 Theoretical Computer Science

Transition from small-scale to large-scale dynamo in a supernova-driven, multiphase medium

Frederick A. Gent, Mordecai-Mark Mac Low, Maarit J. Korpi-Lagg 2024 The Astrophysical Journal

From convective stellar dynamo simulations to Zeeman-Doppler images

T. Hackman, O. Kochukhov, M. Viviani, J. Warnecke, M. J. Korpi-Lagg, J. J. Lehtinen 2024 Astronomy and Astrophysics

Socio-economic pandemic modelling : case of Spain

Jan E. Snellman, Nadia L. Barreiro, Rafael A. Barrio, Cecilia I. Ventura, Tzipe Govezensky, Kimmo K. Kaski, Maarit J. Korpi-Lagg 2024 Scientific Reports

From intangible to tangible : The role of big data and machine learning in walkability studies

Jun Yang, Pia Fricker, Alexander Jung 2024 Computers, Environment and Urban Systems


Moloud Abdar, Mohammad Amin Fahami, Leonardo Rundo, Petia Radeva, Alejandro Frangi, U. Rajendra Acharya, Abbas Khosravi, H. K. Lam, Alexander Jung, Saeid Nahavandi 2023 IEEE Transactions on Industrial Informatics

Locality in Online, Dynamic, Sequential, and Distributed Graph Algorithms

Amirreza Akbari, Navid Eslami, Henrik Lievonen, Darya Melnyk, Joona Särkijärvi, Jukka Suomela 2023 50th International Colloquium on Automata, Languages, and Programming, ICALP 2023
More information on our research in the Aalto research portal.
Research portal
PML research gropu at department of computer science, photo Matti Ahlgren

Research in Computer Science

Research in the Department of Computer Science

Department of Computer Science
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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