Department of Computer Science

Large-scale Computing and Data Analysis

Large-scale distributed/parallel systems and big data analysis and management.

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

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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

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People

Rohit Babbar

Rohit Babbar

Assistant professor
Jorma Laaksonen

Jorma Laaksonen

Senior University Lecturer
T313 Dept. Computer Science
Riku Linna

Riku Linna

Senior University Lecturer
Department of Computer Science
Jukka Suomela

Jukka Suomela

Associate professor
T313 Dept. Computer Science
Linh Truong

Linh Truong

Associate professor
T313 Dept. Computer Science

Latest publications

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
More information on our research in the Research database.
Research database

Research areas

Research areas in department of computer science

Department of Computer Science
PML Research Group in Department of Computer Science

Department of Computer Science

Modern 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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