Research of the Computer Science Department is divided into the following core research areas.
Algorithms, Logic & Computation
The systematic design and analysis of complex, yet efficient and reliable computational systems is at the core of modern computer science. New challenges arise continually at the one end from the emergence of global computing infrastructures such as wireless networks, cloud computing and the Internet of Things, and at the other end from the demands of solving difficult computational problems in science and engineering. Work at the department in this core area covers the following research themes: modern algorithmics, computational logic and formal methods, cryptography and data security, computer-aided system design and and cyber-physical systems.
Complex Systems is a transdisciplinary research area that builds on statistical physics, computer science, data science, and applied mathematics. Complex systems consist of large numbers of interacting elements, with stochastic interactions and non-trivial interaction structure. They are often outcomes of evolutionary processes, and display rich structures and dynamical phenomena from self-organization to phase transitions. Complex systems are found at all scales in Nature, from the complex machinery operating inside our cells to the human brain and to various aspects of human sociality and the networked social organization of humans. Intriguingly, these systems are often shaped by forces of similar nature, and therefore understanding one system may provide surprising insights into entirely different domains.
Data Science and Big Data
We live in the information age, where a deluge of data is being generated by human activity, scientific data collection processes, business transactions, and adoption of new technologies. Distilling the knowledge contained in such big volumes of data has the potential to transform science, technology, business, and arts, and it can revolutionize how the human society is organized and how it functions. Data science is a new discipline that has emerged and it has the objective to provide the underlying theory and the necessary tools to cope with the data revolution.
The Digital Health subarea is based in Aalto on combining the world-class research activities in ICT by Aalto and in medicine and biology by the University of Helsinki and the research of partners, such as the Helsinki and Uusimaa Hospital District (HUS). By this combination, we are developing a globally leading research cluster.
Distributed Systems, Mobile Computing and Security
The research area spans from mobile networking and communications to distributed computing and big data. We envision the accelerated convergence of mobile and cloud computing technologies, and the maturation of big data in the coming years. We are extending our current research on energy-efficient mobile computing, distributed cloud computing, and the Internet of Things. The goal of the Secure Systems research group is to create new technologies and design analysis methods for the development of secure computing and communication systems.
Human-Computer Interaction, Games, Graphics and Audio
The interplay of humans and technology is of central importance in this research area. Our strong basic research on the underlying techniques has applications in several fields. One such area is computer games where our research on interaction techniques, game concepts and computer graphics enables development of future games. In addition to virtual worlds, we aim to enhance the real world as well. For example, our research on acoustics aims to revolutionize the field of acoustic design.
Internet of Things
The advances in sensors and actuators, embedded computing, wireless and wired networking, and cloud technologies are giving unprecedented opportunities to collect data from an ever wider range of products and related services reflecting their actual use, to analyze the data to reveal opportunities for improved operations and added value, and deploy the results back to the source for improved operation. The terms ”Internet of Things” and ”Internet of Everything” cover conveniently these developments.
Machine Learning, Data Mining & Probabilistic Modeling
The faculty covers the key topics of Bayesian inference, data mining, deep learning, graphical models, kernel methods, neural networks, probabilistic modelling, and statistical machine learning. Strong applications include bioinformatics, computational astrophysics, computational biology, computational medicine, data science, human-computer interaction, information retrieval, information visualization, and neuroinformatics.
Security and Privacy
The increasing digitalization and connectivity brings security and privacy concerns to the forefront. In this research area, we study such concerns and develop new technologies that can ensure security and privacy. Our work ranges from analyzing and designing fundamental cryptographic techniques to building secure systems and formally verifying their security and privacy guarantees.
Software and Service Engineering
In software engineering, we study the activities and processes that create artifacts, as well as the actual artifacts created. In software service engineering, we go one step further to study commercial activities, where the value chains and business models aim at producing, buying and selling products or services in which software is an essential part of the value creation and merchandise.
Software Systems and Technologies
The broad challenge of Software Systems and Technology is to develop reliable and efficient methods and tools to build and maintain software that works according to its functional requirements, i.e. correctly, and in addition, satisfies a number of non-functional properties, like dependability. Our research covers novel methods and tools to create high quality computer programmes, as well as studies aimed at designing key platform components for various modern software systems.