Department of Electrical Engineering and Automation

Our research and innovation efforts on industrial and power electronics are taking place at three complementary levels: algorithms, methods, and applications.

The mission of the Renewable Energies for Power Systems group is to pursue groundbreaking work in the generation, transmission, distribution, management, and consumption of electricity.

Electric drives play an important role, e.g., in a large number of industrial applications, electric and hybrid vehicles, elevators, and robotics. Electric drives are systems where the electric motors or generators are controlled by power-electronic converters (such as a frequency converter).

The focus areas of research in power systems and high voltage engineering are distribution networks, their system solutions and reliability engineering, power system components´ load capacity and ageing, control and monitoring systems including computer applications, automation and communication solutions, end use analysis and power quality.

Lighting research group’s fundamental goal is to advance the research and education of illumination engineering and electrical building services.

The aim of the group is to advance research and teaching within smart buildings.

Advancing research in the interdisciplinary field of electromechanics at three different aspects: theoretical, numerical, and experimental.

The research interest of the Nonlinear Systems and Control group lies in the intersection of Control theory and Machine Learning: We aim to synergistically combine tools from nonlinear systems, stability theory, robust & optimal control along with machine learning and optimization techniques, to create systems with provable guarantees on safety and performance.

The cyber-physical systems group develops novel machine learning and control methods for networked multi-agent systems.

The research done by the automatic control group is based on a firm knowledge of system theory, control engineering, simulation methods, optimisation methods, numerical algorithms, and so forth.

The group's research focuses on heavy duty semiautonomous machines and autonomous mobile robotics, mainly in agriculture and forestry.

The group's research focuses on the engineering of software-intensive automation systems.

Intelligent Robotics group performs research in robotics, computer vision and machine learning.

The robotic instruments group develops miniaturized robotics and fine objects manipulation technologies.

The Aalto Robot Learning (RL) research group operates in the intersection of artificial intelligence and robotics. In particular, we focus on reinforcement learning, robotic manipulation, decision making under partial observability, imitation learning, and decision making in multi-agent systems.

The Mobile Robotics research group is led by Assistant Professor Tomasz Kucner.

We are now witnessing an explosion in networked systems: everything is connected and massive amounts of devices are required to be coordinated.

The research in the Electronics integration and reliability unit is strongly multidisciplinary by nature. Our knowhow is based on materials science and, especially, on the understanding of interfacial phenomena between materials in heterogeneous systems.

Bionic and Rehabilitation Engineering (BaRE) research group investigates engineering techniques for human-machine interfacing in order to support, augment and rehabilitate human motor function. Through advancements in basic physiology, motor control, and biomechanics, we tailor novel biosensing and control approaches, as well as design methodologies in order to push the boundaries of current state-of-the-art bionic limbs, exoskeletons and rehabilitation robots.

The group develops computational methods for multi-physics modelling of the human body.

Microsystems technology is a truly multidisciplinary research area. It is based on physical and analytical chemistry, biology, microelectronics, materials science, physics and biomedical technology.

Research of the group focuses on sensor informatics, adaptive signal processing, data fusion systems, and machine learning (including AI), especially for medical applications. Other applications include smartphone sensor fusion, robotics, positioning systems, target tracking, biomedical imaging, and many other indirectly measured time-varying systems.

The Master’s Programme in Automation and Electrical Engineering prepares its graduates to perform in the intersection between hardware and software, ranging from the fields of Electrical Engineering and Energy sectors to Biomedical Engineering, Control Engineering and Robotics. Drawing from extensive research and fundamental theories in mathematical and natural sciences, the programme focuses on the applicable side of technologies, including topics like Autonomous Systems, Health Technology, Smart Grids and Renewable Energy Solutions.

Doctoral education will prepare you for the most demanding expert positions in your field in the academia, companies and public administration. Start here if you’re interested in doctoral studies!

Maarintie 8

Otakaari 3 & Rakentajanaukio 2

Tietotie 3

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The Aalto Factory of the Future is an infrastructure to support innovation in future industrial automation, industry 4.0 & 5.0 and beyond. It allows test and trials of advanced technologies, such as future wireless communication (5G / Wifi6 and beyond) in industry.