University of Oulu, 2019

Appointment of research projects to Infotech Oulu Institute for a period of 2022 - 2025

The University of Oulu’s strategy strengthens its role as a high-level international science and innovation university that contributes to solving global challenges through the selected focus areas of research. Tackling the identified global challenges requires multidisciplinary approaches and research excellence.
The University of Oulu supports the strategy through evaluation of its research, as well as regular open calls and external evaluation of projects supported by the university's focus institutes.

Infotech Oulu Institute is one of the four strategic focus institutes at the University of Oulu supporting high-quality research, coordinating multidisciplinary research activities and doctoral training. Infotech’s science-based expertise meets global challenges determined in the strategy of the University of Oulu (UO) in the focus area ” Digitalization and smart society” exploring how digitalization can work for everyone. The research topics include sensing and ubiquitous wireless sensor systems, wireless communication, and other novel services and systems. The research targets future information infrastructures and integrates aspects of technology adoption by complex human groups, communities, and societies.

The call for new Infotech research projects for 2022 – 2025 was opened on December 4th, 2020 and closed on February 23rd, 2021. Forty-four applications were submitted in time.

An independent scientific evaluation panel was appointed by the Rector of  the University of Oulu on July 1st, 2021. Contrary to normal practice in the evaluation process of focus institutes, the panel’s site visit to the University of Oulu was not organised because of the COVID-19 pandemic.

The panel evaluated the applications remotely based on criteria used by the Academy of Finland. Four independent external experts made additional reviews of five applications for the support of the panel. The panel members and external experts were informed about the regulations on disqualification and confidentiality according to the regulations of the Academy of Finland in the review guidelines of Infotech project applications. In accepting their assignment, they committed to adhering to the guidelines.

Panel members:
· Professor Danica Kragic Jensfelt (panel Chair), Royal Institute of Technology KTH, Sweden
· Professor Erik Bohlin, Chalmers University of Technology, Sweden
· Professor Kostas Kyriakopoulos, National Technical University of Athens, Greece
· Professor Barbara Malič, Jožef Stefan Institute, Slovenia
· Professor Ralf Müller, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany
· Professor Bernhard Roth, Gottfried Wilhelm Leibniz University Hannover, Germany
· Professor Nicu Sebe, University of Trento, Italy
· Professor Aydın Sezgin, Ruhr-Universität Bochum RUB, Germany

The instructions for review were based on the guidelines of the Academy of Finland. The main criteria in the review were the quality of the research plan, the competence of the applicant(s) and the project’s relevance to the call. In addition, the project PI(s) should be highly recognized in their field of science and have demonstrated ability to gain notable external funding for research.

The evaluation panel analysed the applications and combined the reviews together in August 2021. The panel report to Rector with general recommendations and ranking of applications was submitted on September 2nd, 2021. Each applicant will receive the panel’s review of their own application in September 2021.

On the basis of the recommendations given by the evaluation panel I hereby approve the following 12 research projects to the Infotech Institute for a period of 2022 – 2025:

Responsible PI



Postdoctoral researchers

Doctoral students

Myllylä Teemu


Accurate, Deep Tissue Functional Spectroscopy for a Wide Field of Biomedical Research




Komsa Hannu-



Memristors and Neuromorphic Sensors from Vertically Aligned Layered Material




Juuti Jari


Low-energy High-performance Sensing Materials for Environment Digitalization




LaValle Steven


ViRTIA: Virtual Reality-Based Telepresence through Improved Autonomy




Röning Juha


Safe Biomonitoring by BIOICT Integrated Wearables




Samarakoon Sumudu



Robust and Reliable Delay-Sensitive Communication and Control Co-Design (R2D2)




Zhao Guoying

Towards Secure and Reliable Deep Learning Systems against Adversarial Attacks




Heikkilä Janne


A Framework for General SpatialAI (FRAGES)




Tölli Antti


Immersive Extended Reality Environments with Cache-aided Directional Access




Juntti Markku


Energy-Efficient Wireless Access (EEWA)




Silvén Olli


MAALI: Multisensory automation for assisted living






SmartBAN Enabled Human Vital Sign Measurements (SEHU)




These projects will be targeted for strategic support in the form of doctoral student and postdoctoral researcher positions. The positions are filled according to the University´s HR procedures.

The projects are expected to contribute to joint activities of the Infotech Institute, including organising doctoral training.

Jouko Niinimäki

Taina Pihlajaniemi
Vice Rector - Research



Infotech Oulu projects 2022 - 2025 descriptions:

(in alphabetical order by project leader’s name)

Janne Heikkilä, Li Liu: A Framework for General Spatial AI (FRAGES)

Computer vision has already achieved the level of human vision in certain limited tasks. However, when it comes to more general visual perception that enables interacting with the three-dimensional dynamic environment, machines are still far behind the humans. In the project, we address this problem by proposing a generic framework to enhance and fuse multi- modal sensor data and to convert it to higher-level semantic representations. This framework is expected to facilitate emergence of more advanced spatial AI applications.


Matti Hämäläinen, Jari Hannu: SmartBAN Enabled Human Vital Sign Measurements (SEHU)

This project focuses on developing a seamless and stretchable wearable device for human vital sign measurements. Novel sensing methods allow accurate results and thus, can produce data for better diagnostics. End-user’s willingness to carry seamless devices is much higher than the bulky ones. By adopting and further developing novel ETSI SmartBAN standard for low-power wireless body area network connectivity enables real-time data streams between several wearable devices. Optimized communications and sensing allow lower power consumption, long-lasting battery life and more reliable operations. The research will be carried out at the Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland by Centre for Wireless Communications – Networks and Systems (CWC) and Microelectronics (MIC) groups.


Markku Juntti: Energy-Efficient Wireless Access (EEWA)

Project is carried out in CWC–RT. Digitalization requires pervasive wireless connectivity. To emphasize sustainability, the rapidly increasing data traffic require the energy-efficiency of wireless communications and network operation to improve by about an order of magnitude. The core objective of the project is to develop novel scientific knowledge and engineering solutions to enable energy-efficient physical and link layers with related transceiver and resource allocation technologies for the 6G radio access networks technology. The scope of the project focuses on system level optimization with large antenna arrays applied in below 10 GHz massive multiple-input multiple-output (MIMO) and cell-free system design as well as mmWave bands, which are given a special focus. The research methods include theoretical mathematical modeling of transceivers, cellular network, analysis and optimization, computer simulations on device, link and system level as well as practical experimentation.


Jari Juuti, Yang Bai, Heli Jantunen: Low-energy high-performance sensing materials for environment digitalization

This project focuses on research of piezoceramics made at ultra-low temperatures, paving a way towards energy saving in materials fabrication and enhancement for integration capability. Piezoceramics are widely used in sensors which constitute vital components in modern technologies requiring conversion between mechanical and electrical energy. Piezoceramics need to be manufactured at over 1000 degrees Celsius, consuming a considerable amount of energy and leading to increased emission. This project will overturn 100 years’ history by making piezoceramics at temperatures lower than 350 degrees Celsius, via methodologies  of surface chemistry and ceramic-ceramic composite. The project will be carried out in University of Oulu. Success of this project will not only help to save over 90 % energy used by high temperature sintering in piezoceramics industry, but also stimulate the advancement of novel multi-functional components and electronic integration in smart devices and systems.


Hannu-Pekka Komsa, Krisztian Kordas: Memristors and neuromorphic sensors from vertically aligned layered materials

Emergence of ubiquitous computing entails that advanced information processing capabilities are introduced to the miniaturized, inexpensive, wearable devices and sensors around us. Unfortunately, the power needed for such processing tasks can be excessive for the available power budget, especially in wearable devices. Memristor-based neuromorphic computing paradigm promises to change this.  At Microelectronics Research Unit, University of Oulu, we will fabricate memristor devices using layered materials. By combining experimental characterization and computational modeling, we will study the operating mechanism and use this information to further optimize the memristor performance. Finally, in the context of moving towards digitalization and smart society, we will explore the use of memristors in energy-efficient ubiquitous computing and neuromorphic sensor applications.


Steven LaValle: ViRTIA: Virtual Reality-Based Telepresence through Improved Autonomy

Rapid advances in consumer electronics have led to unprecedented investment into an ecosystem of experiences centered on head mounted displays (HMDs). These devices incorporate cutting edge technologies to bring people experiences that are real, often via panoramic cameras, and virtual, via computer graphics. This proposal addresses a crucial obstacle to the success of this ecosystem: How to automatically compensate for the motions of wide-angle and panoramic cameras, both real and virtual, so that comfort is maximized, immersion or presence is preserved, and cybersickness is minimized. The research is expected to deliver published algorithms for moving real and virtual cameras that dramatically improve human experiences for HMD-based applications such as telepresence, virtual travel, and remote education. It is also expected to produce human perception-based engineering criteria, which advance scientific understanding and would benefit the larger industrial ecosystem.


Teemu Myllylä: Accurate, deep tissue functional spectroscopy for a wide field of biomedical research

The project aims at developing a novel spatially accurate deep tissue imaging technique and a possibility monitor in realtime tissue effects of focussed ultrasound (FUS) and X-ray, particularly in brain therapies. X- ray is extensively used in oncology whereas FUS is a rapidly expanding technology. The non-invasiveness of the FUS makes it particularly attractive in transcranial therapies: neuromodulation, surgery and drug delivery. Moreover, recent pre-clinical studies indicate that disrupting blood brain barrier (BBB) with FUS can also facilitate the removal of the protein accumulations in the brain. However, as a significant shortcoming, there is no accurate monitoring available for BBB disruption, neither for FUS transcranial therapies. The goal is to advance both radiotherapy and FUS by integrating optics-based monitoring into the therapies. The novel approach will radically improve the effectiveness of radiotherapy and the FUS  technique for their current and future clinical use.


Juha Röning, Seppo Vainio, Valerio Izzi, Sylvain Sebert, Ville Pimenoff: Safe biomonitoring by bioICT integrated wereables

Human body fluids, including sweat, contain wealth of nano- and macro sized extracellular vesicles (EVs)  linked to the regulation of human physiology as they transfer key homeostasis-controlling molecules, including  active nucleic acids, proteins and metabolites. EVs offer novel ways to biomonitor diseases underpinning our aim to propose EV-based biomarker scores to predict and study new risk or protective factors to pathological conditions and diseases. We will develop and make use of non- invasive skin patches with future aim to identify and monitor persons at high risk for specific diseases. With the help of biobank/cohort data, AI and machine learning expected to be able to prioritize which markers associate with a risk for targeted diseases, speeding up the selection of EV-shuttled markers. The project shall offer new ways to identify diseases by focusing on EV as bioindicators, monitorable through novel integrated EVs read out wearable technologies. Ultimately, the project will likely lead to the development of innovative prevention and therapeutic technologies paving the way for further BioICT applications.


Sumudu Samarakoon: Robust and Reliable Delay-Sensitive Communication and Control Co-Design (R2D2)

The advancement in 5G and beyond systems has enabled the integration of wireless communication in control systems towards low delay, high reliable, and robust designs. Although these two technologies complement one another, current research is mostly carried out independently focusing on either communication or control aspects preventing the realization of the full potential in wireless networked control systems. In this view, the objective of R2D2 is to deliver a unified framework of communication and control co-design considering (i) strict control requirements, (ii) dynamics of the system, and (iii) limitations in the available communication and computation resources. Towards this, various theoretical and algorithmic solutions will be developed for single- and multi-agent control systems within the project that will be validated on sandbox environments and testbeds. The outputs of the project will be instrumental in enabling different verticals including industrial automation, intelligent transport, digital healthcare, virtual/augmented realty, among many others.


Olli Silvén, Miguel Bordallo López: MAALI: Multisensory automation for assisted living

The MAALI project investigates the creation of an intelligent autonomous multi-sensory stratified system to support assisted living. The project investigates technologies that will aid early diagnosis, and the monitoring activity changes for the ageing people living at home. The objective is to impact the automation of a range of assisted living and healthcare needs by employing pattern recognition across a network of low-cost networked sensors in home environment. The project aims to enhance existing assistive technologies by providing the capability to automatically monitor and reason over activity and vital signs data and communicate these data to support actors in case of emergency. The sensors inform each other about activities in the household, and aim to extract the best possible information at each instant of time by employing signal processing and artificial intelligence methods.


Antti Tölli: Immersive Extended Reality Environments with Cache-aided Directional Access

One of the main 6G drivers is about creating and consuming new virtual or digital twin worlds. To this end, the next step in the evolution of human-computer interfaces will bring forward emerging immersive digital experience applications that submerge users in the 3D digital world and allow them to interact with virtual or digital twin objects. This project uniquely focus on developing cache-aided mmWave-based wireless solutions that will reliably provide seamless high data rates and low latencies for future extended reality applications given the specifics of directional mmWave connectivity. The aim is to provide optimized dynamic cache replacement strategies, such that the content relevant to identified system-wide bottleneck areas is proactively incentivized for storage at user devices. Furthermore, cache-aided multiantenna-based coded content delivery mechanisms are developed to facilitate the extremely high area capacity required by the multi-user immersive experience.


Guoying Zhao: Towards Secure and Reliable Deep Learning Systems against Adversarial Attacks

In recent years, deep learning methods have been widely deployed in a range of vision related tasks such as object detection, segmentation and recognition. However, such methods can be vulnerable to adversarial attacks that subtle perturbations to inputs can result in incorrect decisions. In this research, we attempt to explore the new generation of adversarial attacks, improve adversarial robustness of deep neural networks and establish reliable deep learning systems against adversarial attacks for secure digitalization and smart society. This research is also expected to have a great practical and social impact due to the wide applicability of automatic systems to our daily life. This research includes both theoretical analysis and experimental validations using publicly available datasets.  Mainstream computer vision and machine learning methods will also be investigated. The research will be carried out in the Center for Machine Vision and Signal Analysis, University of Oulu.


Last updated: 9.9.2021