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Ilkka Johannes Kosunen
I started as research assistant 2006 at Helsinki Institute for Information Technology (HIIT), first working in the Fun of Gaming (FUGA) EU-project where my responsibility was to create an emotionally adaptive game. In this work I got to know on very low-level how physiological signals are recorded and analyzed, as I reverse-engineered a recording device not meant for real-time use, and implemented a software platform for developing physiologically adaptive systems (EmoEngine). The engine was then used to develop several emotionally adaptive games ranging from tetris to a first-person shooter game. In addition to developing the software I also participated in planning, running and analysing a large user study. During this period I learned both the theory of psychophysiology as well as state-of-the-art statistical methods for analysing physiological data from leading experts in the field, such as Prof. Niklas Ravaja. After the FUGA project, the gaming research was continued in Tekes funded Emokeitai project that extended the use of biosignals to mobile domains. In collaboration with researchers from Waseda University (Japan), as well as Industrial partners (Nokia, Tieto, Polar etc.) I worked on sonification of physiological signals as well as developing mobile psychophysiological application. In this project I learned to interact with industrial partners as well as how to utilize wide range of equipment (Nokia phones, Polar fitness bands etc.) for physiological computing. Also, I again took part in planning and running large scale user study on using audio biofeedback as well as investigating whether physiological signals can be used in predicting decision making. At this point I was already an expert in data-analysis and was singularly responsible for all data processing and analysis from our experiments. After EmoKeitai I finally finished my Master’s Thesis which had been delayed mainly because I had been busy doing actual research (at the point when I got my Master’s I had already several high quality publications). At this point in 2012 I moved (within HIIT) from Aalto University to University of Helsinki and started my doctoral studies. I also started working on the CEEDs EU-project where my responsibility was, together with a small group of master’s students I was mentoring, to create a synthetic environment that would incorporate physiological recordings as well as eye-tracking. The environment was developed in co-operation with Electrolux to produce a virtual refrigerator that would pro-actively introduce its capabilities to a customer who could interact with it using eye-tracking and natural gestures which were being tracked by a depth camera. Again a user study was successfully ran, data analyzed and results disseminated in a high level conference (UbiComp). In addition to working with new technologies such as eye-trackers, depth-cameras and large screens, in this project I was able to learn a leadership role by mentoring number of master’s students who all not only were able to contribute to the project but also acquire their degrees. During CEEDs the project I also made short research visits to our collaborators in Barcelona and Padova. At this point I was also giving lectures on HCI and research design, instructing small groups and organizing seminars. For example, I planned and ran a semester long seminar where each participant had to plan a physiological computing application as well as a research plan for an user study to demonstrate the feasibility of their design. Thus, the student’s learned both practicalities of physiological computing as well as the basics of experiment research methods. After CEEDs I worked in several projects that explored novel search engines as well as using physiology to automatically detect relevance of keywords and abstracts that users were looking at simply by observing their physiological responses. During this work I was introduced to topics such as recommender systems, reinforcement learning, information retrieval and content annotation. I was also able to observe and learning state-of-the-art machine learning and data mining methods that project members from Academy Professor Samuel Kaski’s Finnish Centre of Excellence in Computational Inference Research COIN group taught me. I took again part in several large scale empirical use studies. This work was done as part of the MindSee EU-project, and allowed me to collaborate with world-class experts in BCI such as Prof. Benjamin Blankertz from TU Berlin. After the information retrieval experiments I started working on a neuroadaptive virtual reality meditation system. The system tracked user’s relaxation and concentration and mapped these into the virtual reality so that user could levitate in the VR simply by relaxing. In this study I was responsible for the real-time analysis of the EEG data as well as collaborating with the developer of the VR environment. As always, an extensive user study was conducted which produced several publications. As the examples above demonstrate, I’m highly qualified in all aspects of doing empirical science in the field of physiological computing. I’m able to design an experiment, develop the necessary platform (whether in laptop, mobile phone or VR), select appropriate physiological signals and process them in real-time, supervise the empirical experiment, do the data-analysis as well as disseminate the results. In my PhD I proposed a systematic view of physiological computing ( I had noticed that the field was highly unorganized) and started to develop (with the help of a group of students) a web repository that would help researchers to share not only their results but also their data and code, as well as to serve as a portal for neurohackers to share their inventions, as well as publicize results for the general public. My research path has been driven by my keen interest in the human psychophysiology and its possibilities for real-time computing systems. In practically all of the studies in my list of publications I’ve been responsible (after discussing with the relevant experts in the field) for implementing the physiological computing system, all the way from reverse-engineering recording devices and processing the signals to creating generic platform for building any type of physiological computing application to the actual applications themselves. I have successfully mentored several master’s students as well as led small groups. I’m often consulted on details of advanced data analysis methods related to psychophysiological recordings. I’m also renown expert in development of physiological experiments: for example, I was once “rented” into Helsinki School of Economics for two months to design and implement a user experiment setup. However, now my aim is to take the next step in my career into position where I could not only design experiment based on projects designed by others but to actively follow my own visions on my own projects. Doing so I hope to be in a position to lead capable graduate and PhD students who I can teach the practicalities of experimental research so I do not have to do everything myself. I also hope to take active part in the academic world as a reviewer, editor and organizer/chair of events.
Researcher Id:
ORCID: 0000-0001-7452-987X