Lauri is a guy for science and mountains. He has years of experience in neuroscience and data science. He has PhD in studying cognition and information processing. His PhD is about psychophysiological measures of stress and performance. He has since worked in business in data scientist roles which provide foundation for focusing what’s relevant. Both sides, on the other hand grasping human mind, and on the other the mathematical methods, are the key for unique skillset that allow implementing overarching solutions, manage the bigger picture, and generate valuable insights.
Pablo is currently pursuing his Master's degree in the Faculty of Educational Sciences. In Chile, he completed his teaching degree and went on to teach high-school students in the fields of technology and physics. His research interests lies in understanding the use and role of technology within educational and learning environments. Interested in both quantitative and qualitative methods, he is currently exploring the pedagogical applications of Large Language Models in Higher Education.
Elizaveta is a PhD researcher on the CLIC doctoral program. She obtained her Master’s degree in Cognitive Psychology in 2020 from National Research University Higher School of Economics (NRU HSE), Moscow, Russia. Her current PhD project involves studying neural correlates of attention-deficit and hyperactivity disorder (ADHD) in adults with an ultimate aim to translate theoretical findings into clinical practice, in particular to develop new neurofeedback treatment protocols to target identified correlates of adult ADHD.
Natalia joined the lab in 2021 as a postdoctoral researcher. She completed her PhD and MA in Kyushu University (Japan) in the area of perceptual psychology and psychophysics, and her specialist studies (BA+) in Saint Petersburg University of Aerospace Instrumentation with an engineering degree in audiovisual equipment. She has solid background in audiovisual perception and experience in experimental design with audio and/or visual materials. Her current projects are focused on learning and communication.
Andrei is a brain researcher currently working at the intersection of neuroscience, cognitive science, and learning. He obtained his PhD in Medicine from the University of Helsinki in 2020 and he completed his postdoctoral research at Beth Israel Deaconess Medical Center Harvard Medical School in 2023. In his studies, he uses neurocognitive, electrophysiological, neuroimaging and brain stimulation methods. He has contributed to a range of clinical and basic research fields including spinal cord injury, delirium, neuroplasticity, emotion, attention, and creativity.
Guang started as a doctoral researcher at the Faculty of Educational Sciences in 2022. He completed his bachelor and master studies in clinical medicine at Liaoning university of traditional Chinese medicine (China), and completed his 1st doctoral study in pre-clinical medicine at Beijing University of Chinese medicine (China), focusing on nowcasting influenza outbreak in data-driven approaches. In the past 4 years, he had been working as a lecturer in medical statistics in Beijing City University. He is currently working on the GUESSED project, developing models that help skiers make expert-level decisions in avalanche terrain.
Evgenii is currently a doctoral researcher in the CLIC program, having joined the group in 2023. With a solid foundation in computer science, he specializes in applying machine learning techniques to the analysis of biosignals. He earned his master's degree in Intellectual Vision through the PSRS Erasmus Mundus Joint Master Degree program, a collaborative effort among three European universities. Prior to his doctoral studies, he gained experience working in R&D as a machine learning researcher. In his current research, Evgenii focuses on physiological signal processing and the computational modeling of human behavior, aiming to gain deeper insights into the phenomena of human learning.
Tuisku is a doctoral researcher in cognitive science, and the focus of his research is modelling learning in dynamic tasks with uncertainty. He has a strong background in experimental design and data analysis, and is familiar with a range of methods, from eye-tracking to EEG and other physiological signals.
Hanna is doctoral researcher whose project aims to elucidate the role of neural synchrony in collaborative learning through causal experimental manipulation using transcranial alternating current stimulation. She has a Master’s degree in cognitive science, with a thesis on Empathy and EDA synchrony in VR collaboration, and a rich study history from diverse fields, e.g., statistics, molecular biology, experimental psychology, human-computer interaction and group processes. Hanna believes think that science at its best adopts theories from related fields to provide reliable, holistic descriptions of the world.