Discover more
Tampere University www.tuni.fi
BioMediTech Institute www.biomeditech.fi
Tampere University Faculty of Medicine and Health Technology www.tuni.fi/met/en/
Hyttinen Laboratory — Computational Biophysics and Imaging Group research.tuni.fi/cbig
TAU was created on 1 January 2019 by the merger of Tampere University of Technology and University of Tampere. The multidisciplinary, foundation-based Tampere University is the second-largest university in Finland. TAU conducts scientific research in technology, health and society. Together with Tampere University of Applied Sciences, TAU constitutes the Tampere higher education community comprising approximately 30000 students, 330 professors and 4400 employees.
CBIG is a part of the new Faculty of Medicine and Health Technology that combines medicine, biotechnology and biomedical engineering. The mission of CBIG is to deliver new knowledge and methods for the future personalized medicine. We study cellular biophysics, especially electrophysiology and biomechanics of neuronal and cardiac functions using microscopy, bioimpedance, patch clamp, and multichannel microelectrode arrays (MEAs). We develop optical, electric and X-ray tomography, and single plane illumination microscopy for tissue engineering, in vitro disease and drug modelling, and future 3D histology, providing also structural information for our in vitro disease and drug modelling. We develop in silico models to decipher cellular biophysics in neuronal networks and cardiomyocytes, and integrate in silico and in vitro human induced stem cells for personalized medicine and drug screening platforms.
CBIG is also a part of the Academy of Finland Centre of Excellence in Body-on Chip Research.
This is the TUT team of the project, click on the name to expand the bio:
https://www.linkedin.com/in/jari-hyttinen-3864a14
https://scholar.google.com/citations?user=YKuQ-YsAAAAJ
https://orcid.org/0000-0003-1850-3055
https://twitter.com/jariakhyttinen
I am a Full Professor and the Head of the BioMediTech unit of the Faculty of Medicine and Health Technology. My research group CBIG develops novel computer simulations (in silico) based on cellular biophysics, and in vitro electrophysiology and 3D imaging methods for the future personalized medicine. I have served as the Chair (2001–2004) of the Finnish Society for Medical Physics and Medical Engineering and the President (2015–2017) of the European Alliance of Medical and Biological Engineering and Science (EAMBES), and I am an EAMBES Fellow. A number of my patents have been transferred to companies, including to Injeq Ltd., which I co-founded.
https://www.linkedin.com/in/tanskanen/
https://scholar.google.fi/citations?user=lmalQboAAAAJ
https://orcid.org/0000-0001-7183-318X
I hold a DSc (Tech) in Signal Processing and I am Adj. Prof. in Biomedical Signal Processing. My HERMES tasks include microelectrode array (MEA) signal analysis method development, in vitro MEA electrophysiology, and project management. My background is in telecom and life science signal engineering. I am interested in the analysis of neuronal network function and signal processing methods to extract more information from biomedical measurements. To advocate proper use of information and communications technology (ICT) for health, I serve as a volunteer expert in the IEEE European Public Policy Committee Working Group on ICT.
I am a PhD student, and I hold a MSc degree in Biotechnology, with expertise in cell technology. My previous work includes in vitro neuronal microelectrode array (MEA) experiments, neuronal stimulations, and 3D human induced pluripotent stem cell and human neural stem cell differentiation. My HERMES tasks include hippocampal organoid characterization with fluorescence imaging, as well as assessing in vitro neuronal electrophysiological behavior with MEAs.
I am currently a postdoctoral fellow at TAU. My work is on statistical signal processing, nonlinear time series analysis, computational modelling, and machine learning with applications in functional neuroimaging (MEG and EEG) as well as MEA signal analysis.