Emilia Happonen ([email protected])
I am a postdoctoral researcher in Pharmaceutical Physics group at the Department of Technical Physics. I have graduated as Master of Science from Medical Physics in June 2019. I had my doctoral defense in January 2025. The topic of my doctoral research was photothermal therapy with black porous silicon nanoparticles for targeted cancer treatment. Nowadays, I am studying new mRNA delivery vehicles for efficient cell transfection.
Emmi Kärkkäinen ([email protected])
I’m currently studying the role of small non-coding RNAs in breast cancer.
Hamid Behravan ([email protected])
Senior researcher in artificial intelligence (AI) technology in breast cancer personalized medicine
Leading the AI group in Institute of Clinical Medicine, Pathology, and Forensic Medicine, University of Eastern Finland
Dr. Hamid Behravan has earned his master’s degree in 2013 and his doctorate in 2016 both in Computer Science from University of Eastern Finland. From 2017, he has been working as a senior researcher at the same university with topics related to AI and cancer. His multi-disciplinary research has attracted over 500k Euro grants from Cancer Society of Finland in 2018 and 2020, and from the European regional development fund. Alongside his own research, Dr. Behravan supervises PhD students. His research team develops innovative explainable AI-based methods to predict the breast cancer risk and the patient outcome using genetics, clinical, and imaging data.
Ina Pöhner ([email protected])
Early during my scientific career, I focused on studying protein-protein interactions by computational methods. During my PhD, I shifted my focus to protein-small molecule interactions and their modulation in the context of computer-aided drug design for neglected tropical diseases. As a passionate Linux-user and administrator, I moved on to dive into aspects of scientific databases, data management, biocuration, and FAIR data (data that is Findable, Accessible, Interoperable, and Reusable).
My research at UEF finally connects all the dots: I currently study various anti-bacterial, anti-viral, anti-protozoal, and anti-cancer targets, utilizing powerful combinations of computer-aided drug discovery and modeling techniques, programming, databases, and artificial intelligence (AI). My research focuses primarily on data-intensive drug discovery problems and the application of AI in drug discovery pipelines. For example, my recent projects involved several semi-automated modeling and docking studies for hundreds of target candidates drawn from Omics-level datasets and AI-accelerated billion-scale virtual screening efforts.
Given its data-intensive nature, my research heavily relies on high-performance computing resources and the Finnish supercomputers hosted by CSC – IT Center for Science. As a CSC Scientific Computing Ambassador for UEF, I act as a bridge between UEF’s researchers and CSC experts and aim to support other UEFians in making the most of CSC’s services and resources – Whether you would like to learn more about how you can utilize CSC super- and cloud computing resources in your research, get support for data management, or join some of the various courses and training opportunities offered by CSC, feel free to reach out!
Jarjish Rahaman ([email protected])
I am a doctoral researcher, and my Ph.D. thesis is titled “Modelling and Image Reconstruction for Smart Diffuse Optical Tomography”. Diffuse Optical Tomography (DOT) is an imaging technique for studying biological structures using visible and near-infrared light. It has potential applications in medicine, such as functional brain studies, breast cancer imaging, and small animal imaging.
I work in a MSCA-DN network CONcISE, where the aim is to develop data-efficient and quality-oriented techniques for biomedical optical imaging. My research focuses on DOT, where I develop modeling and inverse problem methodologies for a SMART-DOT system. My research involves the development of a light transport model, formulation of inverse problem solutions, and collaboration with fellow researchers within the network.
Jarkko Rautio ([email protected])
My research is focused on the chemistry-based methods, especially prodrugs, in drug delivery and targeting. Much of the research is currently focusing on exploiting the body’s natural mechanisms for transporting nutrients, the LAT1 and GLUT1 proteins, for targeted drug delivery across the blood-brain barrier (BBB) and cancer cells that express these transporters.
Jiajia Wang ([email protected])
I aim to deepen the understanding of the mechanism of interaction between nanoparticles and immune cells, improve the antigen delivery efficiency for immunotherapy, and address the challenges of poor cancer targeting, low therapy efficiency, and the inability to treat cancer metastasis with biomimetic nanoparticles, which are carried out by coating the nanoparticles with cancer cell membranes.
Jonna Kangasniemi ([email protected])
I am doing a PhD thesis titled “Utilising the radiative transfer equation in optical tomography”. Diffuse optical tomography uses visible or near-infrared light to interrogate the internal properties of biological tissues. The technique has potential for providing functional and structural information of biological targets with applications for example in imaging breast cancer, monitoring treatments, functional brain studies, monitoring infant brain oxygenation level, and small animal studies.
Image reconstruction problem in diffuse optical tomography is a highly ill-posed inverse problem. Ill-posedness means that even small errors in modelling or measurements can lead to large errors in reconstructions. In my thesis, I develop numerical methods for the radiative transfer equation to be applied in diffuse optical tomography.
Jorma Palvimo ([email protected])
Our research builds on our firm expertise in the steroid signaling and transcriptional regulation and our pioneering work on the SUMOylation of transcription factors and chromatin. Our current major goals are to:
– Identify the chromatin-bound proteins associated with the androgen receptor (AR) and the glucocorticoid receptor (GR) and reveal the role of SUMOylation in these associations.
– Discover novel means to target the AR and GR in castration resistant prostate cancer.
– Reveal the chromatin targets and mechanisms by which SUMOylation regulates gene networks and chromatin structure in cellular plasticity.
To address these aims, we will use cutting-edge genome- and proteome-wide tools, including GRO-seq, ChIP-seq, ChIP-SICAP and Turbo-ID proximity labeling, with human prostate cancer cell lines, mesenchymal stem cells and reprogrammable somatic cells as our main model systems.
We anticipate that our systemic studies and studies will provide us with novel leads for targeting steroid receptors. We also believe that our innovative and systematic approaches with multitalented research collaboration will provide us with novel SUMOylation targets and significant discoveries of the mechanisms by which SUMOylation regulates cellular plasticity and homeostasis. The results are likely to have translational potential in regenerative medicine and drug discovery for diseases, such as cancer.