The Team

Andrea Ganna - Team Lead

Andrea is an Associate Professor at FIMM and HiLIFE and a research associate at Harvard Medical School and Massachusetts General Hospital. Previously he did his post-doc at the Analytical and Translation Genetic Unit at Massachusetts General Hospital/Harvard Medical School/Broad Institute and his PhD at Karolinska Institute. His research interests lie at the intersection between epidemiology, genetics and statistics. His research vision is to integrate genetic data and information from electronic health record/national health registries to enhance early detection of common diseases and enable more effective public health interventions. Andrea is the founder of Real World Genetics Oy.

Tatiana Cajuso - Senior Scientist

Tatiana Cajuso joins the lab as a Senior Researcher after completing a postdoctoral fellowship at the Dana-Farber Cancer Institute, where she investigated the genetic mechanisms underlying colorectal cancer progression. Dr. Cajuso earned her Ph.D. from the University of Helsinki, specializing in colorectal cancer genetics and their associations with clinical and molecular features.
Her research integrates multiomics approaches, advanced genomic technologies, and clinical data, with a strong focus on understanding disease predisposition and onset. Ultimately, her goal is to translate these insights into improved patient care and clinical outcomes.

Tuomo Hartonen – Post-doc

Tuomo is a post-doctoral researcher in the Data Science and Genetic Epidemiology lab at FIMM, University of Helsinki working in the INTERVENE-EU project, focusing specifically in applying machine learning and data science methods to harness the information contained in the electronic health records (EHR) and national registries. He is interested in developing new ways to improve disease diagnosis and healthcare resource allocation by utilizing registry and biobank data. Tuomo did his PhD at the laboratory of processor Jussi Taipale at University of Helsinki and University of Cambridge, during which he has been developing methods for analyzing data from high-throughput genomics experiments, lately focusing especially in applying deep learning to determine the sequence determinants of human enhancers and promoters. He has completed master's degrees both in theoretical physics and in translational medicine. Tuomo has previously worked with analysis and modeling of different types of "Big Data" ranging from predicting contacts in folded proteins to analyzing patterns in human mobility from smartphone data.

Pekka Vartiainen - Post-doc

Pekka is a resident doctor in pediatrics and an MD-PhD from University of Helsinki. In his PhD, he studied the health-related quality of life (HRQoL) measurement in capturing treatment effectiveness and the burden of disease in patients with chronic pain. Pekka is also involved in projects of HRQoL measurement and interested in improving the MD education in Finnish universities. As a resident doctor, he has worked in two pediatric hospitals and in primary care. At the DSGE lab, he is working with the FinRegistry data and aiming to model the hospitalization in small children infected with respiratory syncytial virus (RSV). The project ultimately aims for better and cost-effective targeting of novel RSV immunization methods.

Zhiyu Yang - Post-doc

Zhiyu is joining the lab as a post-doctoral researcher after finishing her PhD at Purdue University, USA, focusing on genetics of psychiatric diseases. She is interested in applying different computational and statistical methods to biological data to understand the etiology of human diseases.

She will be working on the INTERVENE-EU project. She hopes her work can help with narrowing the gap between lab discoveries and clinical applications.

Sebastian May-Wilson - Post-doc

Sebastian is a post-doctoral researcher in the DSGE lab working on conducting a GWAS of healthcare costs with the multinational GenCOST consortium. This project aims to discover the genetic variation involved in the increasing costs of global healthcare and expand upon existing work in UK Biobank and FinRegistry. Prior to working at the FIMM institute, Sebastian conducted a Masters in Research in the field of molecular genetics at the University of Glasgow, and a PhD in Precision Medicine at the University of Edinburgh. His PhD was primarily focused on developing a novel computational method of analysing biological pathways and their relationship with complex genetic traits (PathWAS). His research interests are largely focused around population genetics and their involvement in global health, including elements of multi-omics, epigenetics and their incorporation with bioinformatics.

Kristina Zguro - Post-doc

Kristina is joining the DSGE lab as a post-doctoral researcher after completing her Ph.D. studies in Genetics, Oncology and Clinical Medicine at the University of Siena. Throughout her doctoral journey, she closely collaborated with the Medical Genetics Unit, focusing extensively on whole-exome sequencing data analysis to identify novel genetic determinants of COVID-19 severity and investigate the clinical variability observed among patients with rare diseases.
Excited to explore new frontiers, Kristina will be now working on cutting-edge research at the intersection of human genetics and economics.

Zhijian Yang - Post-doc

Zhijian is a postdoctoral researcher in the DSGE lab at FIMM. He earned his PhD in statistical genetics from Sun Yat-sen University, China in 2024. His work focuses on developing statistical methods and analyzing genetic data, such as GWAS data and QTL data, to understand the genetic basis of human complex traits and diseases. During his PhD, he uncovered genetic insights into the coronavirus receptor ACE2 protein and identified potential proteins linked to various diseases and human behaviors. In the lab, he is exploring multi-omics data from the FinnGen cohort, focusing on 'extreme' individuals, to investigate the genetic mechanisms underlying psychiatric disorders.

Rodos Rodosthenous - Research coordinator

Rodos is a Molecular Biologist with extensive expertise in Molecular Epidemiology and Biomarker Development. He has a doctoral degree from Harvard University (T.H. Chan School of Public Health) followed by a post-doctoral training as an American Heart Association Fellow at Massachusetts General Hospital and Harvard Medical School. Before joining the DSGE Lab, Rodos worked as a Scientific Consultant in a health-tech/biotech company.

As a member of the DSGE Lab, Rodos will be involved in development projects related to the Finnish national studies FinnGen and FinnRegistry.

Anne Carson – Project coordinator

Anne is a Project Coordinator for the DSGE lab and the INTERVENE-EU Project. Before joining FIMM, Anne worked at the Department of Human Genetics and Pediatrics at University of California, Los Angeles, in various capacities. She has years of experience in research administration and business service management on the departmental level.

Leena Viiri – Research coordinator

Leena is working on an exciting study that aims to understand the value of AI and genetic data in identifying individuals with abnormal lab values. Leena is a molecular biologist and she has worked as a post-doctoral researcher in the area of Cardiovascular disease both in Finland and in the UK. Previously, she worked at Tampere University in the center of Excellence Body-on-Chip project, where her work focused on developing a 3D in vitro liver model from human-derived induced pluripotent stem cells (iPSCs). Just before joining the DSGE lab, Leena worked at the Finnish Clinical Biobank Tampere as a service coordinator.

Feiyi Wang - PhD candidate

Feiyi completed her master degree in Data Science at Worcester Polytechnic Institute in MA, USA. Upon graduation, she worked as an oncology data scientist in pharmaceutical industry. She was also a research fellow at Dana-Farber Cancer Institute, working on patient pathway extraction and clinical analytics platform development using machine learning and NLP techniques. During her Ph.D. study, she is interested in building novel multimodal deep learning models for disease subtype classification and personalized treatment identification with a utilization of multi-omics data, clinical data and medical imaging data.

Lisa Eick - PhD candidate

At the beginning of her bachelor's degree, Lisa focused exclusively on biological questions and how they can be researched in the wetlab. Lisa's complementary studies in computer science, in addition to her master's degree in biomedical sciences at the University of Marburg, sparked her interest in the area between biology and computer science. After her bioinformatics master's thesis, Lisa wanted to continue working in this field.
Therefore, she is interested in applying machine learning algorithms to biological Big Data as part of her PhD.

Essi Viippola - PhD candidate

Essi has graduated from the University of Oulu with a master's degree in statistics. Before joining the DSGELab, she worked as a data scientist and project manager at an ICT company. She has a broad interest in data-related topics, and she's particularly interested in interpretable machine learning. At the DSGELab she will be working on applying statistical methods and machine/deep learning to electronic health records data.

Jakob German – PhD candidate

As the youngest ever graduated pharmacist in German history, Jakob completed his education from the Freie Universität, Berlin.

During and after his studies, he collected valuable experience in the pharmaceutical industry and business.
Having a passion for people's health, he set himself the goal to accelerate developments in health care.
With his constant curiosity and thirst for intellectually demanding challenges, he developed a strong interest in data-related topics and applying computational methods to medical data.

As a PhD candidate and EWSC Fellow of the Broad Institute of MIT and Harvard, Jakob is currently working on the emulation of randomized controlled trials (RCTs) with real-world data (RWD) and investigating multiomics enrichment strategies to improve study designs and advance the implementation of genetics in clinical decision making.

Kira Detrois - Bioinformatician

Kira is currently doing her Master's in Life Science Informatics at the University of Helsinki with a focus on Biostatistics. She holds a bachelor's degree in Applied Computer Science from the University of Göttingen. Already at the start of her Bachelor's, she was interested in applying her skills to biomedical research. This interest was strengthened by her thesis at the Max Planck Institute for Biophysical Chemistry in Göttingen where she worked on connecting trans-eQTLs to complex diseases. She is particularly interested in improving health care and life quality through early and effective detection and intervention of diseases. At the DSGE Lab, she will be working on the INTERVENE project.

Matteo Ferro - Biostatistician

Matteo is a Biostatistics graduate from the University of Milano-Bicocca. He wrote his thesis entitled "Clustered Statin Adherence Trajectories:A Study on Disease Onset" working with the help of DSGE lab and using Finregistry's medication purchase datasets. His interests range from longitudinal and survival analysis to modern techniques like deep learning, all to be applied to real-world health data.

Alexandra Prinz - MD-PhD candidate

Alexandra is an MD-PhD student at the University of Helsinki and an M.Sc. (Tech.) graduate from Aalto University. Her passion lies in working at the intersection of medicine and technology, focusing on leveraging AI and large-scale health data to study common preventable diseases, particularly in the field of stroke neurology. Before joining the DSGE Lab, Alexandra has gained experience from working in neuroscience and medical research, startups, and tech industry.

Andrea Corbetta - visiting PhD student

Andrea graduated in Biostatistics from the University of Milano-Bicocca. For his master’s thesis, he has been a visiting researcher at FIMM in DSGE Lab. He worked on the genetic-environmental determinants of drug adherence and the COVID19-HGI project. He is now a PhD student at the Polytechnic University of Milan and Human Technopole in the Health Data Science Center. He is working on expanding ML and statistical methods in both Finnish and Italian health registries.

Chiara Caime – Visiting PhD student

Chiara is a PhD student in the Molecular and Translational Medicine Doctoral Program (DIMET) at the University of Milano-Bicocca, within the School of Medicine and Surgery. Her research focuses on medical genetics and epigenetics, specifically in relation to autoimmune liver diseases such as Primary Biliary Cholangitis (PBC), Primary Sclerosing Cholangitis (PSC), and Autoimmune Hepatitis (AIH). In addition to her academic work, Chiara is also a scientific visitor at the Population & Medical Genomics Research Centre of the Human Technopole Foundation. Here, she is involved in advanced genomics and immune-mediated diseases. Her research aims to deepen our understanding of how epigenetic mechanisms influence disease development, which is crucial for advancing precision medicine. At the DSGE lab, Chiara is working to study the correlation mosaic chromosomal alterations (mCAs) and the development of liver diseases.

Daniela Fusco - Visiting PhD student

Daniela is a PhD student in AI for Health and Life Sciences at the University of Turin in Italy. Her research focuses on understanding the molecular mechanisms underlying the genetic correlation between obesity and brain morphology. At DSGE lab, she is working with proteomic data to explore the environmental impact on genetic regulation in proteomics.

Meihui Zhu - Master Student

Meihui is currently a second-year master’s student at Aalto University, specializing in Machine Learning, Data Science, and Artificial Intelligence. She earned her bachelor’s degree from the Chinese University of Hong Kong (Shenzhen), majoring in Computer Science with a minor in Statistics. This summer, she will begin an internship focused on a project that aims to characterize sex-specific differences in the human proteome comprehensively. She is interested in applying her skills in data analysis and machine learning to address complex challenges in the biomedical field.

Previous group members

Tomoko Nakanishi - Post-doc

Ville Pinto de Andrade Anapaz - Master student

Mattia Cordioli - PhD student

Yipeng Cheng - Visiting PhD student

Ettore Brenna - Master student

Anna-Leena Vuorinen - Senior Scientist

Joanne Demmler - Data Manager

Giulia Brunelli - visiting PhD student

Matthias Kirchler - visiting PhD student

Aoxing Liu - Post-doc

Sölvi Rögnvaldsson - Master student

Antti Karvanen – research assistant

Andrius Vabalas – Post-doc

Sakari Jukarainen – Post-doc

Alexandra Prinz - Rotation MD-PhD student

Kristina Zguro - visiting PhD student

Sara Kuitunen – Software developer

Linzi Yu - visiting student

Jiwoo Lee – Bioinformatician

Yllza Zogjani – research assistant

Vincent Llorens - Software Developer

Mari Niemi - Post-doc

Sara Pigazzini - Research assistant

Mads Nordentoft - Epidemiologist

Timo Syvälahti, MD-PhD rotation student

Atte Fohr, Summer intern

Takao Shimizu, Visiting student

Joona Savela, Visiting summer student