People

Dr. Jing Tang is a Full Professor in Medical Bioinformatics at the Faculty of Medicine and Group Leader for Network pharmacology for precision medicine. He received his PhD in Statistics from the University of Helsinki in 2009. He was a research scientist in Systems biology at the Technical Research Centre of Finland (VTT) in 2008-2011. Since 2012 he started at FIMM as a senior researcher focusing on computational network medicine. He received the prestigious ERC Starting Grant in 2016.

Dr. Johanna Eriksson joined the group in November of 2019 to perform the experimental validation of the pharmacology network models developed by computational methods. She received her PhD in genetics from the University of Helsinki in 2015. In her PhD and postdoctoral studies, she has focused on identifying prognostic markers and therapeutic targets for metastasized melanoma.

Research interests: gene expression profiling, biomarker discovery.

Dr. Jie Bao received her PhD in lung cancer pathology from Institute for Molecular Medicine Finland, University of Helsinki, in 2022. In her PhD study she established phenotyping methods and utilized animal models as well as clinical samples to understand the histotype-dependent heterogeneity in non-small cell lung cancer development. Currently, she wishes to continuously investigate cancer heterogeneity through integrating omic-approaches, in vitro/ex vivo drug perturbation studies and functional experiments, with a goal to search for precise solutions to combat drug resistance. Prior to coming to Finland, she has been trained with classical cell biology and neuroscience in UK and Belgium.

Research interests: cancer pathology, image analysis, drug-target profiling, cancer evolution and cell plasticity.

Tolou Shadbahr is a Doctoral researcher whose focus is on Data Science and application of Machine Learning methods for study and analysis of biological dataset, including multi-comics and clinical data. Tolou holds two master’s degree, one from Abo Akademi computer science program, and second one from Aalto university Life Science master. Her background is on computer science, system biology, and machine learning. Her previous works consist of application of machine learning models for drug sensitivity, drug combination prediction, prediction of patient survival status by machine learning, and imputation technique for missing values in clinical data. She is currently working on application of multi-modal machine learning methods for prognosis and diagnosis of Prostate Cancer patients.

Li Shen is a PhD researcher funded by the Finnish Doctoral Education Pilot Program. Before he joined the lab, he obtained a Bachelor’s degree in Bioengineering from Donghua University in China in 2016, and a Master’s degree in Biomedical Engineering from The Hong Kong Polytechnic University (PolyU) in 2023. His research mainly focuses on constructing models and developing tools for predicting drug responses at the single-cell level. 

Qinhan Hou is a PhD researcher developing pharmacological- and medical-related machine learning applications. He received his Master’s degree in Computer Science from Uppsala University in 2022. Before joining the group, he was a machine learning researcher in the Swiss AI Lab, working with Prof. Jürgen Schmidhuber. His research interests include self-supervised representation learning, precision medicine, and biological computation.

Huaiwu Zhang is a PhD researcher working on anti-cancer drug development based on multimodal data fusion and large language models. He received Master's degree in bioinformatics at the Chinese Academy of Sciences, and Bachelor's degree in bioinformatics at the Huazhong University of Science and Technology, China.

Weiming Yang received her master's degree in pharmacology from Shenyang Pharmaceutical University and is now a PhD researcher in the group. Her research focuses on the effect of intestinal flora on drug resistance in cancer patients.

Tomas Laamanen is a doctoral researcher whose interests are in the development of de-novo antibodies against viral infections with the help of machine learning. In order to advance his research his areas of interest include Virology, Structural Biology, Machine Learning Pipelines, Immunology, and Theoretical Machine Learning. Tomas obtained his MSc degree in Applied Mathematics with a minor in Bioinformatics and Digital Health from Aalto University in 2024.

Research interests: Virology, Structural Biology, Machine Learning Pipelines, Immunology, and Theoretical Machine Learning

Weize Gao is a Research Assistant and a Master’s student in Life Science Informatics at the University of Helsinki. Before he joined the lab, he obtained a Bachelor’s degree in Bioinformatics from Harbin Medical University in China, where he worked on medical image processing. His research mainly focuses on single-cell analysis and drug target prediction.

Kaiyang Chen received his Engineer degree in Materials Science from INSA Lyon, along with a dual Master’s degree in Nanotechnology. He gained systematic training in microfluidics and on-chip cell culture during his internship in Paris. He is currently a PhD researcher, focusing on building databases for microphysiological systems (MPS, such as organoids and organ-on-chip) and performing data analysis for MPS-based systems.

Linda Honkanen is a Master’s student in the Life Science Informatics programme at the University of Helsinki, with a BSc background in mathematics and statistics, and specializes in bioinformatics and systems medicine. Her research interests include computational problem-solving and applying data-driven methods to biomedical research. She is currently a research assistant completing her Master’s thesis in the group, focusing on using machine learning and multi-omics data to predict synergistic drug combinations in pancreatic cancer.

Tia Immonen is a Master’s student in Translational Medicine at the University of Helsinki and a research assistant in the group. Her work focuses on cancer cell lineage tracing and other experimental research projects within the group. Alongside her work in the group, she is completing her master’s thesis focusing on CD8⁺ T cell biology.

Adrita Chakraborty is a Master’s student in the Life Science Informatics programme at the University of Helsinki. She holds a bachelor’s degree in Bioinformatics and Biotechnology from Bangladesh. Her research interests include bioinformatics, multi-omics analysis, and computational approaches to understanding complex biological processes, with a particular interest in cancer biology. She is interested in using computational and data-driven methods to explore biological systems and gain insights that could contribute to the understanding and treatment of diseases. She currently works as a research assistant in the group, focusing on NK cell biology in cancer using computational and multi-omics approaches. Her current research involves analysing different types of molecular data to explore biological pathways, identify potential therapeutic targets, and better understand the molecular mechanisms involved in cancer.

Ronja Niittytähti is a Master's student in the Bioinformatics and Systems Medicine track in the Life Science Informatics Master's programme at the University of Helsinki. She completed her Bachelor's degree on Computer Science and is currently working a research assistant in the group. Her Master's thesis work in the group focuses on drug signature prediction and transfer learning from cell-line data to patient data using machine learning models.

Xinliang Sun is a Visiting Researcher at the Faculty of Medicine, University of Helsinki, and a PhD candidate at Central South University. His research focuses on drug repurposing, drug combinations and virtual cells.

Xinyi Zhang is a Visiting Researcher and a PhD candidate at Central South University in China. Her research focuses on developing computational methods to model drug perturbation effects, with the aim of advancing drug response prediction and drug screening.

Rui Liu received her master's degree from China Pharmaceutical University, where her research focused on elucidating the mechanisms of action of plant-based medicine and mining their combination patterns. She is currently a doctoral researcher whose research interests centre on predicting drug responses at single-cell resolution.

Shuixin Li (Dora) is a Research Assistant with a background in bioinformatics and computational biology. Her research focuses on antimicrobial resistance and the use of computational approaches to identify rational antibiotic combinations. She has previous experience in both academic research and the biotechnology industry.