Prof. Przulj is an ICREA Research Professor at Barcelona Supercomputing Center and a Full Professor of Computer Science at University College London. She is a Fellow of several learned societies: the European Laboratory for Learning and Intelligent Systems (ELLIS), the International Society for Computational Biology (ISCB), the International Artificial Intelligence Industry Alliance (AIIA), and the British Computer Society (BCS). Also, she is a member of Academia Europaea – The Academy of Europe, and the Serbian Royal Academy of Scientists and Artists (SKANU). She has been a Scientific Advisor of the Mathematics Institute of the Serbian Academy of Sciences and Arts (SANU) since 2012. In 2014, she received the BCS Roger Needham Award, sponsored by Microsoft Research, in recognition of the potential her research has to revolutionize health and pharmaceutics. She obtained a PhD in Computer Science from the University of Toronto in 2005.
Research interests
Prof. Pržulj initiated utilization of non-negative matrix tri-factorization (NMTF) based ML methodologies for fusion of heterogeneous, systems-level, molecular (multi-omics) networked data (the subject of her ERC Consolidator Grant) to aid to the development of personalized, or precision medicine. In addition, she initiated extraction of biomedical knowledge from the wiring patterns (topology) of omics network data to complement the genetic sequences as a source of new biomedical information (subject of her ERC Starting Grant). She is best known for introducing graphlets in 2004, a data mining methodology now widely extended and utilized to produce feature vectors capturing network topology, that are used as input into many AI/ML algorithms for network data analytics in various domains; graphlets are subject of over 21,000 research papers and hundreds of patents according to Google Scholar. She now develops AI methods for embedding and fusion of time-series multi-omic data in medicine.
Selected publications
- Mihajlovic K, Ceddia G, Malod-Dognin N, Novak G, Kyriakis D, Skupin A & Przulj N 2024, 'Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease', Scientific reports, 14 - 1.
- Maier, A et al. 2024, 'Drugst.One - a plug-and-play solution for online systems medicine and network-based drug repurposing', Nucleic Acids Research, 52-1-481-488.
- Doria-Belenguer S, Xenos A, Ceddia G, Malod-Dognin N & Przulj N 2024, 'The axes of biology: a novel axes-based network embedding paradigm to decipher the functional mechanisms of the cell', Bioinformatics advances, 4 - 1 - vbae075.
- Zitnik, M et al. 2024, 'Current and future directions in network biology', Bioinformatics advances, 4 - 1 -vbae099.
- Windels SFL, Velasco DT, Rotkevich M, Malod-Dognin N & Przulj N 2024, 'Graphlet-based hyperbolic embeddings capture evolutionary dynamics in genetic networks', Bioinformatics, 40 - 11 - btae650.
Selected research activities
Prof. Pržulj is a leader in Artificial Intelligence (AI) and Machine Learning (ML) algorithms for multi-omic data analysis and fusion applied to precision medicine. She published over 100 peer-reviewed journal and conference papers in the most prestigious venues, including four in Science, also 13 peer-reviewed book chapters and 2 books. Her research has been cited over 13,000 times, h-index=50, i10-index=81 (Google Scholar), and supported by over €25 million in competitive research funding. Notably, she received three prestigious, single PI, European Research Council (ERC) grants: ERC Consolidator (2018-2025), ERCProof of Concept (2020-2023) and ERCStarting (2012-2017).