Speakers

Alexander Kurilshikov is an Assitant Professor at the UMCG, University of Groningen. His team aims to explore the interactions between the human microbiome and other kind of human ‘omics’ data to investigate the possible impact of the microbiota on human health. Using data from the LifeLines-DEEP population cohort, they showed how the gut microbiome is shaped by external and intrinsic factors such as diet, medication and diseases (Zhernakova et al, Science, 2016). Now Alex is focusing on further analysis of the microbiome’s role in shaping human serum metabolism, which is the key element in many metabolic disorders and cardiovascular disease events.

Dorien is a PhD candidate in the unit of medical statistics and decision making and a junior teacher at DASH. She graduted in Econometrics and operations research, from Erasmus University Rotterdam, followed master's degree in Theoretical Physics from the University of Amsterdam. Her PhD project focuses in in developing unsupervised machine learning methods for dimension reduction, and pattern recognition in population cohort data and performing further data analysis using the outcomes of these methods.

Prof. Tong is currently Director at Centre of Artificial Intelligence driven Drug Discovery, Faculty of Applied Sciences, and Professor in the Faculty of Health Sciences and Sports, Macao Polytechnic University. His research focus included AI-driven drug discovery, crystal engineering, and formulation science. To date, he has published 85 articles in SCIE-listed journals, 3 book chapters in scientific collections and 7 patents. In academia-industry collaboration, he has participated, and has assisted, the R&D activities in 2 Phase II candidates, 2 Phase I candidates, 10+ preclinical drug candidates, and numerous generic drugs, medical foods, health supplements, and cosmetic products. Some of which are brand name products reputable in national and international levels.

Joel P. Arrais is an Associate Professor at the Department of Informatics Engineering, University of Coimbra. He has received his MSc and PhD in Computer Science from University of Aveiro in 2004 and 2010 respectively. His research interest are on developing algorithms to model biological problems. He is particularly interested in using pattern recognition and machine learning methods. He has been involved on several studies that focused on the analysis and knowledge extraction from gene-expression data.

José Sousa was the Manager of the Advanced Informatics Core Technology Unit in the Faculty of Medicine, Health and Life Sciences at Queen´s University Belfast (QUB). He obtained his PhD under Prof. Ricardo Machado (University of Minho, Portugal) and Prof. Jose Mendes (University of Aveiro, Portugal) supervision at University of Minho, Portugal on developing complex network models to study software usage alignment with the project requirements. Previously and during his PhD he worked as Information Systems Director at I3S, a research institution of University of Porto, where he deployed and managed all the IT infrastructure as well as deploying and developing software to support management and research operations. He was a collaborator of HDRUK – Swansea/QUB substantial site as AI researcher and actively working with QUB Centre for Public Health as part of the QUB support to Northern Ireland Public Health response to pandemic where he has developed self-learning AI on publicly available and self-reporting data. He also has worked on genetic alignment modelling and on mining socio-technical systems. Currenlty, José is a Research Team Leader of Personal Health Data Science, at CEnter for Computational Personalized Medicine (SANO), Krakow, Poland.

Luis H. M. Torres received the BSc and MSc degree in Biomedical Engineering, specializing in Clinical Informatics and Bioinformatics, from the University of Coimbra. He is currently a research fellow at the Center of Informatics and Systems of the University of Coimbra and is pursuing the PhD degree in Computer Science at the Department of Informatics Engineering of the University of Coimbra. His research interests include deep learning and meta-learning applied to biology, genetics and drug discovery.

Maryam Abbasi is a researcher in AI and Machine Learning, holding a PhD in Informatics Engineering, as well as a Master's and a Bachelor's degree in Computer Science. She is affiliated with the Institute of Applied Research (i2A) at the Polytechnic Institute of Coimbra (IPC), the Centre for Natural Resources, Environment and Society (CERNAS), and the Laboratory of Artificial Neural Networks (LARN) at the Center for Informatics and Systems of the University of Coimbra (CISUC). Her research focuses on data analysis and data science within AI and machine learning.
Her research interests include pattern recognition and machine learning. She is particularly focused on developing algorithms to model biological problems using machine learning models. She is also keen on applying the concept of multi-objective optimization to real-life problems, such as those found in bioinformatics.

Matthias Futschik is a bioinformatician and systems biologist with over 20 years of international research experience. He obtained a PhD in Information Science from the University of Otago in Dunedin, New Zealand, and has held leading positions for over 15 years in both the academic and entrepreneurial sectors across New Zealand, Germany, Portugal, and the UK. Currently, he serves as a principal investigator at the Centre for Innovative Biomedicine and Biotechnology at the University of Coimbra (CIBB) and holds an honorary professorship at the University of Plymouth, UK. His work spans the development of methodologies and resources, applied bioinformatics, and interdisciplinary research. Areas of expertise include genomics, transcriptomics, multi-omics approaches, analysis of NGS and high-throughput data, and network-oriented investigations of human diseases and developmental processes.

Paulina obtained her M.Sc. in Biophysics (Medical Physics) from Faculty of Physics, Astronomy and Applied Computer Science at Jagiellonian University. After that Paulina started interdisciplinary PhD studies “Interdisciplinarity for Innovation Medicine” in the area of chemistry and physics at Jerzy Haber Institute of Catalysis and Surface Chemistry Polish Academy of Sciences and at Henryk Niewodniczański Institute of Nuclear Physics Polish Academy of Sciences. Her doctoral project concerns conformational changes in proteins that are of great importance in the development of neurodegenerative diseases, and she carried out part of the project at University of Oldenburg and at Yale Medical School. Paulina defended doctoral degree in September 2022. She also worked as Data Scientist in a start-up dealing with diagnosis the condition of human heart. At Sano Paulina will work on applying data science in personalized medicine. In her free time, she loves travelling and expanding knowledge on the possibilities of supporting medical care by new technologies.

Tommaso Mazza is a distinguished leader in computational biology and bioinformatics, blending computer science with biomedical engineering. MSc in Computer Science Engineering and PhD in Computer Science and Biomedical Engineering. He was researcher at Microsoft Research COSBI (Trento, 2008) and at the Laboratory of Translational Genomics (Center for Integrative Biology, Trento, 2010). Adjunct professor for University RomaTre of Rome (2015-2016), University TorVergata (2019-2020), and University of Rome (2022-2024). He was Chief technology officer of the Innovative startup QRARE s.r.l since 2021. Currently, Tommaso Mazza is Head of the Bioinformatics lab at IRCCS Casa Sollievo della Sofferenza (FG) and CSS-Mendel (Rome), Italy, since 2012 and research affiliate at IRCCS Ospedale Pediatrico Bambino Gesù. He authored more than 180 peer-reviewed scientific articles and his research interests span from Network Biology, Computational Systems Biology, to Big Data & Scientific programming.

Yves Moreau is a professor of bioinformatics at the University of Leuven, Belgium. His team focuses on artificial intelligence and machine learning algorithms for the integration of complex data in clinical genomics, real-world clinical data analysis, and drug discovery. He is also a concerned scientist engaged in a reflection on how information technology and artificial intelligence are transforming our world and on how to make sure this transformation is beneficial for all. In particular, he actively pushes back against the emergence of surveillance societies that has been made possible by technological advances. He has been actively investigating abuses of DNA profiling technology in Xinjiang, Tibet, and Kuwait. Beyond pointing at the responsibility of governments, he also demands that tech companies be liable for the reckless supply of technology that is key to human rights abuses. Moreover, he is actively pursuing the reevaluation of unethical biometric research, in particular on forensic population genetics and facial recognition, and has obtained the retraction of 35 unethical journal articles so far. His work has been covered in major scientific journals, such as Nature and Science, and news outlets, such as The New York Times, The Guardian, and the BBC. He received the 2023 Einstein Foundation Individual Award for Promoting Quality in Research