Beth Wilson
Beth Wilson
Stakeholder Engagement Officer
- bethwilson@unimelb.edu.au
Beth Wilson is the MACSYS Centre Stakeholder Engagement Officer. A partnerships and engagement specialist, Beth is committed to fostering collaborative and mutually beneficial relationships with industry to drive impactful outcomes.
Beth has previously led partner engagement and work integrated learning in an innovative transdisciplinary tertiary setting. Developing partnerships with industry, community and government organisations, Beth designed programs that ensured mutual learning and professional development for both students and industry partners.
Thomas Soerianto
Strategic Research Committee
Research Fellow
- thomas.soerianto@unimelb.edu.au
Dr. Thomas Soerianto is a research fellow in the Department of Biochemistry and Pharmacology at the University of Melbourne’s Bio21 Institute, where he is developing workflows for collection of robust multi-omic datasets that will be used for the synthesis and validation of mathematical cell models.
Dr. Soerianto completed his PhD in Biochemistry in the University of Melbourne investigating the dark metabolome of the human parasite Leishmania using high-resolution mass spectrometry coupled with stable isotope labeling and computational mass spectrometry approaches. This was followed by a short postdoctoral appointment at the University of Melbourne with Dr. Wing Yan Chan where he developed high throughput metabolomic approaches for the analysis of coral and algae endosymbionts. Currently, he works with Professor Malcolm McConville to establish quantitative multi-omic data collection workflows. His collaborations have extended throughout the University of Melbourne and other institutions, including WEHI and La Trobe University. His expertise lies in liquid chromatography, mass spectrometry, computational mass spectrometry, and bioinformatics; and he is interested in applying mass spectrometry in a systems biology context.
Runze Li
Strategic Research Committee
PhD Candidate
Runze is a PhD candidate under the mentorship of Professors Wenjie Zhang and Hanchen Wang.
His research focuses on leveraging machine learning techniques to enhance algorithms for time series databases and protein biosynthesis. Previously, he completed both his undergraduate and postgraduate studies at the University of New South Wales, where he specialized in developing machine learning algorithms for graph-structured data.
Eric Stone
Strategic Research Committee
Chief Investigator
Professor Eric Stone is internationally recognised for his research in mathematical biology, evolutionary inference, and systems genetics; having made theoretical and methodological contributions to understanding the genotype-phenotype map and how it evolves over time.
At the Australian National University, Professor Stone is Director of the Biological Data Science Institute, an interdisciplinary academic unit aiming to recruit, build and coordinate expertise in biological data science to accelerate the translation of biological data to biological knowledge. His broad focus is on using statistical methods and mathematical theory to illuminate how genetic variation has shaped biological diversity, with a specific interest in systems genetic approaches. Genetic variation – whether natural, experimental or engineered – can induce a cascade of molecular variation that perturbs the genotype-phenotype map; characterising these perturbations will be essential for the reverse engineering of multiscale models and the development of predictive modelling for biotechnological and synthetic biology applications in MACSYS.
Jean (Jiayu) Wen
Strategic Research Committee
Node Leader
Associate Professor Jean (Jiayu) Wen is a computational biologist with expertise in computational and statistical method development, machine learning, high-throughput genomic data analysis, and molecular biology experiments to model gene regulatory interaction.
Wen is an Associate Professor at The John Curtin School of Medical Research at Australian National University (ANU) where she holds an Australian Research Council (ARC) Future Fellowship (2017-22), an ARC Discovery Project (2022-25), and an ANU Future Scheme Fellowship (2019-23). She has extensive experience developing computational methods and machine learning models of diverse modes of gene regulatory networks. Her work has made original contributions to both computational methodological advances and novel biological discoveries, evidenced by her consistently highly cited publications in the top journals of the field, with over 50% of her papers having appeared in the top 1-2% of journals in the field of computational biology and genomics.
Her research is in close collaboration with investigators from diverse disciplines, and she has established many strong national (6 current) and international (10 current) collaborations with world-leading computational and experimental biologists. The current goal of her research group is to make use of machine learning, computational and statistical method development, and the power of deep sequencing approaches combined with experimental validation to explore diverse modes of gene regulatory networks. Her skills and expertise in integrative computational models of gene regulation networks, founded on her research training in these areas in world-leading gene regulation laboratories (Memorial Sloan-Kettering Institute and Copenhagen University), are of particular importance for the data-driven modelling approaches.
Richi Nayak
Strategic Research Committee
Chief Investigator
Professor Richi Nayak is an internationally recognised data scientist with expertise in data and text mining (NLP), machine learning, and web intelligence. She is a Professor in the School of Computer Science and Leader of the Complex Data Analysis Program at the Centre for Data Science, Queensland University of Technology.
Professor Nayak has successfully managed over 25 industry-related projects, attracting a total income exceeding $15M. Professor Nayak has a successful track-record of combining knowledge in her diverse areas of expertise to solve real-world problems encountered in the Social and Biological Sciences as well as Engineering. She has delivered innovative automated data-driven systems, built upon novel machine learning algorithms, which have been adopted by both industry and Government.
Professor Nayak was awarded the 2016 WiT (Women in Technology) Infotech Outstanding Achievement Award for exemplary service to the field of data analytics.
Christopher Drovandi
Strategic Research Committee
Chief Investigator
Professor Christopher Drovandi’s research focuses on computational and applied statistics where he develops new statistical theory and algorithms for calibrating complex mathematical and statistical models to data. He is a Program Director of the Queensland University of Technology Centre for Data Science.
Professor Drovandi’s research in statistics has been recognised nationally and internationally. In 2021 Drovandi was awarded a Moran medal by the National Academy of Sciences and has served as the Chair of the Bayesian Statistics Section of the Statistical Society of Australia (2016-19). His international reputation as a statistics researcher is supported by his strong publication track record. Completing his PhD around 10 years ago, Drovandi has published more than 100 journal articles, developing and applying fundamental and cutting-edge data science tools to deliver new insights in multidisciplinary collaborations across biology, ecology, physiology, finance, sport and exercise science. His track record has led to more than 50 invited talks at international conferences and research institutions.
Traude Beilharz
Strategic Research Committee
Chief Investigator
Professor Traude Beilharz is an RNA biologist and biochemist interested in the birth, life and death of RNA as the molecule that brings the genome to life. In MACSYS, Traude combines her love of collaborative data-driven research and the Baker’s yeast, Saccharomyces cerevisiae.
Traude believes that the cross-disciplinary research applied in MACSYS to pursuit of whole-cell models will enable a new academic discipline -Predictive Biology- and new career paths toward research and entrepreneurship in digital biology.
In addition to her research, Traude enables excellence by supporting the thriving of the Centre’s diversity. She uses her mindset and leadership coaching qualifications to ensure each MACSYS member is safe to bring their best ideas, creativity and ambition -knowing that this looks different in each of us, and that the Centre’s success depends on it.
Jennifer Flegg
Strategic Research Committee
Director
Professor Jennifer Flegg is an applied mathematician in the School of Mathematics and Statistics at the University of Melbourne. Professor Flegg is an established international academic leader in mathematical biology with a focus on developing mathematical models of biological phenomena and calibrating them to data.
Professor Flegg’s research focuses on using mathematics and statistics to answer questions in biology and medicine, with a particular emphasis on mathematical models in areas such as wound healing, tumour growth and infectious disease epidemiology.
Professor Flegg has an extensive publication record in peer-reviewed journals and has been awarded several prestigious honours for her work, including the JH Michell Medal in 2020 for excellence in research by ANZIAM (Australian and New Zealand Industrial and Applied Mathematics), the Christopher Heyde Medal in 2020 from the Australian Academy of Science and the Society for Mathematical Biology Leah Edelstein-Keshet Prize in 2021. She also serves as an Editorial Board member for PLOS Computational Biology, eLife, Bulletin of Mathematical Biology and SIAM Journal on Applied Mathematics.