Sydney Informatics Hub encompasses experts from diverse technical backgrounds. Our biographical information is displayed below.

Bradley Evans

Dr. Bradley Evans

Acting Academic Director

Bradley Evans is a Senior Lecturer in Big Environmental Data and Biosphere-Atmosphere Interactions in the School of Life and Environmental Sciences, and brings a wealth of experience in informatics and research computing, particularly in data-intensive environment and climate modelling, to the role of directing the Informatics Hub.

Geraint Lewis

Professor Geraint Lewis

Deputy Director

Geraint F. Lewis is a Professor of Astrophysics (Teaching and Research) at the Sydney Institute for Astronomy, part of the University of Sydney’s School of Physics. He is head of the Gravitational Astrophysics Group, is the Associate Head for Research, and Deputy Director of the Sydney Informatics Hub. He is a Welsh astrophysicist, who is best known for his work on dark energy, gravitational lensing and galactic cannibalism.

He completed his first degree at the University of London and PhD at the University of Cambridge’s Institute of Astronomy. He has worked in the State University of New York, the University of Victoria in Canada, and the University of Washington in Seattle. He then became a Research Astronomer at the Anglo-Australian Observatory in 2000. In 2002, Lewis joined the University of Sydney.

He undertakes a broad spectrum of research in cosmology. On the largest scales, his program involves looking at the influence of dark energy and dark matter on the evolution and ultimate fate of the universe.

Another aspect of his research uses the phenomenon of gravitational lensing to probe the nature and distribution of the pervasive dark matter, and employing individual stars to magnify the hearts of quasars, the most luminous objects in the universe.

Closer to home, Lewis’s research focuses upon galactic cannibalism, where small dwarf galaxies are torn apart by the much more massive Milky Way and Andromeda Galaxy. Using telescopes from around the world, including the 10-m Keck telescope in Hawaii, he has mapped the tell-tale signs of tidal disruption and destruction, providing important clues to how large galaxies have grown over time.

Gareth Denyer

Professor Gareth Denyer

Research Data Steward

Associate Professor Gareth Denyer currently works in the areas of molecular biology and genetics, and nutrition and metabolism. Gareth did his undergraduate degree at the University of Oxford and stayed there to do a PhD under the supervision of Professor Sir Philip Randle. He was appointed as a Lecturer in Metabolism, in the Department of Biochemistry in 1990. He was the recipient of the University Excellence in Teaching Award in 1995, and was part of the ELATE Committee that won the group award in 2010. In 2012, he won the Australian Society for Biochemistry and Molecular Biology Teaching Award. He has over 70 publications over a wide range of discipline areas including metabolic regulation, microarray analysis, glycemic index testing, nutritional analysis, and molecular biology.

Gareth main interest is in the molecular mechanisms underlying body ‘set point’. He uses DNA microarrays to look at transcriptome patterns in circumstances of metabolic interest - for example:

  • how does gene expression change in different tissues when we consume different diets - especially those of different glycemic index?
  • how do different hormones (like insulin and leptin) affect which genes are switched on and off?
  • what gene expression patterns characterise large and small adipocytes? What happens as adipocytes change in size (as in weight loss and weight gain).
  • what gene expression patterns characterise different types of obesity?

Data Science Research Engineers

Peter Thiem

Peter Thiem

Team Lead, Research Hub Engineers

Peter is a software development professional with 10+ years of professional experience in software design, development, maintenance, as well as team and technical leadership. He is interested in applying advanced computation, software/data engineering and machine learning to research problems. For more information, see Peter’s profile on LinkedIn.

Dr. Maryam Montazerolghaem

Dr. Maryam Montazerolghaem

Maryam specialises in applied machine learning and statistical modelling. She has diverse experience spanning industrial and academic projects such as public health management, agriculture and dairy production, climate modelling, spatiotemporal data modelling and visualisation, wind generators and renewable energy integration, image and signal processing, time series analysis, bioinformatics, transport management, customer service and customer engagement. Maryam holds a PhD in climate modelling (the University of Sydney), M.Sc. in Medical Engineering (Bioelectric) and BSc. in Electrical and Telecommunication Engineering. She provides consulting services for data-driven project development. In her spare time, she is an enthusiast of Bayesian Statistics, Deep Learning and Fuzzy Logic.

Dr. Sebastian Haan

Dr. Sebastian Haan

Seb joined the University of Sydney in 2016 as a research data engineer and specialises in machine learning and data visualisation methods. With a background in particle and astrophysics (PhD, University of Heidelberg, Germany), his career is built on international research positions at the California Institute of Technology (USA), CSIRO Astronomy & Space Science (Sydney), the Max-Planck-Institute (Heidelberg, Germany), and the German Electron Synchrotron (DESY, Hamburg). He has published and peer-reviewed in several major scientific journals (see his ResearchGate profile here). Having long term experience in analysing a wide range of complex data, he is keen on tackling new challenges in the rapidly changing field of machine learning for a large variety of data science applications. His latest research focuses on probabilistic models to explain and predict the occurrence of crime as well as novel 3D image processing methods for astronomical instruments. Besides data science and research, he enjoys to take things apart - but can’t always put them together again.

David Kohn

David Kohn

David is a data scientist who has previously worked in finance, psychology and survey design and analysis. At SIH and CTDS David has worked on Bayesian methods as well as applied projects in mental health, aged care, application development, criminology and political science.

Dr. Alexander Judge

Dr. Alexander Judge

After completing his PhD in Theoretical Astrophysics Alex joined CUDOS, an ARC Centre of Excellence, where he conducted research into next generation optical communication and quantum computation technologies. Following 6 years in this academic research environment he then spent 2 years as a consultant for two IT startups before joining SIH in late 2016.

Rafael Possas

Rafael Possas

Rafael is a data scientist and software engineer with extensive business experience in a wide range of industries, having worked for 11 years on business intelligence applications in both Australia and Brazil. Rafael has applied cloud computing technologies to store, process and extract insights from large amounts of data. On the data science side, neural networks and reinforcement learning have been the main focus, allowing the discovery of patterns and insights on very large datasets. Rafael has both research and business specialisations which allows him to have strong understanding of machine learning methods and results-driven problem solving skills.

Joel Nothman

Dr. Joel Nothman

Joel spent many years as a student at the University of Sydney (BSc / BA (Uni. Medal) 2008; PhD 2014) becoming an expert in natural language processing and linguistics, as well as in software engineering and machine learning more generally. He is a substantial contributor to the Scientific Python open-source software community, and brings this knowledge of developing scientific software for public use to the SIH team. He enjoys communicating about research, and also lectures for the School of IT.

See LinkedIn, GitHub and Google Scholar

Gordon McDonald

Dr. Gordon McDonald

Gordon has been a data science research engineer at SIH since mid-2016, applying machine learning and bayesian statistical techniques to heath-related projects with both the Westmead Institute of Medical Research and the Woolcock Institute. Since joining SIH he has also worked on projects involving dental health, electoral and demographic data, chemical concentration simulations, and reviews on internet sales websites. Gordon’s background is in Physics, Chemistry and Mathematics, and he completed his PhD experimental quantum mechanics at the Australian National University, in which he developed compact new designs of quantum sensors to detect gravity with part-per-billion accuracy.

Email: GitHub: gdmcdonald ResearchGate: Gordon_Mcdonald2

Madhura Killedar

Dr. Madhura Killedar

Dr Madhura Killedar is a Research Engineer working with the Sydney Health Data Coalition and partners at Westmead Institute of Medical Research. She received her PhD in physics at the University of Sydney in 2011 and conducted postdoctoral research in astrophysics in Italy and Germany. Her work has included building approximate Bayesian tools to bridge the gap between cosmological simulations and space-telescope data, and applying classification methods informed by machine learning techniques to a range of astronomy problems. She has also developed computational population health models with a focus on optimising health outcomes, allocative efficiency, and statistical uncertainty in the fields of HIV and child nutrition as a research scientist at the Burnet Institute.

Emily Neo

Emily Neo

After graduating from the University of Sydney’s Business School (BComm (Lib) (Uni Medal)), Emily worked as a consultant within financial services, data analytics and product development. During her time in industry, she focused particularly on portfolio/account risk, modelling for profitability, and developing automated and streamlined products to improve business processes and productivity. Emily’s interests include applications of machine learning and statistical approaches to address research and commercial problems. At SIH, she is dedicated to working on Business School research partnerships.

Nikzad Rizvandi

Dr. Nikzad Rizvandi

Nikzad started his position at SIH in September 2016 after five years working in industry as data scientist and research software engineer. He got his PhD in computer science as a joint research program between the University of Sydney and National ICT Australia (now Data61) in 2013, and a Bachelor of Science in electronics engineering from Sharif University of Technology at 2002. He was awarded Google Australia best publication prize at 2011 for his work in the area of energy efficiency in high performance computing systems. Before starting his PhD, he spent around 7 years as engineer in research organisations in Iran and Belgium where he was transferring research ideas in digital signal/image processing and machine vision to real products. Currently, his interest lies in applying machine learning techniques (from decision trees, to deep learning, to bayesian statistics) on agriculture, medical and psychology applications.

Vijay Raghunath

Vijay Raghunath

Vijay started his position as Data Science Software Engineer at SIH from May 2018 and is presently involved in e-Health Analytics projects. He is pursuing his Masters in Data Science from the University of Sydney and has completed his Bachelors in Computer Science (Hons) from the University of Mumbai, India in 2004. He has 12 years of experience in working with leading software consultancies and has worked for Fortune 500 customers across the globe. Vijay’s current interests lie in developing complex data pipelines for big data ecosystems, data visualisation techniques, Digital Transformation, Data Governance and ethics.

GitHub, LinkedIn

Di Lu

Di Lu

Di joined SIH as a Data Science Software Engineer after having received the degree of Bachelor in Software Engineer (Hons) in June 2018. Previously, he was a research assistant at CTDS working on the application of Variational Bayesian Optimisation methods to real-world problems. He also worked in an A.I startup where he developed solid full-stack development skills. Di’s interest and specialisation are Bayesian statistics, stochastic decision making processes and application development. He particularly loves reading beautiful code with a warm cup of tea on a sunny day.

Research Data Management

Adele Haythornthwaite

Dr. Adele Haythornthwaite

Senior Policy Officer

Adele oversees the development of research data management policy, and works with the Research Data Steward to identify and implement strategies to improve research data outcomes across the University. Adele has previously worked in IT developing commercial software, and has a PhD (Uni. Sydney) in biology, specialising in small mammal ecology in arid environments. At SIH, Adele is exploring mechanisms by which health and clinical data can be better accessed by researchers.

Daniele Vicari

Dr. Daniele Vicari

Digital Research Support Officer

Daniele has worked as biochemistry researcher in the past. She maintained her passion for teaching while working in several educational institutions in Brazil, USA, Switzerland and Australia as a teacher, tutor and mentor of students. Taking advantage of her extensive experience of training undergraduate and graduate students, she is currently supporting, training and advising staff and student researchers in how to use the eNotebook and other digital tools to achieve best research data management practices in the University of Sydney.

Helena Lynn

Dr. Helena Lynn

Digital Research Support Officer

Helena Lynn completed her PhD in molecular virology at the University of Sydney in 2015. She now uses her research experience to engage with researchers and students on best-practice research data management within the University context. She delivers training, consults on and provides functional user support for the eNotebook, REDCap and other digital research tools.


Informatics and Research Computing

Rosemarie Sadsad

Dr. Rosemarie Sadsad

Informatics Services Lead

Dr. Rosemarie Sadsad is the Informatics Services Lead at the Sydney Informatics Hub. She is a computer biomedical engineer, with a Ph.D. in health informatics (UNSW). She also conducts research in pathogen genomics and clinical decision support for NSW Health. Rosemarie specialises in complex systems analysis (multiscale modelling and simulation, network analyses), decision support systems, pathogen genomics, and bioinformatics. She has over 10 years experience applying these skills and knowledge across the health domain including health services, heart disease, Dementia, and largely, infectious diseases and is a member of the National Communicable Disease Genomics Network. Her interests are in utlising innovative technology and analytics to synthesise complex big data and improve its accessibility on the ground through effective communication and visualisation.


Nathaniel Butterworth

Dr. Nathaniel Butterworth

Senior Research Informatics Technical Officer (Visualisation)

Nathan has worked as a postdoctoral research associate in the EarthByte group at the University of Sydney. Here he learned the crafts of data mining and machine learning on big data projects. Prior to this he completed a PhD in geosciences entitled, “The dynamics of subduction and its tectonic implications”. Before pursuing geophysics he received his BSc from the University of Wollongong in 2008 and his honours in astrophysics from the University of Sydney in 2009. Between his postdoc and starting at SIH in July 2017, Nathan spent 2 years travelling the world with a telescope and engaging the global community with just how cool science is. Now he returns to the academic world to enable and inspire researchers to embrace the services of the Sydney Informatics Hub.

Tracy Chew

Tracy Chew

Senior Research Bioinformatics Technical Officer

Tracy is a bioinformatics technical officer at the Sydney Informatics Hub. She began with an interest in animal science, completing her Bachelor of Animal and Veterinary Bioscience (Hons I) at the University of Sydney. Her interests developed into using computational tools to understand animal genomes and how they play a role in the health and evolution of companion animals. She went on to pursue a PhD focussing on the identification and diagnostic testing of causal loci for rare diseases such as haemophilia and retinal atrophy in the domestic dog. She is also characterising new genetic mutations in the dog and is exploring the amazing phenomenon of how over 400 phenotypically diverse breeds of dog (from the little Chihuahua to the Great Dane) emerged from the grey wolf in a relatively short period of time.


Hayim Dar

Dr. Hayim Dar

Informatics Technical Officer (Modeling & Simulation)

Hayim started out in Physics before switching over to Computational Neuroscience in hopes of unlocking the mysteries of the brain. So far he’s only managed to explore some neuronal circuit models for short term, episodic memory, and a neural model for spatial learning based on the statistics of exploratory trajectories. Taking a break, Hayim has joined the SIH as a Modeling and Simulation technical officer, living by the motto “If you think you have a model, simulate it!” He is the resident Matlab consultant, and is also keen to help researchers scale up their computations and simulations using cluster and GPU computing.


Statistical Service

Christopher Howden

Christopher Howden

Statistical Service Lead

Chris Howden is the Statistical Service Lead. He has experience with statistical analysis, modelling and data visualisation skills to create evidence based business and political strategy.