The Sydney Informatics Hub brings together experts from diverse analytical and technical backgrounds.

Service Teams:

Academic Leadership

Tom Bishop

Associate Professor Tom Bishop

Acting Academic Director

Tom Bishop is an Associate Professor in the School of Life and Environmental Sciences. His research interests are in modelling and predicting the variation of environmental properties in space and time with an emphasis on applying this to the domains of soil, agriculture and hydrology. His main teaching is within Data Science-related units including ones in applied statistics, hydrology and GIS. He brings this passion for research data and analysis to directing the provision of similar services to researchers across the University.

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.

Data Science & Research Engineering

Joel Nothman

Dr. Joel Nothman

Acting Data Science Services Lead

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

Group Lead

Gordon’s background is in Physics, Chemistry and Mathematics (PhB, Australian National Univeristy, Uni Medal 2009), and he completed his PhD experimental quantum mechanics (2015) at the Australian National University, in which he developed compact new designs of quantum sensors to detect gravity with part-per-billion accuracy. Since joining SIH as a data scientist in 2016, he has been applying machine learning and bayesian statistical techniques to:

  • Heath-related projects with the Westmead Institute of Medical Research, the Woolcock Institute, and Sydney Children’s hospital.

  • Developing a software tool to streamline the process of analyzing metabolites through High Pressure Liquid Chromatography Mass Spectroscopy (HPLC-MS) at the Charles Perkins Centre.

  • Financial and occupational transition modelling for the NSW Department of Industry’s Smart and Skilled program for Vocational education and training.

  • Other projects involving dental health, electoral and demographic data, chemical concentration simulations, animal behaviour modelling and reviews on internet sales websites.

Gordon is part of the university’s Statistical Consulting Service as well as being a qualified Software Carpentry instructor, delivering hands-on training on behalf of SIH.

Email, GitHub, LinkedIn, Google Scholar, ResearchGate, Twitter.

Chao Sun

Dr. Chao Sun

Group Lead

With a background in electronics engineering, Chao has been working in the digital humanities for several years. As the Data Scientist of the Faculty of Arts and Social Sciences at this university, Chao created strong relationships with researchers, consulting on diverse research projects, to identify and collect large scale data sources, prototype data science techniques, and develop visualisations for researchers.

Email, LinkedIn

Darya Vanichkina

Dr. Darya Vanichkina

Acting Group Lead and Data Science Trainer

Darya is a data scientist with a biology background and experience in big data, machine learning, and statistics. She is a Software and Data Carpentry instructor and contributor, passionate about using evidence-based teaching practices to develop courses around quantitative skills, programming and reproducible research methodologies for researchers and non-technical audiences. Darya holds a PhD in Bioinformatics and Genomics from the University of Queensland, and is a Specialist Biochemist with a major in Molecular Biology. At SIH, Darya’s role is that of Data Analytics Trainer, working across the different faculties of the University to develop and deliver data science focussed discipline-specific workshops.

Email, LinkedIn, Github, Google Scholar, Website, Twitter

Louis Mercorelli

Dr. Louis Mercorelli

Lou is a PhD/MBA in Finance and Economics with a specialization in Quantitative Finance. He worked for Accenture (6+ years) and Deloitte (6+ years) as a senior project manager for many global finanacial clients. Over the last 15 years, he has worked as an independent consultant in many of the newest technologies (blockchain, CUDA/OpenCL, AWS, HFT, etc). Going forward, his goal is to achieve the highest caliber of skills in the following areas:

  • Strong consulting skills including exceptional project/program delivery, clear communication, sharp presentations, top tier publications and the highest leadership/management skills.

  • Strong skills in the newest technologies including blockchain solutions, parallel processing solutions (CUDA/OpenCL), big data management (AWS), algorithmic trading (high frequency), modelling and analysing unique data sets and anything cloud related.

  • He is always improving his skills in the following technologies (Python, Amazon AWS, C/C++, GNU R, Unix, Perl, VBA, Matlab, SQL, parallel programming, kdb+, IRESS, Swift, Haskell, functional programming). He is also continuously improving his knowledge in Econometrics, Math (Stochastic) and Statistics.

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.

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.

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.

Ben Mather

Dr. Ben Mather

Ben joined SIH after a postdoc at the Dublin Institute for Advanced Studies in Ireland from 2017-2018. Previously, he completed his PhD at the University of Melbourne in 2016. Ben has a background in geophysics with a particular focus on Bayesian inversion of thermochemical properties of the lithosphere subject to available data and their uncertainties. Currently, Ben is working on developing numerical simulations of erosion and depositional processes, fluid flow, and geodynamic evolution that can scale to large computing infrastructures. A firm supporter of open source software, many of Ben’s projects are available in publically accessible repositories.

Email, Github, ResearchGate, Website, Twitter

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.

Sergio Pintaldi

Dr. Sergio Pintaldi

Sergio is a Data Science Software Engineer in the SIH Data Science Team. He obtained a PhD in Mechanical Engineering with RMIT University in Melbourne, and worked in renewable energy for the past 6 years at the CSIRO Energy Centre in Newcastle and then with SwitchDin. His skills range from thermal modelling and simulation to big data processing and pipelines in production environments.

His areas of expertise are:

  • thermodynamics modelling, control and thermal systems dynamical simulations
  • Data modelling and analytics
  • Data visualization
  • IoT data pipelines
  • Data engineering and databases
  • Python (coding), Linux (OS), SQL (database), RabbitMQ (data streaming), Ansible (DevOps)

Email, GitHub, LinkedIn, Google Scholar.

Marius Mather

Marius Mather

Marius is a data scientist and statistician with a background in psychology and mental health research. He has a Master of Biostatistics from the University of Sydney and previously worked at the Matilda Centre for Research in Mental Health and Substance Use as a biostatistician. Marius is passionate about making data science more accessible to researchers in a variety of fields through the use of open source tools. His interests are statistical and causal inference, open and reproducible science, machine learning and Bayesian statistics.

Research Data Consulting

General enquiries:

Adele Haythornthwaite

Dr. Adele Haythornthwaite

Research Data Consulting Lead

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.


Olya Ryjenko

Olya Ryjenko

Research Data Consultant

Olya joined the University of Sydney in 2008 as a Research Speech Pathologist at the Australian Stuttering Research Centre, where she developed her passion for solving healthcare problems with the application of technology. In recent years, she worked as a Senior Research and Technology Officer for the Centre, administering research data management systems and designing data management protocols for the Centre’s clinical trials. As a Digital Research Support Officer at the Sydney Informatics Hub, Olya provides support and training to researchers and students across the university in enterprise digital research tools and data management practices.

Taylor Syme

Taylor Syme

Research Data Consultant

Taylor studied molecular biology and neuroimmunology during his PhD at the University of Sydney, during which he embraced the eNotebook to manage his own research. He also has extensive experience in training undergraduate students using this powerful tool. Taylor is now using this experience at SIH, where he is currently supporting, training and advising staff and student researchers in how to use the eNotebook and other digital tools to achieve best practice in research data management.

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.


Tracy Chew

Dr. 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.


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.

Contact me at, GitHub, LinkedIn, or Instagram @astrobutter

Cali Willet

Dr. Cali Willet

Senior Research Bioinformatics Technical Officer

Cali is a bioinformatician at the Sydney Informatics Hub. She completed her PhD in animal genomics and computational biology in the Faculty of Veterinary Science at the University of Sydney. She is interested in the genetics of disease in humans and animals, and how cutting edge genomic technologies are rapidly increasing our ability to understand complex biologies and phenotypes, in particular large scale genomic rearrangements. Currently she is working on optimising mammalian genomics pipelines to facilitate higher sample throughput on HPC, to be applied to diverse projects including human cancers and livestock studies.


Kristian Maras

Kristian Maras

Senior Research Informatics Technical Officer - Modelling and Simulation

Kristian is passionate about applied mathematical modelling, including optimisation and complex systems. He holds a Masters in Science - Mathematical and Statistical Modelling (UTS). His career in academia covers transdisciplinary research consulting in Energy and Sustainability, building models to guide efficient use of resources, data analysis and geospatial mapping.

Prior to that he has a commercial background in both Energy and Finance markets and originally studied a double degree in Commerce - Actuarial studies and Applied Finance (Macquarie University).


Statistical Consulting Service

Christopher Howden

Christopher Howden

Statistical Service Lead

Chris Howden is the Statistical Consulting Lead. He has been teaching and applying advanced statistical and quantitative methods since 1999, and managing data science/statistical teams since 2006. With experience in data visualisation, analysis, design, modelling, big data and training in the Academic, Public and Private sectors across a broad range of domains such as: Audio Processing of Gunshots, Criminal statistics, Ecology, Market Research (FMCG, Sensory and Services), Social Research, Psychology, Medical, Genetic and other miscellaneous areas e.g. modelling household waste. His focus is using the most appropriate analysis in developing evidence based insight and strategy to help Researchers achieve their objectives.


Jim Matthews

Jim Matthews

Statistical Consultant

Jim has worked as a statistician with the Sydney Informatics Hub since August 2018 and has also worked with the Bosch Institute in the Faculty of Medicine and Health. Jim’s interests include experimental design, quality and precision of test methods, and especially working with researchers and statistical methods to achieve research goals.

Prior to completing his Master of Statistics degree at the University of Wollongong in 2014, Jim worked in the iron & steel industry and the refractories industry for many years in a number of capacities with an emphasis on refractory design and performance and laboratory evaluation.


Alex Shaw

Dr. Alex Shaw

Statistical Consultant

Alex has a background in medical research, with expertise in molecular biology, cell biology, bioinformatics, genomics and genetics. During his research career, Alex witnessed a sharp increase in the quantity and complexity of data being collected across the various research fields he was exposed to. He undertook a Master of Biostatistics, with the aim of helping other researchers conduct their analyses in this data-rich world. Alex joined the statistical consulting team in mid-2019. As well as consulting, Alex has an interest and experience in teaching statistics. His overall goal is to empower researchers to embrace the statistical challenges and opportunities that come from working with complex datasets in their chosen field.


Kathrin Schemann

Dr. Kathrin Schemann

Statistical Consultant

Kathrin Schemann is a biostatistician with a background in animal and human health and holds a Master of Biostatistics and a PhD in Veterinary Epidemiology. Kathrin has a decade of practical experience in applying her wide-ranging study design and data analysis skills to multi-disciplinary research and operational work in a range of settings and domains, including government and academia and covering animal- and veterinary science, psychology, policy science, service planning, health statistics, population health information systems as well as clinical and population health research. She has taught applied biostatistics to undergraduate and postgraduate students since 2009. Kathrin is passionate about making statistics approachable and aims to assist researchers in optimising their study design and statistical analysis to improve the quality of their research.