Associate Professor Tom Bishop
Acting Academic Director
Tom Bishop is an associate professor in the School of Life and Environmental Sciences, and mainly teaches in the field of data science. 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.
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.
Gordon’s background is in Physics, Chemistry and Mathematics (PhB, Australian National University, 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:
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.
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.
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.
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 financial 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 calibre 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.
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. 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.
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.
Nikzad started his position at SIH in September 2016 after five years working in industry as a 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 an 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 is a Research 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:
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.
Henry is a data scientist with a background in parasite ecology, conservation, and infectious disease research. He has a PhD in Biology from the University of Sydney and has worked as a member of the Marie Bashir Institute for Infectious Disease and Biosecurity at the University of Sydney. Henry enjoys finding innovate and efficient ways to collect, process, analyse, and visualise complex data sets. His areas of expertise include non-normal distributions, modelling, geospatial analysis, and time-series analysis.
Jazmin is a data scientist at SIH and has a Bachelor of Science (Hons I) in biochemistry, molecular biology and microbiology. She is currently finishing her PhD in biophysics at the University of Sydney where she is using full-atomistic molecular dynamics to elucidate the intrinsic properties of tropoelastin, the protein that gives human tissue stretch and resilience. Previously, she worked at Institutional Analytics and Planning at the University of Sydney, where she analysed geospatial, educational and operations based data. In her spare time, Jazmin is a freelance illustrator and avid data visualisation appreciator, having worked with multiple academics at the University of Sydney to provide illustrations for their publications and reports.
Sabastine comes from an agriculture and geospatial background and has used his expertise in these areas to model and predict variations of environmental attributes, such as vegetation productivity, and soil functions across space and time over large areas. Sabastine holds a PhD in Agriculture from the University of Sydney and was involved in tutoring data science and geographic information systems (GIS) related units at the University. Sabastine is passionate about providing data science technologies and support to researchers across different disciplines.
PhD (Ecology), Syd.
Adele has previously worked in IT developing commercial software. For her PhD, she specialised in small mammal ecology in arid environments, and has extensive experience working in various research groups at Sydney.
Adele oversees the development of research data management policy, and works with the research community to identify, advocate for and implement strategies to improve research data outcomes across the University. She is continuing to explore mechanisms to improve researchers' access to health and clinical data, and management of sensitive data in research.
PhD (Molecular Biology and Neuroimmunology), Syd.
Dr 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.
PhD (Anatomy), UNSW.
Cameron has joined SIH after working as a researcher attached to a clinical team the Sydney Children's Hospital Network between 2017-2019. He completed his PhD at NeuRA where he looked at improving child car restraints and has experience with histology and microscopy. Leveraging his broad research experience, Cameron is providing support and training to researchers and students across the university in digital research tools and data management.
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 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.
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.
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 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).
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 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 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 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.