There are no upcoming events.
If you are interested in any further information on our past events feel free to contact the CIC team.
The Hackathon has been postponed to early in 2018.
Sky Mining 2017 is a public hackathon taking data science to the skies.
Over 48 hours this event will bring together scientists, coders, technologists and enthusiasts from academia and industry to work on challenges Australian-based astronomers face.
Remote participation is a possibility, please contact us to discuss options.
This event is run by the Astronomy Data and Computing Services (ADACS) initiative. ADACS is delivered jointly by Swinburne University of Technology, Curtin University, and Pawsey Supercomputing Centre. This Project is an initiative of the Australian Government being conducted as part of the National Collaborative Research Infrastructure Strategy and administered by Astronomy Australia Ltd (AAL).
Professor Dirk Ifenthaler presents Can Data and Analytics Support Learning and Teaching?
Remarkable repertoires of computer-based applications and systems have been developed for supporting learning and teaching. Currently, promising learning analytics applications are being developed which utilise data produced through these computer-based applications and systems. Such learner generated data and other relevant information may be further used to personalise and continuously adapt these learning environments. Accordingly, learning analytics emphasise insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. Learners may benefit from learning analytics through optimised learning pathways, personalised interventions, and real-time scaffolds. Further, learning analytics provide teachers detailed analysis and monitoring on the individual student level, allowing to identify particularly instable factors, like motivation or attention losses, before they occur.
Along theoretical foundations and empirical evidence from cognitive psychology as well as the learning sciences, this presentation will explore the readiness and promising opportunities of the emerging learning analytics field.
Professor Dirk Ifenthaler’s research focuses on the intersection of cognitive psychology, educational technology, data analytics, and organisational learning – see Dirk’s website for a full list of scholarly outcomes at www.ifenthaler.info. Professor Ifenthaler who currently works at the University of Mannheim is the Editor-in-Chief of the Springer journal Technology, Knowledge and Learning (http://www.springer.com/10758).
The presentation will be followed by afternoon tea and networking opportunity.
Professor Rainer Schnell presents
Recent Developments in Bloom Filter-based Methods for Privacy Preserving Record Linkage
Combining data of the same unit using multiple databases is becoming increasingly popular in official statistics, the social sciences, medical research, criminology and other quantitative research fields. If the data entities are natural persons, linking different data sources is often restricted to encrypted personal identifiers when no unique personal linkage key (PID) is available. In this setting, techniques of the very active research field of Privacy Preserving Record Linkage (PPRL) have to be used.
Recently, Bloom Filters for PPRL applications have become increasingly popular, due to their similarity-preserving properties which enable the use of similarity threshold-based linkage techniques. Since these properties could lead to security vulnerabilities, the cryptographic properties of Bloom Filters are of special interest.
Previous research has shown that the straight application of Bloom Filters has a non-zero re-identification risk. Some recently developed techniques for attacking Bloom Filter encodings will be described shortly. We will present new results on new methods to make attacks on Bloom Filters increasingly difficult. These computationally simple algorithms modify the identifiers by different cryptographic diffusion techniques, among these are applications of Cellular Automata and Markov Chains. The presentation will demonstrate these new algorithms and show their performance concerning precision and recall in large databases.
Rainer Schnell holds the chair for Research Methodology in the Social Sciences at the University of Duisburg-Essen, Germany. He is former Director of the Centre for Comparative Surveys at City University London and graduated with a postdoctoral degree in Research Methodology at the University of Mannheim in 1996. His research focuses on non-sampling errors, applied sampling, census operations and privacy preserving record linkage. Professor Schnell founded the German Record Linkage Centre and was founding editor of the journal “Survey Research Methods”. He is the author of books on Statistical Graphics (1994), Nonresponse (1997), Survey Methodology (2012), Research Methodology (10th ed. 2013) and of more than 30 papers on Privacy Preserving Record Linkage.
The presentation will be followed by afternoon tea and networking.
- Data preparation
- Exploratory data analysis
- Cross validation
- Learning curves
- Model tuning
- Dimensionality reduction
Professor Vishnu Pareek presents Modelling of Pyrolysis Process
Pyrolysis is an important thermochemical conversion process for the conversion of biomass into useful commodities. In this presentation, Professor Pareek will discuss the fundamentals of the pyrolysis process with special emphasis on the multi-scale aspects of its modelling. A number of case-studies for different scales of modelling will also be discussed.
Vishnu Pareek is a Professor of Chemical Engineering at Curtin University. He has varied research interests encompassing both fundamental and applied nature research but his focus is in the area of computational fluid dynamics (CFD) and multiphase modelling.
He is currently also serving as the Head of School for the School of Chemical and Petroleum Engineering.
Software Carpentry‘s mission is to help scientists and engineers get more research done in less time and with less pain by teaching them basic lab skills for scientific computing. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. For more information on what we teach and why, please see our paper “Best Practices for Scientific Computing“.
Who: The course is aimed at graduate students and researchers. You don’t need to have any previous knowledge of the tools that will be presented at the workshop.
Content: We will be teaching introductions to the Unix shell, version control with Git as well as programming with Python and R. For the syllabus and schedule see
When: Monday 28 to Wednesday 30 August 2017, 9am to 5pm
The goal of this introductory workshop is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
- Introduction to R and RStudio
- Project Management With RStudio
- Data Structures
- Exploring and sub-setting your data
- Writing functions
- Introduction to the tidyverse (dplyr, tidyr, ggplot2)
- Dataframe manipulation with dplyr and tidyr
- Creating Publication-Quality Graphics with ggplot2
- Producing reports
Speaker: Dr. Andrea Bedini
Title: The Blockchain – A gentle introduction.
RSVP: Please register via Eventbrite by COB Monday 10 July 2017
In his presentation, Dr Bedini will offer a gentle introduction to the concepts behind the blockchain, answering the three big questions that arise with any new technology: What is it? How does it work? And why do we need it?
The blockchain is the disruptive technology at the base of Bitcoin, the world’s first decentralised cryptocurrency. It has received media attention and the public discussion has some enthusiasts claiming that the blockchain is the biggest invention since the emergence of the Internet.
The blockchain’s ground-breaking innovation lies in allowing people to safely conduct transactions electronically without the requirement of a trusted third-party. From its first application in the financial industry, this technology is now finding applications in many other industries such as real-estate, law, energy, and even music.
Andrea Bedini obtained his PhD in theoretical physics from Milan University and has been a Research Fellow at the School of Mathematics and Statistics of the University of Melbourne. His research included mathematical combinatorics, statistical physics, genomics and traffic flow modelling, and was supported by the ARC Centre of Excellence for Mathematics and Statistics of Complex (MASCOS) and the ARC Centre of Excellence for Mathematical and Statistical Frontiers Systems (ACEMS). Andrea is also an experienced software developer and has published scientific software packages to complement his academic publications.
He is one of the maintainers of PyTables, a Python library for managing large datasets. After 5 years in research, Andrea has decided that developing tools for research might be more exciting than research itself, and someone else should do the grant-writing. He has now joined the Curtin Institute for Computation as a data scientist/computational specialist assisting the Curtin Business School.
If you are interested in connecting with researchers across the university to talk about research and potential multi-disciplinary projects please come along to the CIC research morning tea. RVSP by 30 June 2017 via email to firstname.lastname@example.org
Weapons of Maths Construction: how a combination of maths theory and algorithms conquers inequalities and constructs optimal solutions.
Prof. Song Wang
RSVP: Please register via Eventbrite at this link by COB Monday 12 June 2017
Professor Song Wang received a B.Sc. from Wuhan University of Hydraulic and Electric Engineering, China, in 1982 and a Ph.D. in Numerical Analysis from Trinity College Dublin, Ireland, in 1989. He worked with a Dublin-based hi-tech company -Tritech Ltd., The University of New South Wales, Curtin University of Technology and The University of Western Australia, before returning to Curtin University in July 2014 as Professor and Head of Department of Mathematics & Statistics. His research interests include numerical solution of PDEs, numerical optimization and optimal control, optimum design and computational finance. He has published many research papers in these areas and his early work on numerical solution of semiconductor device equations of the drift-diffusion model has been featured in a review paper and a book chapter published respectively in a top journal Reports on Progress in Physics and a volume of the prestigious book series Handbook of Numerical Analysis. He is currently on the editorial boards of several international journals.