Sydney Hacky Hour

Sydney Informatics Hub are hosting their own Hacky Hour!

Hacky Hour is a regular meet-up where researchers can congregate to collaborate, and get research help in a social environment. Experts will be on hand to advise on problems related to coding, data analytics, or digital tools, with knowledgeable folk from SIH and other departments who can help you with your questions.

Hacky Hour has been successfully replicated at other universities such as UTS, Melbourne, Griffith Univeristy and The University of British Columbia.

Come to a session!

How do you get involved? Just show up. If you have a laptop or tablet, bring it along so you can show what you’re working on. We have bioinformaticians, computer scientists, data scientists, data strategists, research computing and digital tool specialists, and other mentors on call to give you a hand with your problems. Check who’s rostered this session.

If you have a specific question you’d like to discuss, let us know before the session so we can find an appropriate mentor.

Hacky Hour moves around campus and visits our satellite campuses too. Next session details:

Time and Date:

3-4pm, Thursday 11th April 2019

And a special guest talk straight after Hacky Hour

Sean McMahon presents his PhD in Robotic Vision 4-5pm

Sean is a PhD candidate from the Australian Centre for Robotic Vision, he has helped run and organise numerous deep learning and machine learning courses, ranging from beginner to advanced.

He will be presenting his PhD in robotic vision about training a deep neural network to detect hazards on construction sites. Sean will share his experiences as a senior mentor at Queensland AI, where he ran multiple courses on deep learning. One of the interesting things about detecting hazards is that they are not defined by a single type of object, for example, a ladder on the ground is trippable, but not when it is leaning against a wall. Here, the ladder’s affordance, or its action possibilities, change depending on how it is placed in the environment.

Over the course his PhD, Sean had to collect and label his own datasets before training the Convolutional Neural Networks (CNN), encountering many difficulties and gaining intuitions into how to train a CNN from custom data.


ThinkSpace (Upstairs from the SciTech Library)

Level 2 - Jane Foss Russell Building G02

Get in touch with us at if you would like to host a Hacky Hour at your research group!

People come to Hacky Hour for many reasons:

  • Get advice on how to best collect and manage your data
  • Have someone to show you the basics in R.
  • Learn the best way to show some spatial data on a map.
  • You recently attended an Intersect training course and want more help using tool ‘X’.
  • Your honours student is pestering you to use version control and need help getting started.
  • You need to get a huge dataset from a colleague overseas as quickly and easily as possible.
  • You’d like a friendly environment to hack away at your data-crunching scripts, and maybe pick up a collaborator.

Even if you don’t have any problems you want solved, come along to:

  • Network and chat with other like-minded researchers.
  • Help solve someone else’s problem.
  • Wrangle your data in the presence of others like-minded.
  • Run your own special-interest data or analytical groups nearby and reach a wider audience.
  • Help a colleague overcome their fears of using Git.
  • Show off a really useful tool you just discovered.

We will be running some mini-workshops in things like Jupyter Notebooks, ParaView, MATLAB, visualisation, and docker in the weeks to come. Stay tuned for more details.

If you’re interested in training in anything particular please let us know by filling out this survey.

BMC Hacky Hour

Meet the mentors

Each Hacky Hour will be staffed by a variety of mentors and experts in different areas. Check below to see who’ll be around at the next session:

Next session: ThinkSpace

Nicholas Ho Nicholas Ho – Data Science

Machine learning · Transcriptomics · R · Bioinformatics · Health

Darya Vanichkina Darya Vanichkina – Data Science

Bioinformatics · Genomics & Transcriptomics · Machine learning · Health · Python · R

Nathaniel Butterworth Nathaniel Butterworth – Research Computing

Visualisation · Python · Artemis HPC · Argus Research Desktops · Astrophysics · Geophysics

Emily Neo Emily Neo – Econometrics

Time series · Financial/risk analysis · R · SQL · Scala · Spark

Christopher Howden Christopher Howden – Statistician

Statistical Methods · Statistical Design

Madhura Killedar Madhura Killedar – Data Science: Statistics

Bayesian modeling · Simulation · Machine learning· R · Python · Astrophysics · Cosmology

Kayla Maloney Kayla Maloney – Visualisation

Data visualisation & communication · Design · Geoscience

Olya Ryjenko Olya Ryjenko – Data consulting

Digital research tools · eNotebooks · Data capture and surveys · Speech Pathology · eHealth

Upcoming sessions: ThinkSpace (11 April), Physics (May), and beyond…

Rosemarie Sadsad Rosemarie Sadsad – Bioinformatics

Phylogenetics · long/short read DNA sequence analysis · Metagenomics · Pipelines · Modelling & Simulation · Bioinformatics & Genomics · Infectious Diseases · Health Systems

Tracy Chew Tracy Chew – Bioinformatics

DNA/RNA sequence analysis · Association analysis · Animal genomics · Veterinary science

Creative coding · Data visualisation · Design thinking · Psychology · Educational Design · UX · Web development

David Kohn David Kohn – Data Science: Bayesian modeling

Bayesian modeling · Python · R · Matlab · Stata · SPSS · SQL · Machine learning · Web

Gordon McDonald Gordon McDonald – Data Science

Simulation · Machine learning · Bayesian statistics · Physics · Chemistry · R · Matlab

Software Engineering · Data Science · Applications · Web development · Databases · Python · R · Scikit-Learn · SQL · Java · AWS · Hadoop · HTML · CSS · JavaScript · GIT · Jira · Web · Security · Accessibility

Aldo Saavedra Aldo Saavedra – Senior Research Scientist

Statistical Methods · Machine Learning · eHealth · Data Science · Physics

Srdjan Luzajic Srdjan Luzajic – Data Centre Networking

Core networking · Moving big data · Firewalls & DMZ

Find contact details for Hacky Hour trainers or drop us a line at

Usyd Hacky Hour is brought to you by..