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Startup Grind Adelaide is collaborating with AI Collaborative Network for our next event on Wednesday 12 September.
We have gathered 4 amazing speakers to share their work and ideas in Artificial Intelligence, Machine Learning and Data Science (with demos!), followed by a panel discussion.
More importantly, this is an opportunity for you to meet, network and make friends with people who have an interest in AI/ML/DS! We welcome people from all backgrounds and walks of life - not only technical and business people, but also those with a general interest in this growing field.
Tickets include food and drinks. Get your ticket now!
This event is proudly sponsored by Tyto.AI
AI Collaborative Network Adelaide
The AI Collaborative Network is an inclusive community of people that are interested in Artificial Intelligence, Machine Learning and Data Science, and how this affects the world today and in the future. We care about knowledge sharing, collaboration, and providing a fun space for people to come together, through local events and online community platforms.
We are always on the lookout for people who can come and share their work in AI/ML/DS, and we love demos! Get in touch on Slack, Facebook or email firstname.lastname@example.org
Want to support the community? We’re looking for people/groups who want to collaborate with us, or sponsors to help us continue to run awesome no/low cost events!
-------------------- Speakers --------------------
Dr. Katherine Enderling is a Senior Architect and Analytics Lead at LIFELENZ, a start-up company set up to reward and empower people in today's liquid workforce.
She leads a team of data scientists and software engineers building a cutting edge system to predict and organise complicated rosters, build people’s careers and deliver value from the resulting data.
Katherine has a PhD in Software Architecture from St Andrews University in Scotland and an honours degree in Maths and Comp Sci at Adelaide University. After her studies she worked at a bio-tech start up in Edinburgh and a semiconductor manufacturer in Austria. After a decade in Europe she moved back to Adelaide and started with Accenture Digital, building marketing analytics software. Katherine is passionate about encouraging more women to join this lucrative and interesting industry and is a member of the founding committee of HerTechPath.
Dr. Mark McDonnell is co-founder and CTO of Athlete’s AI. He completed a PhD in Electronic Engineering at University of Adelaide in 2006. Since then he has established a research laboratory in a South Australian university, that seeks new knowledge at the intersection of computational neuroscience, computer vision and machine learning. He has published over 100 scientific and engineering research articles and a granted US patent, and is regularly invited to speak at international conferences. Mark has worked extensively with local companies to deliver applied machine learning solutions across the agriculture, health, manufacturing and finance sectors.
Dr. Emily Hackett-Jones received her MSc at the University of Adelaide in subatomic physics, before moving to the UK to complete a PhD in theoretical and mathematical physics.
Emily's career has spanned both industry and academia, and a variety of different topics. After her studies in string theory, she returned to Australia in 2009 to begin research into biological systems and cell motion. She then spent five years working for Accenture as a data scientist, working in digital marketing, looking at how machine learning can aid business decisions.
Today Emily works as a Bioinformatician in the Centre for Cancer Biology at the University of South Australia. She analyses data that comes from DNA sequencing experiments to better understand the mechanisms that drive cancer metastasis. As a regular speaker for ChooseMaths and HerTechPath, she actively encourages women to pursue STEM careers.
Thomas Rowntree is a Research Engineer at the Australian Centre for Robotics Vision (ACRV) and the Australian Institute for Machine Learning (AIML), both of which reside at The University of Adelaide. His focus is on Machine Learning, Computer Vision, and Robotics. He was on the ACRV team that won the Amazon Robotics Challenge 2017, a global competition aimed at pushing the boundaries of robotic perception and manipulation.
Dennis Liu is a PhD candidate at the University of Adelaide in the School of Mathematical Sciences. Having started in 2017, he is interested in developing models of disease outbreaks based on social media trends and vaccination rates. After working as a chemical engineer for nearly 4 years, Dennis returned to university to pursue a PhD in statistics and applied probability, and is interested in using data science and digital data streams to solve real world problems.
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The future of data science by Dr. Katherine Enderling
One challenging aspect of machine learning - even for experienced practitioners - is choosing the correct tools for a specific task. Anyone using machine learning must make decisions about everything from how to clean data, what features to extract or build or what learning algorithm to use. Recently, some groups have been looking to automate some parts of this process, or even the whole pipeline. This field is generally known as AutoML, and in this talk, Katherine will give a short introduction to an AutoML project out of MIT.
Athlete’s AI: Real-time video analytics in the hands of all athletes by Dr. Mark McDonnell
Video analytics is a powerful tool for athletes and their coaches. It can help improve performance by providing biomechanical analysis, match statistics and tagging of key events. However, current solutions require painstaking manual labelling and editing, and so are high cost, slow and provide limited insights. Athlete’s AI combines computer vision, machine learning and cloud computing to deliver three distinct advantages over our competitors: lower cost, faster real-time analytics, and further insights.
In this talk Dr. Mark McDonnell will provide an overview of Athlete’s AI’s tennis product, and demonstrate its capabilities in action. He will also describe some of the technical challenges that the team has solved by designing cutting-edge deep neural networks.
Big data and bioinformatics by Dr. Emily Hackett-Jones
Single cell sequencing is a hot topic in biology at the moment. It allows the genes in thousands of individual cells to be analyzed separately. This can be very helpful if you want to distinguish cancerous cells from normal tissue, for example. Alongside this new technology comes massive amounts of data, leading to great technical and scientific challenges and opportunities for applying new machine learning techniques. Emily will give a brief intro to this topic - no prior biology knowledge necessary!