David B Dean

Machine Learning Researcher and Software Engineer

About me

I’m a machine learning leader, researcher and data engineer with 19+ years of experience in developing and improving state-of-the art machine-learning research algorithms and turning them into useful, reusable code that can make life easier for researchers, software engineers, and everyone else!

I’m a Data Science Leader

I’ve led the Learning Analytics Team at TAFE NSW for 5 years, helping grow the ability of TAFE NSW to take a data-science approach, including prototyping and evaluating AI and ML techniques, to improve the learning experiences for vocational training across the entirety of TAFE NSW.

I have enjoyed supervising PhD students in the past and have done occasional seasonal academic work.

Throughout 2017, I worked with the University of Queensland developing an exciting new Masters of Data Science, and I enjoyed developing datasets and teaching material that helps in the training of future professional data scientists.

I have also done some mentoring with CoderDojo Brisbane, and helping kids get excited about coding is pretty awesome.

I’m a geospatial enthusiast and OpenStreetMap evangalist

When I was still in Brisbane, I ran local events for the OpenStreetMap community. So, if you came here looking for OpenStreetMap events in Brisbane, please go have a look at the Brisbane Events Page on the OSM Wiki to see if something is happening.

Armidale is a bit quiet for this sort of thing, but it would be great to get similar events running here.

I’ve been an OpenStreetMap member since 2007, and was responsible for a lot of the original mapping and social events in Brisbane, Australia. I’m seeking to apply my AI and machine-learning experience into GIS applications that can help the OpenStreetMap community.

I’ve worked in medical machine learning

In the past, I have done some machine-learning consultation work with two exciting medical machine-learning start-ups, Wink Health in California, and M3dicine in Brisbane. It’s great to be able to help medical professionals and the general population to get access to improved health care through innovative signal processing and machine learning.

I’ve been a speech and video ML researcher

I have been working with audio-visual speech since 2004, and loved showing that visual information is almost always complementary to acoustic over a wide range of applications.

A large part of my post-doctoral experience focused on conducting research, development and commercialisation of state of the art speaker recognition and diarisation research.

I have publications

As of March 2023, I have 1,664 citations across more than 90 publications, with 44 publications having more than 10 citations, and a h-index of 21. More details, and a full list of publications can be found on my Google Scholar profile.

Publication venues include:

I’m looking for work

Feel free to download my résumé, or visit my LinkedIn. Get in touch if you have something interesting in mind!