The Women in Machine Learning Program Blog Series Part 5 – Georgie Kennedy

We are publishing a blog series on the brilliant women we had involved in the Women in Machine Learning program last year.  

Whoever you are, and whatever your background we are sure you will find their thoughts on Machine Learning, inclusion and their stories inspirational and inspiring.  

Georgie Kennedy

With a duel background in bio-med and software, Georgie spent over 8 years as a software consultant in health services. She is now settled into a PhD at UNSW with the Center for Big Data Research in Health.

My background is in biomedical engineering, and I have worked professionally in a healthcare setting as a software developer and consultant for a number of years.  When I took some time off for maternity leave, for a number of reasons I decided to head back into the academic world – in particular, I was mindful of my priority to maintain a relevant set of skills that would allow me to work on problems that I found exciting and engaging.

There is plenty out there that shows that medical data is ripe for machine learning applications – it’s clear that with the right tools, we have the capacity to produce clinically relevant predictions and insights. Demonstrating this is only the first step in a long journey to getting these tools settled into a comfortable relationship with patients and clinicians, however.  It’s obviously totally appropriate to set an extremely high bar for explainability, usability, and trust in a setting like this, which can be offputting I guess, but I prefer to look at this as an opportunity which means that there are tonnes of interesting problems to be tackled.

The Women in Machine Learning program came at a great time for me in my research – I’d done a bunch of self-directed learning, but honestly, nothing beats getting your hands onto some data and working with a team to actually build things.  I’m grateful for the opportunity to sit with not only the experienced instructors but also a really interesting group of women and spend time learning and sharing skills. A PhD can be an isolating time in some ways, and I’ve really missed that shared problem-solving.

I’m looking forward to helping my 2 girls feel comfortable in the world of technology to whatever level they are interested…it’ll be a while before I can really wow them with my calculus skills (they’ve gotta start school first!), but I’m as confident as you ever can be that between me and their early childhood educator of a father, they won’t get any silly ideas about what girls ought or oughtn’t be interested in. 

Do you or your company what to support the Women in Machine Learning  program in 2019? Register your interest here. 

We will be opening applications for the Women in Machine Learning  program later in 2019. Register your details here to be amongst the first to apply.

Interested in a career in Machine Learning? We are hiring, check out our current openings here.  

Did you enjoy reading Georgie’s post? Check out the rest of our Women in Machine Learning blog series…

Part 1
Part 2: Ayesha
Part 3: Ashley
Part 4: Genevieve

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