We had the opportunity to quickly catch up with Dr. Denis Bauer. She will deliver a keynote titled – Life Science Research at Scale and a full day workshop titled – Crunch Data and Deploy Serverless Architecture the Smart Way (Register)

What got you into Data Science/AI?
The human genome was decoded when I started Uni, this has sparked my interest and excitement around analysing the 3 billion letters that our genome is made of. With this much information just eyeballing the information does not work and even some statistical methods are breaking down, which is why I started on Machine Learning and AI.

What is most exciting for you in Data Science/AI?
With the recent explosion in readily available compute, it has never been easier to train highly complex machine learning models. It is hence incredible exciting to be able to answer questions around health that before were deemed to complex or even impossible to answer.

What do you think is the biggest challenge faced by Data Scientist today?
It has become incredibly difficult to evaluate novel tech at the speed it is released, at the same time it has never been more critical to prioritize approaches to maximize your return on investment and stay competitive. For us the hypothesis-driven approach to specifically cloud architecture evaluation has worked well. We have summarized this approach in a recent article

What do you think is the biggest obstacle for Data Science/AI adoption?
The biggest obstacle is an incomplete education or rather the advertisements from vendors of expert-free AI. AI/Machine Learning has the issue of producing misleadingly good results during training/testing if this is not performed correctly. Therefore, more than any other analytical or statistical model, a seemingly outstanding model may in fact be overfitting your trainings data and does not provide the general insights you assume it has captured or is not accurately predict on new data, so will perform poorly during application/production. This threatens adoption because it may corrode trust in the robustness of the generated ML/AI models, not because the technology is not capable but because it was not performed and assessed by an expert.

Which is your favorite session at ODSC India that you looking forward to attend?
Favio VázquezDeep Learning with Apache Spark

You are traveling all the way from Sydney. What got you interested to present at this conference?
This is the nearest ODSC for me

Any personal message/remarks you want to share with the DS/AI community in India?
I was so impressed with the expertise and dedication to novel IT practices of the Agile India attendees. I am therefore looking forward to learning equally much from the DS/AI community in India and hope to set up mutually beneficial connections going forward.