Show Notes

Many data scientists dream of using their skills to develop ground-breaking AI technology. Yet, few manage to translate their dreams into commercially viable products – or even know where to begin. 

In this episode, start-up founder Dr Jeroen Vendrig joins Dr Genevieve Hayes to discuss his experiences in developing AI-driven products, both in an academic setting and in a variety of organisations within the commercial world.

This is the first part of a three-part special focussing on the use of data science in start-ups.

Guest Bio

Dr Jeroen Vendrig is the Chief Technology Officer of ProofTec, an Australian technology start-up specialising in the development of AI-driven software for damage detection and assessment of high value assets. He has over 20 years’ experience in video analytics with world leading R&D labs and has over 25 patents in force.

Talking Points

  • The key differences between doing data science/AI in an academic setting and doing it in the commercial world.
  • How to go about translating academic research into commercially viable AI-based products.
  • What makes for a successful university/commercial collaboration?
  • The challenges of building AI products from scratch, including lack of data and how to tell if a project has the potential to be commercially viable.
  • Protecting IP for AI systems.
  • The impact of having real end users on AI product development.
  • The most valuable skills data scientists can develop for building commercial AI technologies.


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Value Driven Data Science
Episode 18: Making AI Commercially Viable