Michael Green

Machine Learning


Aarhus University
Peter Bøgh Andersen Auditorium
Finlandsgade 23, Nygaard-bygningen
8200 Aarhus N


16:30 Doors open
17:00 Welcome and Presentation, part 1
17:45 Break
18:00 Presentation, part 2
19:00 Meetup ends

About the talk

In a world where deep learning and other massively scalable perception machines are at our disposal, allowing us to build amazing applications, the time is now ripe to move beyond the concept of pure perception and into broader Artificial Intelligence (AI). The path towards AI goes through what’s missing in many applications today; Inference. Only when we combine Inference machines and Perception machines can we truly talk about AI. The benefit will be a machine that knows what to expect before observing it’s environment and that can take prior information into account. With ever more mature Probabilistic programming languages available, we can express this marriage of perception and inference. In this talk we will scrape the surface of how to build Bayesian predictive inference machines using Probabilistic programming.


Spawned in the Swedish Special Forces, bred in Theoretical Physics, hardened in Finance and softened in Marketing; Dr. Michael Green has developed, tested and deployed statistical machine learning models for a wide range of products over the last 15 years to help people make smarter and faster decisions with confidence.


He’s the inventor of the Artificial Intelligence engine deep within the Blackwood Seven AI media platform responsible for the quantification and decision making in their internal processes. Dr. Green’s background is somewhat nontraditional in the media world as he has a doctorate in Theoretical Physics where his research was primarily focused on emerging complex systems. It didn’t take long before he realized the commercial potential for AI.


He started out building Deep Artificial Neural Networks for helping physicians detect acute coronary syndromes in the emergency departments in Swedish hospitals saving 4% more lives while reducing costs by 40%. After that he spent a couple of years in the financial sector developing the statistical foundation for a business intelligence software that allowed banks and asset management companies to calculate the amount of money they stood to lose on a given trading day. He later traveled the EMEA region installing and evangelizing this software in major asset management companies. The last 7 years he’s been in the media and marketing industry developing and refining machine learning and AI methods together with Bayesian inference to quantify the effect different activities have on hard core KPI’s like sales.


In his spare time he enjoys running and has participated in multiple marathons over the years. In addition he teaches and practices Martial Arts which helps maintain a healthy work-life balance. Currently, he holds the 3rd degree Black belt in Karate.