Panel: The Purpose of Machine Learning

Thomas van Heyningen

Thomas is an enthusiastic and practical data scientist. He is always finding ways to integrate data science into business processes. Approaching each use case with a fresh sense of curiosity, figuring out the process and problem at hand. Working as a data science consultant in The Netherlands, Thomas has seen common pitfalls and their resolution in several companies.  

Assuring business results get achieved from the sometimes-murky water of data science projects.

Nicholas Mitchell

Nicholas is a Machine Learning Engineer at Argo AI, solving the task of perception for autonomous vehicles. He is also a part-time researcher, completing a Ph.D. in cross-domain applications of AI.

Jendrik Jördening

Jendrik is Head of Data Science at Nooxit. He formerly worked at Aurubis and Akka Germany on Data Science and Deep Learning in the field of industry 4.0 and autonomous machines.

At the same time he took part in the Udacity Self-Driving Car Nanodegree, participating with a group of other Udacity student in the Self-Racing Cars event at the Thunderhill race-track in California.

There, the group of students taught a car to drive around every turn of the race track autonomously. 

Diana Hu

Diana currently is advising startups and angel investing. Previously she was the head of the AR platform at Niantic. She led the AR teams building the core AR tech used in games like Pokemon Go and Harry Potter Wizards Unite. 

Previously, she was the Cofounder and CTO of Escher Reality, a startup that was acquired by Niantic. Escher Reality builds the backend for Augmented Reality applications. In the past, Diana led data science teams to bring research projects into products for cloud television at Intel and Verizon Labs. She holds seven patents in computer vision and machine learning.