Abstract: 

Exploring available open-source reinforcement learning tools and insights on how to go from research to production.

Bio: 

During her Bachelor of Economics in Buenos Aires, Argentina, Maggie learned to see the world from the lens of mathematics and statistics. She then started teaching herself how to code out of curiosity, got a job as a Junior Software Engineer in Sydney, Australia, and went on to do a Master of Software Development to further develop her skills. She completed her Masters degree with a research project involving some cute Pepper robots at UTS’ Social Robotics Lab - which won RoboCup’s Home category in 2019.

Throughout the years, Maggie has dipped her toes in various industries, from business development and digital marketing at Google to not-for-profit, banking, autonomous vehicles and more recently quantum technology. She has practical experience applying deep reinforcement learning techniques to quantum control problems and then deploying her research to production for customers to enjoy.

Maggie is involved with various nonprofits that teach coding to people of all ages, with a focus on teenage girls. She suspects that if she had had that level of exposure to computer science during high school, it would have captivated her right away. That’s Maggie's wish for future generations - but she also reminds us that it's never too late!