Women in AI Dinner schedule

Marieke is an investor at Octopus Ventures. As a former Growth investor, she works with several later stage startups in the OV portfolio and leverages her network and experience to source B2B opportunities such as Glofox and Ometria. Marieke serves on a number of investee company boards including CB4, Conversocial, Glofox, Ometria and OpenSignal.

When not meeting founders or working with her portfolio companies, Marieke is most likely to be found snowboarding or climbing in the Alpes or on her yoga mat.

AI for Spoken Communication

Do you want to know how chat bots like Amazon Alexa works? Why does Alexa understand what you say and how does she know what to answer? In this event we will discuss AI building blocks that Alexa has and what kind of improvement does AI provide in contrast to rule-based solutions

Elena is a manager in Applied Science in Amazon Alexa, working on developing new algorithms for natural language processing and speech. Before coming to Amazon, Elena made her PhD in Machine learning in the university of Nijmegen, the Netherlands. She also worked in Booking.com leading a team that was developing chat bot for Customer Service department.

From 100 Billion Neurons to 200 Billion Tweets

Cortex is the core Machine Learning organisation within Twitter. With a portfolio of research projects ranging from real-time personalisation to graph learning and geometric deep learning, Applied Research offers a unique ecosystem that fosters the exploration of new challenges around recommender systems, content understanding and representation learning. In this talk, I’m going to expand on some recent challenges that we tackled.

Ira Ktena is a Machine Learning Researcher with the Cortex Applied Research team at Twitter UK. She completed a Doctoral degree in Medical Image Computing at Imperial College London, where her research focused on developing methods for modelling graph-structured neuroimaging data using traditional graph theoretical approaches and geometric deep learning. During that time she visited Massachusetts General Hospital, Harvard Medical School to implement ML models for Neurology applications. She previously worked on audio generative models as a Research Intern at Spotify.

AI for Health

AI techniques have made it in our everyday lives. However they are not yet included in some critical aspects of our society, like healthcare. In this talk, I will review some of the recent applications that our team has developed to bring these methods to clinical practice and display their potential to transform healthcare.

Jessica received her PhD in Electrical Engineering from the University of Liège, Belgium, in 2013. She was a post-doctoral researcher at the Laboratory of Behavioral and Cognitive Neuroscience, Stanford University before obtaining a Marie Curie fellowship with University College London. Her research applied machine learning techniques to neuroimaging data (both cognitive and clinical neuroscience) and investigated the limitations of such models, especially in terms of interpretation. She is now a Research Scientist at Google Health where I continue investigating the use of machine learning techniques for healthcare. As one of the few women in Engineering, she has been sensitised to diversity issues in her field and has been advocating for women in science.