Women in AI Dinner schedule

At Alice, Courtenay Siegfried is a founding partner and VP of Communications and Impact. Alice (HelloAlice.com) was the first AI platform designed to help business owners find the right path to start and grow their companies. Prior to Alice, Courtenay lived the entrepreneur life as owner and president of 20K Group, a global communications agency. She also co-founded Launchpad Skills for Success, a training company specializing in emotional intelligence and business communications. Courtenay is active in her community and currently serves on the League of Women Voters of the Houston Area Board of Directors and Discovery Green Programming Committee.

Creating Applications That Converse, Understand and Become More Intelligent

Advances in natural language processing (NLP) are increasingly eroding the barriers between frictionless human-machine interaction, creating opportunities to develop nuanced and natural communication techniques that more accurately convey person-to-person dialogue. In this talk, I'll discuss how convolutional neural networks and long short-term memory networks are enabling more sophisticated NLP systems and building the necessary components to lay the foundation for advanced dialogue.

Margaret is a Vice President of Software Engineering for Conversational AI Platforms at Capital One. She sets the technology strategy for Eno, Capital One’s banking chatbot, as well as enterprise messaging capabilities for email, push and SMS. Margaret is also an advocate for closing the gap in women in technology as a member of Capital One’s Women in Technology working group. Margaret has been with Capital One for 20 years, in roles of increasing responsibility within Technology and Operations. She holds a BS in Operations Research & Industrial Engineering from Cornell University and her MS and PhD from Lehigh University in the same field. Prior to joining Capital One, she spent three years as an Assistant Professor at the University of Virginia, in Systems Engineering. Her research interests have been varied, but always along the common theme of using technology to solve complex business problems. Margaret is a board member of CodeVA.org and the Computer Science Industrial Advisory Board at Virginia Commonwealth University. Margaret lives in Richmond, VA with her husband and two teenage daughters.

The Sparse Data Problem in Machine Learning

This talk will include information about the difference between sparse data and missing data, how to increase model accuracy with sparse data and how deep learning compensates for sparse or missing data.

Giewee Hammond has an extensive mathematics background which she uses to resolve complex problems for Upstream E&P. She is a Lead Data Scientist for her division and has strategized and filled the need for constructing a productive advanced data analytics team to meet the demands of upstream advanced data analytics projects. She lectures and participates in Houston Data Analytics, a meetup which she founded in January 2018. She runs a not for profit named, Wahjay-STEM, which she uses to help schools adopt robotics as a part of their in-school curriculum. She is a committee chair for the Society of Petroleum Engineering Analytics study group and contributes to digital transformation efforts within the professional society. She highly values the importance of data preprocessing, data exploration, model validation and model interpretation. She holds the following master degrees: Actuarial Science and Analytics.

Machine Learning in Medical Imaging

Dr. Kanchi is a postdoctoral fellow in the Department of Diagnostic Radiology at the University of Texas MD Anderson Cancer Center (MDACC). Dr. Kanchi’s research focuses on the use of bioinformatics and machine learning methods in order to understand the diverse data types in cancer genetics. Her current work deals with learning from radiological image data such as MRI, PET and CT. Dr Kanchi is committed to a responsible conduct in research (RCR). As chair of the RCR subcommittee of the postdoctoral association at MDACC, she organizes monthly RCR lectures on various RCR topics and spreads awareness about performing research responsibly. She is strongly interested in bioinformatics, statistical genomics and machine learning.