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Explainable Artificial Intelligence: How to hold machines accountable?

August 13, 2020 @ 5:00 pm - 6:30 pm PDT

Hosted by Stella M. and Nazanin Z.

Join us to know more about Explainable Artificial Intelligence with speakers from Intuit and NVIDIA. Hear technical talks from women in AI about how they apply state-of-the-art methods to make AI more explainable and accountable. All are welcome to attend, feel free to share the session and join at 5pm PDT.
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Diane Chang serves as Distinguished Data Scientist at Intuit, where she powers the prosperity of consumers and small businesses with machine learning, behavioral analysis, and risk prediction. Diane initially worked on TurboTax, looking at the effectiveness of our digital marketing campaigns, understanding user behavior in the product, and analyzing how customers get help when they need it. She also helped launch QuickBooks Capital, predicting outcomes for loan applicants. She is currently applying AI/ML techniques to security, risk and fraud. Diane has a PhD in Operations Research from Stanford. She previously worked for a small mathematical consulting firm, and a start-up in the online advertising space. Prior to joining Intuit, Diane was a stay-at-home mom for 6 years.

Siddha Ganju, an AI researcher who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. As an AI Advisor to NASA FDL, she helped build an automated meteor detection pipeline for the CAMS project at NASA, which ended up discovering a comet. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices. Her work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN’s petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS. She has served as a featured jury member in several international tech competitions including CES. As an advocate for diversity and inclusion in technology, she speaks at schools and colleges to motivate and grow a new generation of technologies from all backgrounds. She is also the author of O’Reilly’s Practical Deep Learning for Cloud, Mobile and Edge.

Nazanin Zaker is a senior data scientist at Intuit AI working on document understanding. Prior to that she focused on deriving actionable insights and explainability for the financial status of the QuickBook Advance (QBA) customers. She applied time series models in order to extract the trend and seasonality patterns of different Key Performance Identifiers of QBA customers. In the past years, she worked as an AI researcher in companies like Motorola (A Google Company), Cisco and SAP. She was a research assistant during PhD and master program focused on solving pattern recognition problems in vision and signal processing. She is an advocate for women in tech, founder of Women in AI at Intuit and recognized as influencer of the year in Women in Big Data (WiBD) in 2018.


August 13, 2020
5:00 pm - 6:30 pm PDT