Organizers

Shadow (Hongying) Zhao is currently a tech lead / staff data scientist at Moloco, solving challenging problems in the ad-tech ecosystem and optimizing the performance of its DSP (demand side platform).

Previously, she spent 5 year at LinkedIn. Her main focuses were in the go-to-market problem space, including optimizations of marketing targeting, sales planning, and sales outreach productivity. She has been leading a series of customer journey related initiatives that maximizes the LinkedIn business efficiency and profitability via machine learning, causal inference and experimentation. 

Mert is the VP of Marketing Science, Analytics and Performance Product at GoodRX solving data science challenges on growth marketing, strategy and finance related to increasing customer value, revenue, optimizing cost-of-acquisition by building data solutions for financial planning and forecasting, measurement and optimization across investment levers and audiences for paid & owned acquisition, re-engagement, retention and win-back, pricing using analytics, machine learning, predictive modeling, mathematical optimization and causal inference methods.

Anbang Xu is a Senior Manager at NVIDIA. He leads a Machine Learning team to develop enterprise AI solutions. His research is a mix of Applied Machine Learning and HCI. He is the Associate Editor of ACM Transactions on Interactive Intelligent Systems. He has published 50+ research articles and 25+ patents and received 2,700+ citations. He received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.

Neha Gupta is Director of AI at Uniphore. Before joining Unihpore, Neha grew her career via time at companies such as Common Room, Linkedin, Uber and Adobe working on challenging problems ranging from personalization, recommendations, forecasting and go-to-market ML.  Neha graduated with her Ph.D degree in Computer Science from University of Maryland, College Park. She has several publications in top tier conferences and has chaired two prior workshops on Offline and Online evaluation of ML Systems  in KDD (2019) and WWW (2015).