Organizers

Shadow is currently a manager of Produt Data Science at Moloco, working on optimizing the ads bidding efficiency of its DSP (demand side platform) product and helping advertiser find the right user on the open internet. Before joining Moloco, she spent 5 years at LinkedIn. Her main focuses at LinkedIn were in the go-to-market problem space, including optimizations of marketing targeting, sales planning, sales outreach productivity and omni-channel efficiency. She led a series of customer journey related initiatives that maximizes the LinkedIn business efficiency and profitability via machine learning, causal inference and experimentation.  

Mert leads the Search Verticals and International Growth DS team at Google where he focuses on new search products to find product market fit and achieve scale. Customer journeys are central to Google’s product approach. Previously,  Mert was the VP of Marketing Science, Analytics and Performance Product at GoodRX and held similar roles at Noom and Uber 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. Mert has published over 20 research papers and received over 1000 citations. He received his Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign.

Zhenyu is the Technical Director of Data Science at Roblox, with a focus on recommendation algorithm evaluation and optimization, content exploration, and LLM evaluation. Previously, he worked as Head of Data Science at Tencent Global Games and Tech Lead at Uber platform team. He has experience in experimentation, causal inference, modeling, product analytics, and data platform solutions. He co-founded CausalML open-source project, which is focused on providing complementary and practical solutions for causal learning, such as uplift modeling and observational causal inference.

Brad is the head of Growth Data Science at Pinterest. His team specializes in solving challenging data science problems related to user acquisition, onboarding, retention, paid marketing and forecasting. Previously, he led the Search Data Science team at Airbnb where he spent 7 years focused on improving search ranking, personalization, and marketplace optimization. Prior to that, he was at Apple working on query understanding for Maps Search. He has multiple publications at top tier conferences, including KDD and The Web Conference. Brad received his PhD in Statistics from North Carolina State University. 

Anbang Xu is a Director of Machine Learning 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 3,300+ citations. He received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.