Keynotes

In this keynote, Dr. Maxime Cohen shares how Generative AI can reshape pricing decisions across industries. Drawing from large-scale experiments involving hundreds of thousands of products and multiple large language models (LLMs), the presentation highlights critical findings on differences in pricing across LLMs, the impact of prompt design, and the ethical implications of bias and discrimination. Dr. Cohen also explores the competitive consequences of AI-driven pricing and the potential for automating MLOps with GenAI. Real-world examples from real estate, used cars, fashion, and gig work reveal the transformative—and sometimes troubling—power of AI in pricing.

BIOGRAPHY

Maxime Cohen is the Scale AI Chair Professor and the Academic Director of the Bensadoun School of Retail Management at McGill University. He is the Chief of AI Strategy of the CIUSSS West-Central Montreal (Jewish General Hospital) and the Scientific Director of the non-profit MyOpenCourt.org. He is also a Scientific Advisor in AI at IVADO Labs, and actively advising corporations, retailers, and startups on topics related to pricing, retail, and data science. Before joining McGill, Cohen was an Assistant Professor of Technology, Operations, and Statistics at NYU Stern and a Research Scientist at Google AI.

Cohen’s expertise lies at the intersection of data science and operations. He has worked on retail, ride-sharing, airline, sustainability, cloud computing, online advertising, peer-to-peer lending, real estate, healthcare, and conflict analytics, in addition to collaborating with many companies including Google AI, Microsoft, Meta, Uber, Waze, Amazon, Expedia, Oracle Retail, IBM Research, Via, Spotify, Aldo Group, Couche-Tard/Circle K, Loblaws, Canadian Tire, L’Oréal, Cargo, and Staples. He has also served on the advisory board of several startups. In each project, Cohen worked closely with the company to develop solutions using tools such as machine learning, deep learning, optimization, stochastic modeling, econometrics, and field experiments. More recently, he worked with hundreds of physicians and business managers to guide them on how to responsibly adopt GenAI tools and customized AI agents to boost their productivity.  Cohen’s research and teaching have received 40+ awards.

Enterprises have long pursued technologies to enhance decision-making, yet innovations such as search and knowledge graphs often gained traction in consumer markets before achieving widespread enterprise adoption. The reason is clear: enterprise knowledge is fragmented, domain-specific, and mistakes carry high stakes. Large language models (LLMs) are changing that equation. More than another tool, they open new ways to build, query, and apply knowledge across domains such as legal, finance, and customer experience. With this opportunity comes new challenges—trust, reliability, and governance—that will define the next generation of intelligent enterprises. In this keynote, Yunyao Li will explore how LLMs are reshaping enterprise decision-making and what it will take to move from experimentation to transformation.

BIOGRAPHY

Yunyao Li is a Director of Machine Learning at Adobe Experience Platform (AEP), where she leads strategic initiatives such as AEP Agent Orchestrator to bring the power of Generative AI and Knowledge Graph to enterprise systems. Previously, she was the Head of Machine Learning at Apple Knowledge Platform. Before joining Apple, she was a Distinguished Research Staff Member and Senior Research Manager at IBM Research – Almaden. She is particularly known for her work in enterprise search, and database usability. In these areas, she has published over 100 peer-reviewed articles, been granted 36 patents, created and taught multiple graduate-level courses, co-authored two books, and won many awards for her technical and leadership contributions. She is an ACM Distinguished Member, a member of the inaugural New Voices program of the American National Academies, and a “Young Scientist” by World Laureates Forum (2019). She was selected as a member of the North American Chapter of the Association for Computational Linguistics (NAACL) Executive Board (2022-2024). In addition, Yunyao also serves on advisory boards for university programs, an an organizer and senior committee member for top conferences, and on editorial boards. She received her undergraduate degrees from Tsinghua University, and her masters and Ph.D. degrees from the University of Michigan – Ann Arbor.