Speakers: Gary Bogdani, Head, Collective Intelligence at Unilever, Jing Guo, Forecasting Data Science Product Manager at Unilever and Dr. John Armitage at Larus Technologies.
Moderator: Professor Chi-Guhn Lee, Professor of Industrial Engineering, University of Toronto.
Abstract: In this talk, we will be sharing about Unilever’s AI-driven decision support systems (DSSs) for trade investment optimization — Lumos ML. Trade investment optimization is crucial for driving profitability across Unilever’s vast portfolio with more than 1500+ products selling across major ecommerce and retail chains. Lumos ML turns vast amount of raw data into actionable trade investment recommendations that are easy to understand and act upon by business users. In this talk, we will be providing an overview on the trade-optimization challenges, the ML & multi-objective optimization methodologies, building trust with the business, and the DSSs for the use case of trade investment optimization within Unilever Canada.
Speakers Bio
Gary Bogdani – Head, Collective Intelligence, Unilever – Gary has a Bsc in Chemical and Industrial Engineering from University of Tirana Albania, with numerous certifications and licenses in the space of software engineering and architecture from reputable organizations such as Microsoft, Sun Microsystems, Oracle, MIT Sloan School of Management, Queens U Smith School of Business etc. Gary is a member of both University of Toronto’s SOSCIP and IMDA board of advisors. He has more than 20 years technology and business experience, 17 of them spent in various progressive positions at Unilever Canada and Unilever North America. Gary leads the ULC Collective Intelligence team with an expanded enterprise data, capabilities and AI/ML agenda. As a leader in developing AI/ML strategy for Unilever Gary has engaged with several Canadian partners in building Unilever’s data science program and talent pipeline.
Jing Guo – Forecasting Data Science Product Manager, Unilever- Jing holds an Msc in Industrial Engineering from University of Toronto with several years of experience in building ml driven solutions. As part of CI team at Unilever Jing is leading the data science work for both demand forecasting and pricing workstreams. During 2020 Jing was actively engaged in a global team of Unilever data scientists that formulated and applied forecasting model improvements in 10 major Unilever markets (countries), to reflect Covid related effects.
Dr. John Armitage, Larus Technologies received his Ph.D. degree in Physics Optoelectronics from the University of Cambridge (UK) in 2019. He brings over eight years of Artificial Intelligence (AI) and Machine Learning (ML) practical experience. He has published 4 journal papers, 1 patent. Dr. Armitage brings a wealth of technical expertise accumulated over 10 years of post-secondary education in the field of information fusion, AI/ML and predictive analytics.