We bring together practitioners and researchers in the Information Retrieval domain to promote knowledge sharing and innovation across academia and industry. This Industry Day of ECIR 2024 will be held on Thursday March 28th 2024 in Glasgow, UK, immediately after the main conference program.
Confirmed Industry Day Speakers:
Ben AllisonApplied ML Scientist at Amazon
Ben is a machine learning scientist that was worked across a range of applied ML problems at Amazon and beyond. He currently runs the ad serving and monetization org for Amazon’s performance brand advertising products. He got his PhD from the University of Sheffield in Machine Learning and NLP before doing a post-doc at the University of Edinburgh. Since coming to Amazon he’s worked in catalog, personalization, and now ads for the last 5 years. He enjoys multi-disciplinary challenges and collaborations that span machine learning, statistics, causal inference and optimization and has worked extensively on Deep Learning, Reinforcement Learning, NLP and Recommender Systems as well as the core ad tech problems.
Mounia LalmasSenior Research Director at Spotify
Mounia Lalmas is a Senior Director of Research at Spotify, and the Head of Tech Research in Personalisation, where she leads an interdisciplinary team of research scientists, working on personalization. Mounia also holds an honorary professorship at University College London. She also holds an additional appointment as a Distinguished Research Fellow at the University of Amsterdam. Before that, she was a Director of Research at Yahoo, where she led a team of researchers working on advertising quality. She also worked with various teams at Yahoo on topics related to user engagement in the context of news, search, and user-generated content. Prior to this, she held a Microsoft Research/RAEng Research Chair at the School of Computing Science, University of Glasgow. Before that, she was Professor of Information Retrieval at the Department of Computer Science at Queen Mary, University of London. She is regularly a senior programme committee member at conferences such as WSDM, KDD, WWW and SIGIR. She was programme co-chair for SIGIR 2015, WWW 2018 and WSDM 2020, and CIKM 2023.
Ed H. ChiResearch Scientist at Google Deepmind
Ed H. Chi is a Distinguished Scientist at Google DeepMind, leading machine learning research teams working on large language models (LaMDA/Bard), neural recommendations, and reliable machine learning. With 39 patents and ~200 research articles, he is also known for research on user behavior in web and social media. As the Research Platform Lead, he helped launched Bard, a conversational AI experiment, and delivered significant improvements for YouTube, News, Ads, Google Play Store at Google with >660 product improvements since 2013.
Prior to Google, he was Area Manager and Principal Scientist at Xerox Palo Alto Research Center‘s Augmented Social Cognition Group in researching how social computing systems help groups of people to remember, think and reason. Ed earned his 3 degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota. Inducted as an ACM Fellow and into the CHI Academy, he also received a 20-year Test of Time award for research in information visualization. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press. An avid golfer, swimmer, photographer and snowboarder in his spare time, he also has a blackbelt in Taekwondo.