Biography: Emine Yilmaz is a Professor and an EPSRC Fellow at University College London, Department of Computer Science. She is also a faculty fellow at the Alan Turing Institute and an ELLIS fellow. At UCL she is one of the faculty members affiliated with the UCL Centre for Artificial Intelligence, where she lead the Web Intelligence Group. She also works as an Amazon Scholar for Amazon, where she works with the Alexa Shopping team and is a co-founder of Humanloop, a UCL spinout company.

Emine research interests lie in the fields of information retrieval and natural language processing. Her research in these areas is mainly guided by principles from machine learning, statistics and information theory. She has authored more than 150 papers in these areas (> 6,250 citations, H-index = 39). She has received several awards for her research, including the Karen Sparck Jones Award, a Google Faculty Research Award and a Bloomberg Data Science Research Award. Emine’s research has been funded by several funding bodies including EU Horizon 2020, EPSRC, Alan Turing Institute, Google and Bloomberg and Elsevier.

Emine has served in various senior roles, including co-editor-in-chief for the Information Retrieval Journal, a member of the editorial board for the AI Journal and an elected member of the executive committee for ACM SIGIR. She currently serves as an Associate Editor for ACM Transactions on Information Systems and am a member of the Steering Committee for ACM SIGIR Asia-Pacific. She has served in various roles including PC Chair for ACM SIGIR 2024 Perspectives Track, ACM SIGIR 2023 Industry Track (SIRIP), ACM CIKM 2022 Applied Track, ECIR 2020, ACM SIGIR 2018 and ACM ICTIR 2017 Conferences, Panels Chair for The Web Conference (WWW) 2021, Practice and Experience Chair for ACM WSDM 2017, and as the Doctoral Consortium Chair for ECIR 2017.

Since 2019 Emine has been a co-organising the TREC Deep Learning Track, funded by the National Institute of Standards and Technology (NIST). Between 2015-2017 I co-organised the TREC Tasks Track.