Rate My Professor Jie Yin

Yin's research focuses on developing novel machine learning algorithms for complex data, including large-scale graphs, with specializations in graph learning, knowledge graphs, interpretable AI, few-shot and continual learning, text analytics, natural language processing, and social media mining. He has authored over 70 papers in top-tier venues such as NeurIPS, ICML, ICLR, KDD, AAAI, IJCAI, ICDM, and CIKM. Key publications include 'Network Representation Learning: A Survey' (2020), cited over 945 times; 'Using social media to enhance emergency situation awareness' (2012), with 972 citations; and 'Sensor-based abnormal human-activity detection' (2008), cited 547 times. His work has accumulated over 6,900 citations. Yin has received notable awards, including the ACL 2024 Outstanding Paper Award, Unit of Study Student Survey Award for Teaching (2023), recognition as one of the World's Top 2 Percent academics in machine learning by Stanford University/Elsevier (2023), multiple Dean's Citation for Teaching Awards (2020, 2019), and Dean's Citation for Engaged Research Partnerships (2018). He serves as Associate Editor for IEEE Transactions on Big Data since 2021, guest editor for special issues, and chairs/program committee member for major conferences like NeurIPS and KDD. Yin coordinates and lectures courses such as Data Science in Business (BUSS6002), Machine Learning for Business (QBUS6850), and Business Analytics in Practice (QBUS3600). He is Chief Investigator on ARC Discovery Project DP250100871.