Speaker: Dr. Öğr. Üyesi Resul Tugay

Topic: Learning, Deducing and Linking Entities

Abstract: In this seminar, I will discuss three projects from my PhD and my Machine Learning Research Internship at TikTok. These projects encompass entity linking, where I developed advanced methods for connecting entities across datasets; fake engagements, focusing on the detection and prevention of fraudulent activities on social media; and data currency, which involves evaluating and enhancing the value of data in machine learning. I will also introduce my current project, which offers promising opportunities for collaboration and further research

Bio: Resul is an Asst. Prof. at Atatürk University, Dept of Artificial Intelligence and Data Engineering. Before Atatürk University, he worked as a lecturer at Gazi University and earned his Ph.D. in computer science at the University of Edinburgh in 2023. He has also served as a research assistant on a project in collaboration with the University of Edinburgh, University of Oxford and the NatWest Group. Before joining Edinburgh, he held positions as a research and teaching assistant at Istanbul Technical University, where he received the Outstanding Research and Teaching (R&T) Award in 2018-2019 consecutively. He also worked as a researcher ın TUBITAK and BAP projects during his MSc. Resul has worked as a PhD ML Research intern at TikTok and Huawei London. Additionally, he has provided consultancy services to several tech companies, including ETS, n11, and kariyer.net. Currently he is a scientific advisor to BTS group and researcher in TUBITAK 1515 Frontier R& ;D Laboratory Support Programme. His primary research interests encompass recommender systems, entity learning, and NLP/ML. Overall, his research has been published in top-tier venues such as ICDE, VLDB, ECML, etc.