Neil leads the User Modeling & Personalization team at Snap Research. His work focuses on machine learning algorithms and applications on large-scale user interaction data, especially applied to structured representations like graphs. His work has resulted in 60+ conference and journal publications, in top venues such as ICLR, NeurIPS, KDD, WSDM, WWW, AAAI and more, including several best-paper awards. He has also served as an Organizer, Chair, Area chair, and Senior Program Committee member at a number of these. He has had previous research experiences at Lawrence Livermore National Laboratory, Microsoft Research, and Twitch. He earned a PhD in Computer Science in 2017 from Carnegie Mellon University’s Computer Science Department, funded partially by the NSF Graduate Research Fellowship.