Members of the NCIPHER Lab had a great time and learned a lot at JSM in Boston last week! To kick off the week, on Sunday night, research associate Claire Pearsall presented a poster with updates on her research on spillover effects of substance use on HIV outcomes in the uConnect cohort. On Monday morning, Dr. Buchanan and Dr. Katenka with Ke Zhang delivered a short course on statistical methods for causal inference in networks, which was a big hit! On Tuesday Ke Zhang chaired and Dr. Buchanan presented in a session about targeted and doubly debiased machine learning methods for public health studies with interference, along with our friends and collaborators Dr. Paul Zivich, Dr. Heejong Bong, and Dr. Mark Van Der Laan. Later that afternoon, Dr. TingFang Lee also presented her flexible, practice-oriented tutorial framework for simulating causal data under interference (not pictured). Then on Wednesday morning Ke Zhang presented updates on her research on methods for causal effects of multicomponent interventions in longitudinal studies with interference in the TasP study from KwaZulu-Natal South Africa. Finally, on Thursday morning Ke Zhang chaired a topic-contributed paper session on spillover, sampling, and generalizability methods for public health impact with presenters Yihan Bao, Dr. Daniel Nevo, Dr. Harsh Parikh, and Dr. Gary Hettinger. Thanks so much to Dr. Laura Forastiere for organizing that session, and thanks to everyone who came to our presentations and course at JSM! We had the best time presenting, learning, and connecting with the larger statistics community—with Dr. Buchanan appearing in the conference program no less than 7 times—we can’t wait to see everyone again soon!