The Genomics Training Grant held a successful retreat on Friday April 28 organized by trainees Rebecca Danning and Stephanie Armbruster and attended by grant PIs Xihong Lin and Curtis Huttenhower. Each of the participants gave lightning presentations of … Continue reading “Genomics Training Grant Retreat”
Harvard Biostatistics Department Seminar Monday, May 8 | 1:00-1:50pm | FXB G11 Dr. Zihuai He Assistant Professor of Neurology and of Medicine Stanford University Advancing conditional independent feature selection in … Continue reading “Biostats Department Seminar – 5/8”
Contact David Cruikshank for Zoom information.
Biostatistics Journal Club: Linear models for characterizing measurement uncertainty and comparing evaluators: a review, with applicationsWednesday, May 3, 20231:00pm-2:00pmRegister hereMark Vangel, PhD, Massachusetts General HospitalThis journal club considers two models … Continue reading “Harvard Catalyst Journal Club – 5/3”
The Department of Epidemiology invites you to: The 7th Cutter SymposiumLongevity: The Role of EpidemicsFriday, May 5, 2023 | Snyder Auditorium (Kresge G1)3:00-5:00pm Symposium5:00-7:00pm ReceptionOpen to the publicRegister for in-person and livestream … Continue reading “7th Cutter Symposium – 5/5”
Congratulations to Biostats PhD candidate Intekhab (Inté) Hossain who was awarded a best poster award at RECOMB’s Computational Cancer Biology (CCB) satellite conference for his paper “Biologically informed NeuralODEs for genome-wide regulatory dynamics”. The conference was held between … Continue reading “Intekhab Hossain receives best poster award at RECOMB’s Computational Cancer Biology (CCB) satellite conference”
We are extremely pleased to announce Dr. David Harrington will be the recipient of the 2023 Marvin Zelen Leadership Award in Statistical Science! We will host Dave for a lecture on “The special relationship … Continue reading “Marvin Zelen Leadership Award – 4/26”
Harvard Biostatistics Colloquium SeriesThursday, April 271:00-2:00pmFXB G11Eric LaberProfessor of Statistical ScienceDuke UniversityReinforcement Learning for Respondent-Driven Sampling