‌‌This lunch series features distinguished faculty mentors in an informal session about mentorship, career advancement and satisfaction at UCSF.

During this informal discussion Dr. Neilands, who was the co awardee of the 2025 UCSF Lifetime Achievement in Mentoring Award, will share his thoughts and experiences on how to be an effective mentor. The discussion will rely heavily on audience participation – so please bring your questions.

‌Torsten B. Neilands, Professor at the UCSF Division of Prevention Science in the Department of Medicine at UCSF. Originally trained as a social and quantitative psychologist, he spent eight years as a statistical consultant at the University of Texas academic computing center before coming to UCSF in 2001. Since arriving at UCSF, he has participated as a statistical co-investigator or consultant on over 100 NIH, CDC, and state projects in the areas of HIV prevention, reproductive health, aging research, and tobacco use prevention. His methodological areas of interest are multivariate statistical models with a special interest in latent variable models for survey scale development and validation as well as mixed effects (i.e., multilevel; HLM) models for clustered and longitudinal data, including dyadic data. 

His substantive interests include training the next generation of prevention researchers working in U.S. communities disproportionately affected by chronic diseases, including HIV and aging-related conditions. He is currently PI of two NIH-sponsored R25 research education grants to foster grant-writing and related research capacity-building for early-career faculty working in U.S. communities disproportionately impacted by HIV and STIs to prevent the spread of HIV/AIDS and STIs and to improve the lives of those living with HIV/AIDS. He also actively collaborates as a senior statistician and quantitative methods co-investigator on multiple prevention research projects. He is a co-author of Primer of Applied Regression & Analysis of Variance with Drs. Stanton Glantz and Bryan Slinker (McGraw-Hill, 2016). 

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