SPORR Rigor and Reproducibility
RaRe Researcher Awards
2025 Awards Nominations Open
About the awards:
RaRe (Rigor and Reproducibility) Awards are given by Stanford Program on Research Rigor and Reproducibility (SPORR) to promote the highest standard of research at Stanford School of Medicine. The awards were established in 2023.
C. Glenn Begley Award is named in honor of Dr. C. Glenn Begley, a renowned hematologist/oncologist and long-time SPARK advisor whose work highlighted critical challenges in preclinical reproducibility. This award celebrates teams that uphold the highest standards of scientific integrity, fostering innovation that is both impactful and reliable. This award is presented by SPARK in collaboration with the Stanford Program on Research Rigor and Reproducibility (SPORR). The award was established in 2025.
Winners
Health Policy Data Science Lab, led by Sherri Rose - for creation of a detailed lab manual with analytic practices that assure reliability, and a new course in rigor and reproducibility for computational scientists.
Merve Kaptan, Postdoctoral Scholar - for rigorous and field-changing methods in development of a deep-learning model for spinal cord imaging
Matthew Lau, Student - for development of CRISPR kits to bring reproducible research to thousands of high school students in the Bay Area
C. Glenn Begley Award:
Sai Gourisankar, Postdoctoral Scholar - for rigorous approach to drug development for lymphoma
Nomination text (applications) can be seen here.
2024 Winners:
- Jan Niklas Hansen - for creation of free software that allows complex image analysis of specific fields of cell biology
- Kif Liakath-Ali - for rigorous and reproducible experimental designs in assessing mRNA alternative splicing in neurons - Award Coverage in The Mercury News
Nomination text (applications) can be seen here.
Media Coverage:
2023 Winners:
- Thomas Robinson - For a rigorous and reproducible design of a large scale, community-based child and family obesity intervention trial
- Arjun Divyang Desai - For creation of a large corpus of machine readable medical images, tutorials and reproducible research workflows used to train AI in medical imaging
- Jade Benjamin-Chung - For creation of an online open source lab manual that describes, among other topics, authorship guidelines, creation of reproducible workflows, and data management.
- (Emma) Lundberg Lab - For a decade long effort to build the Cell Atlas of the Human Protein Atlas database and for promoting bioimaging analysis using reproducible, open methods and citizen science.
Honorable Mentions:
- Xiaotao Shen - For creation of computational framework that can achieve traceable, shareable, and reproducible workflows in the field of metabolomics
- Joseph P. Garner - For decades long work on improving rigor and reproducibility of animal and translational research
Nomination text (applications) can be seen here.
Media Coverage:
StanfordMed Pulse covered the event and awardees.