Stanford CVI’s Travel Awards
Attend a conference and exchange ideas!
The Stanford CVI Travel Awards Program provides CVI trainees with financial support to attend workshops and conferences, enabling them to enhance their training, share their research, network with peers, and gain new insights that can positively impact their work and that of others.
About the Program
Stanford CVI provides a $750 award to trainees who are giving presentations at scientific conferences. These stipends are awarded quarterly.
To be eligible for the award, applicants must be postdocs, instructors, graduate students, or nurses, and they must be a CVI member. The PI/mentor must also be a CVI member. The presentation must list Stanford CVI as an affiliation for the applicant.
Once the travel is complete, it is the responsibility of the trainee and their department finance administrator to submit the reimbursement request to the CVI finance department.
Details
1) You must be a CVI Member to apply -- to become a member click here
2) Your mentor must also be a CVI Member
3) An accepted abstract to a national or international meeting related to cardiovascular research
4) The abstract must list Stanford Cardiovascular Institute in the author affiliations when first submitted
5) Attendance and participation in the conference must occur after the CVI Travel Award has been conferred
6) For conferences occurring on or after June 13, 2025
Deadline: May 30, 2025, at 11:59 pm PST
Future Award Deadlines
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201
Awards since 2013
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Travel Awardees
February 2025
Gastruloids Enable Modeling of the Earliest Stages of Human Cardiac and Hepatic Vascularization
Multi-Cellular Engineered Living Systems (MCELS) Symposium 2025
Senior Scientist
Preeclamptic and Normotensive iPSC-Derived Endothelial Cells Have Distinct Responses to Maternal Circulating Factors
Society for Reproductive Investigation Annual Meeting
Xi Plummer
Maternal-Fetal Medicine Fellow
Analyzing Demographic Representation in Cardiothoracic Anesthesiology and Thoracic Surgery through Text-to-Image Generators
Society of Cardiovascular Anesthesiologists Annual Meeting
Megan Chung
MD Student
Automated Machine Learning Models of Baseline Electroanatomic Features Can Predict AF Catheter Ablation Outcomes
Heart Rhythm Society Conference
Muhammad Fazal
Cardiology Fellow