Dr. Xiaojie Qiu

Assistant Professor

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Biography

Dr. Xiaojie Qiu is an Assistant Professor in the Department of Genetics at Stanford University, with a courtesy appointment in the Department of Computer Science. His Ph.D. from the University of Washington focused on single-cell genomics and led to significant advancements in pseudotemporal trajectory analysis with Monocle 2 and Monocle 3. Xiaojie completed his postdoctoral research at the Whitehead Institute at MIT, working on RNA velocity and creating Dynamo, a toolkit for reconstructing RNA velocity vector fields. He also developed Spateo, enhancing multi-dimensional spatiotemporal modeling for high-definition spatial transcriptomics. At Stanford, Xiaojie's research aims to integrate machine learning and genomics to address critical questions in mammalian cell fate transitions, particularly in heart evolution and disease development. His work has been funded by several prestigious institutes and organizations.

Research Interests

Experience

Assistant Professor

2023-12-16 — Present

Stanford University • Stanford, CA

Leading research in single-cell spatial genomics and developing predictive models for heart disease.

Awards

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Highly Cited Researcher

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NIH Director's New Innovator Award

2024-10-08
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Arc Ignite Award

2023-09-01
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Pathway Independence Awards (K99/R00)

2023-02-01

Courses

BIOE 391 GENE 260

Requirements for Stanford University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:26
Reading
Required:26
Writing
Required:26
Speaking
Required:26
Total
Required:100
GRE General
Verbal
Required:160
Quantitative
Required:165
Analytical Writing
Required:4.5
Overall
Required:4.5
Prerequisites
Bachelor degree from an accredited institution Strong background in mathematics and programming
Application Checklist
  • Statement of Purpose
  • Three letters of recommendation
  • Official transcripts
  • Resume/CV
Specialization Notes

The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.