AcaRevival Initiative

Experienced academic misconduct or bullying? We're building a real weapon against it.

Read Manifesto →
QL

Qian Liu

Stanford University

No ratings yetBe the first to rate
Loading...

About Qian Liu at Stanford University (Stanford)

Qian Liu is a researcher based at Stanford University. They specialize in Medical Imaging Techniques and Applications, Genetic Mapping and Diversity in Plants and Animals, and Radiomics and Machine Learning in Medical Imaging, with ongoing contributions to these areas. Their academic career is distinguished by over 15,547 citations, demonstrating their leading role in the global research community. With a formidable H-index of 58, Qian Liu continues to drive innovation in their area of expertise.

Research Areas

Medical Imaging Techniques and ApplicationsGenetic Mapping and Diversity in Plants and AnimalsRadiomics and Machine Learning in Medical ImagingPhotoacoustic and Ultrasonic ImagingAdvanced X-ray and CT Imaging

Academic Impact Matrix

Research output metrics for Qian Liu aggregated from public academic databases. Student lab experience data is pending.

Academic data verified · April 2026 · Next sync: May 2026

Research Output

Total Citations15,547

Top 15% in field

Publications946

Highly prolific researcher

h-index58

Field leader

i10-index300

Exceptional breadth

Lab Environment

No lab data yet for Qian Liu

+ Contribute First Review
  • Supervisionawaiting data
  • Responsivenessawaiting data
  • Fundingawaiting data
  • Communicationawaiting data
  • Work-Life Balanceawaiting data

Top Publications

Reviews (0)

No reviews yet for this supervisor.

Be the first to share your experience!

Is your PI driving you crazy?

Featured Article

The Sunday Night Dread: Surviving a Micromanaging PhD Supervisor

Real advice from PhD students on recognizing and navigating difficult supervisor relationships

Your experience matters. After reading the guide, share your review to help other PhD students.

Frequently Asked Questions

Not sure how to interpret mixed signals? A structured decision guide can help you think through high-risk supervision choices more clearly. Download the free guide.