Dr. Lianli Liu

Assistant Professor

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Biography

Lianli Liu is a Clinical Assistant Professor in the Department of Radiation Oncology at Stanford University specializing in Radiation Physics. She holds a PhD in Electrical Engineering from the University of Michigan, where she also completed her residency training in Therapeutic Medical Physics. Dr. Liu is actively involved in several innovative programs at Stanford, including radiosurgery and MR-guided radiotherapy. Her research primarily focuses on optimizing radiotherapy workflows using artificial intelligence, enhancing medical imaging techniques, and improving data modeling for radiotherapy beams. She has also published numerous papers on the intersection of technology and radiation therapy and serves as an Associate Editor for the Medical Physics journal. In recognition of her contributions to the field, she has received several awards, including the Seed Grant from the Stanford Institute for Human-Centered Artificial Intelligence and the Summa Cum Laude Merit Award from the International Society for Magnetic Resonance in Medicine.

Research Interests

Experience

Clinical Assistant Professor

2020-01-01 — Present

Stanford University • Stanford, CA

Clinical Assistant Professor focused on Radiation Physics in Radiation Oncology.

Awards

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Seed Grant

2021-01-01
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Summa Cum Laude Merit Award

2018-01-01
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Barbour Scholarship

2017-01-01

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.