AcaRevival Initiative

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

Read Manifesto →
VV

Valerie Doan Phi Van

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Valerie Doan Phi Van at Massachusetts Institute of Technology (MIT)

Valerie Doan Phi Van is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Tuberculosis Research and Epidemiology, Infectious Diseases and Tuberculosis, and Neuroscience and Neural Engineering. As an established researcher, their work has gained over 183 citations, reflecting growing recognition within the scientific community. Their H-index of 8 further reflects consistent scholarly impact.

Research Areas

Tuberculosis Research and EpidemiologyInfectious Diseases and TuberculosisNeuroscience and Neural EngineeringMRI in cancer diagnosisPhotoreceptor and optogenetics research

Academic Impact Matrix

Research output metrics for Valerie Doan Phi Van aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations183

Emerging researcher

Publications11

Selective publication record

h-index8

Developing track record

i10-index6

Early-stage portfolio

Lab Environment

No lab data yet for Valerie Doan Phi Van

+ 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.