AcaRevival Initiative

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

Read Manifesto →
NM

Nicole Martinez‐Martin

Stanford University

No ratings yetBe the first to rate
Loading...

About Nicole Martinez‐Martin at Stanford University (Stanford)

Nicole Martinez‐Martin is an academic professional affiliated with Stanford University. Their primary research focus includes Artificial Intelligence in Healthcare and Education, Ethics in Clinical Research, and Digital Mental Health Interventions. As a highly cited researcher, their work has accumulated over 1,239 citations, reflecting substantial influence across the academic community. Their H-index of 15 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Artificial Intelligence in Healthcare and EducationEthics in Clinical ResearchDigital Mental Health InterventionsTelemedicine and Telehealth ImplementationNeuroethicsHuman EnhancementBiomedical Innovations

Academic Impact Matrix

Research output metrics for Nicole Martinez‐Martin aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations1,239

Emerging researcher

Publications53

Selective publication record

h-index15

Developing track record

i10-index21

Early-stage portfolio

Lab Environment

No lab data yet for Nicole Martinez‐Martin

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

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.