AcaRevival Initiative

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

Read Manifesto →
CM

Caroline Martin

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Caroline Martin at Massachusetts Institute of Technology (MIT)

Caroline Martin is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Single-cell and spatial transcriptomics, Neuroinflammation and Neurodegeneration Mechanisms, and Plant Molecular Biology Research. As a highly cited researcher, their work has accumulated over 4,449 citations, reflecting substantial influence across the academic community. Their H-index of 9 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Single-cell and spatial transcriptomicsNeuroinflammation and Neurodegeneration MechanismsPlant Molecular Biology ResearchGene Regulatory Network AnalysisCell Image Analysis Techniques

Academic Impact Matrix

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

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

Research Output

Total Citations4,449

Emerging researcher

Publications13

Selective publication record

h-index9

Developing track record

i10-index9

Early-stage portfolio

Lab Environment

No lab data yet for Caroline 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.