AcaRevival Initiative

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

Read Manifesto →
JD

James Damewood

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About James Damewood at Massachusetts Institute of Technology (MIT)

James Damewood holds an academic position at Massachusetts Institute of Technology. Their scholarly work centers on Machine Learning in Materials Science, Cell Adhesion Molecules Research, and Computational Drug Discovery Methods. With over 841 citations accumulated, their work continues to earn recognition across academic communities. Their H-index of 14 highlights a growing trajectory of research influence.

Research Areas

Machine Learning in Materials ScienceCell Adhesion Molecules ResearchComputational Drug Discovery MethodsChemical Synthesis and AnalysisCytokine Signaling Pathways and Interactions

Academic Impact Matrix

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

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

Research Output

Total Citations841

Emerging researcher

Publications35

Selective publication record

h-index14

Developing track record

i10-index18

Early-stage portfolio

Lab Environment

No lab data yet for James Damewood

+ 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.