AcaRevival Initiative

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

Read Manifesto →
GA

Genevieve Abbruzzese

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Genevieve Abbruzzese at Massachusetts Institute of Technology (MIT)

Genevieve Abbruzzese is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Esophageal Cancer Research and Treatment, Gastric Cancer Management and Outcomes, and Lung Cancer Treatments and Mutations. As an established researcher, their work has gained over 774 citations, reflecting growing recognition within the scientific community. Their H-index of 15 further reflects consistent scholarly impact.

Research Areas

Esophageal Cancer Research and TreatmentGastric Cancer Management and OutcomesLung Cancer Treatments and MutationsNeurological disorders and treatmentsAdvanced Proteomics Techniques and Applications

Academic Impact Matrix

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

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

Research Output

Total Citations1,548

Emerging researcher

Publications184

Active researcher

h-index15

Developing track record

i10-index22

Early-stage portfolio

Lab Environment

No lab data yet for Genevieve Abbruzzese

+ 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.