AcaRevival Initiative

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

Read Manifesto →
MC

Min Chen

Stanford University

No ratings yetBe the first to rate
Loading...

About Min Chen at Stanford University (Stanford)

Min Chen is a researcher based at Stanford University. They specialize in Nanoplatforms for cancer theranostics, Peptidase Inhibition and Analysis, and Cancer Immunotherapy and Biomarkers, with ongoing contributions to these areas. Their academic career is distinguished by over 1,321 citations, demonstrating their leading role in the global research community. With a formidable H-index of 17, Min Chen continues to drive innovation in their area of expertise.

Research Areas

Nanoplatforms for cancer theranosticsPeptidase Inhibition and AnalysisCancer Immunotherapy and BiomarkersAdvanced biosensing and bioanalysis techniquesCancer Mechanisms and Therapy
Stop Acting Like a Student.

Most PhDs fail because they never learn the hidden rules of the lab. The top 15% do.

sponsored · disclosure
The Professor Is In
#1 PhD Survival GuideAcademic Discount Available
The Hidden Rules of Grad School — What Your Advisor Won't Tell You
View Peer Reviews on Amazon →
Logitech MX Master 3S
Lab Standard ConfigAcademic Discount Available
Your Wrist Will Thank You After Year Two
Access Toolkit Specs →

Curated by the RateMySupervisor community for research productivity. · As an Amazon Associate we earn from qualifying purchases.

Academic Impact Matrix

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

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

Research Output

Total Citations3,963

Emerging researcher

Publications171

Active researcher

h-index17

Developing track record

i10-index22

Early-stage portfolio

Lab Environment

No lab data yet for Min Chen

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

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.