AcaRevival Initiative

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

Read Manifesto →
MM

Mohammad Movassaghi

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Mohammad Movassaghi at Massachusetts Institute of Technology (MIT)

Mohammad Movassaghi is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Advanced Synthetic Organic Chemistry, Chemical synthesis and alkaloids, and Synthetic Organic Chemistry Methods. As a highly cited researcher, their work has accumulated over 7,862 citations, reflecting substantial influence across the academic community. Their H-index of 50 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Advanced Synthetic Organic ChemistryChemical synthesis and alkaloidsSynthetic Organic Chemistry MethodsAlkaloids: synthesis and pharmacologyCrystallization and Solubility Studies

Academic Impact Matrix

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

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

Research Output

Total Citations7,862

Emerging researcher

Publications267

Highly prolific researcher

h-index50

Field leader

i10-index90

Broad impact

Lab Environment

No lab data yet for Mohammad Movassaghi

+ 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.