AcaRevival Initiative

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

Read Manifesto →
JL

Jian-Ming LIU

Chemical and Biomolecular Engineering

Harvard University

No ratings yetBe the first to rate
Loading...

About Jian-Ming LIU at Harvard University (Harvard)

Jian-Ming LIU is an academic professional affiliated with the Chemical and Biomolecular Engineering Department at Harvard University. Their primary research focus includes Microbial Metabolic Engineering, Bioproduction, and Biofuels. As a highly cited researcher, their work has accumulated over 3,220 citations, reflecting substantial influence across the academic community. Their H-index of 32 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Microbial Metabolic EngineeringBioproductionBiofuelsEnzyme CatalysisCO2 UtilizationBioconversionElectrochemical-Biosynthesis SystemsBiomolecular Condensates

Academic Impact Matrix

Research output metrics for Jian-Ming LIU aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations3,220

Emerging researcher

Publications200

Active researcher

h-index32

Established scholar

i10-index64

Growing portfolio

Lab Environment

No lab data yet for Jian-Ming LIU

+ 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.