AcaRevival Initiative

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

Read Manifesto →
YC

Yunsie Chung

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Yunsie Chung at Massachusetts Institute of Technology (MIT)

Yunsie Chung is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Computational Drug Discovery Methods, Machine Learning in Materials Science, and Various Chemistry Research Topics. As a highly cited researcher, their work has accumulated over 1,091 citations, reflecting substantial influence across the academic community. Their H-index of 12 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Computational Drug Discovery MethodsMachine Learning in Materials ScienceVarious Chemistry Research TopicsAnalytical Chemistry and ChromatographyChemical Thermodynamics and Molecular Structure

Academic Impact Matrix

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

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

Research Output

Total Citations1,091

Emerging researcher

Publications46

Selective publication record

h-index12

Developing track record

i10-index15

Early-stage portfolio

Lab Environment

No lab data yet for Yunsie Chung

+ 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.