AcaRevival Initiative

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

Read Manifesto →
HK

Heather J. Kulik

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Heather J. Kulik at Massachusetts Institute of Technology (MIT)

Heather J. Kulik holds an academic position at Massachusetts Institute of Technology. Their scholarly work centers on Machine Learning in Materials Science, Computational Drug Discovery Methods, and Metal-Organic Frameworks: Synthesis and Applications. With over 12,003 citations to their name, their contributions have had a measurable and lasting impact on the field. An H-index of 56 underscores the consistent quality and influence of their published research.

Research Areas

Machine Learning in Materials ScienceComputational Drug Discovery MethodsMetal-Organic Frameworks: Synthesis and ApplicationsAdvanced Chemical Physics StudiesProtein Structure and Dynamics

Academic Impact Matrix

Research output metrics for Heather J. Kulik aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations48,012

Top 5% globally

Publications2092

Highly prolific researcher

h-index56

Field leader

i10-index174

Exceptional breadth

Lab Environment

No lab data yet for Heather J. Kulik

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

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.