AcaRevival Initiative

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

Read Manifesto →
MF

Michale S. Fee

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Michale S. Fee at Massachusetts Institute of Technology (MIT)

Michale S. Fee is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Animal Vocal Communication and Behavior, Animal Behavior and Reproduction, and Marine animal studies overview. As a highly cited researcher, their work has accumulated over 10,450 citations, reflecting substantial influence across the academic community. Their H-index of 47 further reflects the breadth and sustained impact of their scholarly contributions.

Research Areas

Animal Vocal Communication and BehaviorAnimal Behavior and ReproductionMarine animal studies overviewNeural dynamics and brain functionNeuroscience and Neural Engineering

Academic Impact Matrix

Research output metrics for Michale S. Fee aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations10,450

Above average

Publications102

Selective publication record

h-index47

Established scholar

i10-index69

Growing portfolio

Lab Environment

No lab data yet for Michale S. Fee

+ 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.