AcaRevival Initiative

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

Read Manifesto →
JS

Julie Shah

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Julie Shah at Massachusetts Institute of Technology (MIT)

Julie Shah is a researcher based at Massachusetts Institute of Technology. They specialize in Human-Automation Interaction and Safety, Robot Manipulation and Learning, and Explainable Artificial Intelligence (XAI), with ongoing contributions to these areas. Their academic career is distinguished by over 6,942 citations, demonstrating their leading role in the global research community. With a formidable H-index of 43, Julie Shah continues to drive innovation in their area of expertise.

Research Areas

Human-Automation Interaction and SafetyRobot Manipulation and LearningExplainable Artificial Intelligence (XAI)Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Academic Impact Matrix

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

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

Research Output

Total Citations20,826

Top 5% globally

Publications702

Highly prolific researcher

h-index43

Established scholar

i10-index107

Broad impact

Lab Environment

No lab data yet for Julie Shah

+ 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.