AcaRevival Initiative

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

Read Manifesto →
ZK

Ziliang Kang

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Ziliang Kang at Massachusetts Institute of Technology (MIT)

Ziliang Kang is an academic professional affiliated with Massachusetts Institute of Technology. Their primary research focus includes Topology Optimization in Engineering, Shape Memory Alloy Transformations, and Composite Structure Analysis and Optimization. As an established researcher, their work has gained over 359 citations, reflecting growing recognition within the scientific community. Their H-index of 10 further reflects consistent scholarly impact.

Research Areas

Topology Optimization in EngineeringShape Memory Alloy TransformationsComposite Structure Analysis and OptimizationAdvanced Sensor and Energy Harvesting MaterialsElectric Vehicles and Infrastructure

Academic Impact Matrix

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

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

Research Output

Total Citations359

Emerging researcher

Publications23

Selective publication record

h-index10

Developing track record

i10-index10

Early-stage portfolio

Lab Environment

No lab data yet for Ziliang Kang

+ 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.