AcaRevival Initiative

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

Read Manifesto →
UF

Umair Farooq

Massachusetts Institute of Technology

No ratings yetBe the first to rate
Loading...

About Umair Farooq at Massachusetts Institute of Technology (MIT)

Umair Farooq holds an academic position at Massachusetts Institute of Technology. Their scholarly work centers on Advanced Neural Network Applications, Advanced Memory and Neural Computing, and Plant nutrient uptake and metabolism. With over 381 citations accumulated, their work continues to earn recognition across academic communities. Their H-index of 4 highlights a growing trajectory of research influence.

Research Areas

Advanced Neural Network ApplicationsAdvanced Memory and Neural ComputingPlant nutrient uptake and metabolismCCD and CMOS Imaging SensorsCrop Yield and Soil Fertility

Academic Impact Matrix

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

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

Research Output

Total Citations381

Emerging researcher

Publications5

Selective publication record

h-index4

Developing track record

i10-index4

Early-stage portfolio

Lab Environment

No lab data yet for Umair Farooq

+ 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.