AcaRevival Initiative

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

Read Manifesto →
MS

Matthew A. Smith

Neuroscience

University of Pittsburgh

No ratings yetBe the first to rate
Loading...

About Matthew A. Smith at University of Pittsburgh (Pitt)

Matthew A. Smith is a neuroscientist at Carnegie Mellon University, focusing on neural dynamics, visual perception, and brain-computer interfaces. Their recent contributions to the field are exemplified by influential works such as "Compact deep neural network models of visual cortex", and "Recent Visual Experience Reshapes V4 Neuronal Activity and Improves Perceptual Performance".

Research Areas

neural dynamicsvisual perceptionbrain-computer interfacesEEGsaccade generationsuperior colliculusfrontal eye fields
Stop Acting Like a Student.

Most PhDs fail because they never learn the hidden rules of the lab. The top 15% do.

sponsored · disclosure

Curated by the RateMySupervisor community for research productivity. · As an Amazon Associate we earn from qualifying purchases.

Academic Impact Matrix

Research output metrics for Matthew A. Smith aggregated from public academic databases. Student lab experience data is pending.

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

Research Output

Total Citations8,508

Above average

Publications267

Highly prolific researcher

h-index44

Established scholar

i10-index107

Broad impact

Lab Environment

No lab data yet for Matthew A. Smith

+ 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.