Cyrus Omar designs intelligent user interfaces for modern programming languages.

Education

Carnegie Mellon University
PhD, Computer Science
UIUC
BS, Computer Science
BS, Molecular & Cellular Biology

Advising

PhD Students

Research Staff

Masters and Undergraduates

There are 10+ masters and undergraduate researchers in FP Lab — see the FP Lab webpage!

Former Advisees

FP Lab alum also include 200+ undergraduate and MS students, 15 of whom went on to PhD programs!

Service

2026
PLDI PC · PROPL Chair · VL/HCC PC · HATRA PC · LMPL PC · PLMW @ SPLASH Speaker · SPLASH SRC Judge · CSE Course Review Committee
2024
OOPSLA PC · VL/HCC PC · Onward! PC · LIVE PC · SPLASH-E PC · HATRA Publicity Chair · CSE DEI Committee
2023
PLDI PC · ECOOP PC · VL/HCC PC · MWPLS Co-chair · TyDe SC Chair · ECOOP Area Chair (Brave New Ideas and Pearls) · HATRA PC · IFL PC · SPLASH-E PC · SPLASH SRC · PLMW @ ICFP Panelist · CSE DEI Committee · CSE Hosting Committee

For older service roles, refer to my CV.

Awards and Honors

I lead the Future of Programming Lab (FP Lab), part of the vibrant MPLSE research community.
I am on sabbatical at the University of Cambridge for 2026–27, as a Visiting Fellow in the Energy and Environment Group in the Department of Computer Science and Technology and an Associate Scholar at Pembroke College.

Neural Correlation Is Stimulus Modulated by Feedforward Inhibitory Circuitry

Jason W. Middleton, Cyrus Omar, Brent Doiron, and Daniel J. Simons.

Journal paper in The Journal of Neuroscience (vol 32 issue 2).

Correlated variability of neural spiking activity has important consequences for signal processing. How incoming sensory signals shape correlations of population responses remains unclear. Cross-correlations between spiking of different neurons may be particularly consequential in sparsely firing neural populations such as those found in layer 2/3 of sensory cortex. In rat whisker barrel cortex, we found that pairs of excitatory layer 2/3 neurons exhibit similarly low levels of spike count correlation during both spontaneous and sensory-evoked states. The spontaneous activity of excitatory–inhibitory neuron pairs is positively correlated, while sensory stimuli actively decorrelate joint responses. Computational modeling shows how threshold nonlinearities and local inhibition form the basis of a general decorrelating mechanism. We show that inhibitory population activity maintains low correlations in excitatory populations, especially during periods of sensory-evoked coactivation. The role of feedforward inhibition has been previously described in the context of trial-averaged phenomena. Our findings reveal a novel role for inhibition to shape correlations of neural variability and thereby prevent excessive correlations in the face of feedforward sensory-evoked activation.

# 1st Jan 2012•journal, neuro

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