Rate My Professor Cheng Lyu

Ly specializes in computational neuroscience, investigating the variability and fluctuations of cortical neural network activity and their dynamics under sensory inputs. His research addresses mathematical challenges including numerical solutions to probability density equations, large-scale Monte-Carlo simulations, and applied analysis of stochastic systems. Models developed include noisy neural oscillators, spiking stochastic networks, biophysical cellular simulations, and sensory signal coding mechanisms. Key publications include 'A Theoretical Framework for Analyzing Coupled Neuronal Networks: Application to the Olfactory System' (PLoS Computational Biology, 2017, with A. Barreiro, S.H. Gautam, W.L. Shew), 'Dynamics of Coupled Noisy Neural Oscillators with Heterogeneous Phase Resetting Curves' (SIAM Journal on Applied Dynamical Systems, 2014), 'Divisive Gain Modulation with Dynamic Stimuli in Integrate-and-Fire Neurons' (PLoS Computational Biology, 2009, with B. Doiron), and 'Critical Analysis of Dimension Reduction for a Moment Closure Method in a Population Density Approach to Neural Network Modeling' (Neural Computation, 2007, with D. Tranchina). Additional works cover synchronization dynamics, spike train statistics, phase-resetting curves, and firing rate dynamics in recurrent networks, amassing over 680 citations. Ly is a lifetime member of the Society for Industrial and Applied Mathematics and the Virginia Academy of Sciences, and holds memberships in Pi Mu Epsilon and Phi Beta Kappa. He has received grants including $240,800 from the University of Arkansas for 'Tunable Multi-timescale Cortical Dynamics' and support through the One VCU Research Strategic Priorities Plan.