Andrey Kuznetsov


  • 919-515-5292
  • Engineering Building III (EB3) 3258

Dr. Kuznetsov is interested in developing models of electrically charged monolith filters capable of capturing viruses.

At the graduate level, Dr. Kuznetsov teaches Heat Transfer Theory and Applications (MAE 505) and Advanced Convective heat Transfer (MAE 708). In both of these courses, he presents real-life problems that have unexpected solutions. For example, he once told his students the true story of a problem that several Cosmonauts faced when first arriving at an uninhabited space station. The station was without power and its interior was very cold. They needed to know precisely the temperature in the station but did not have any devices to measure temperature. So, one of the Cosmonaut’s spit on a wall and measured with a watch the time it took for it to freeze. Stories like this demonstrate how physical principles solve problems in unexpected ways and bring the material to life.

At the undergraduate level, Dr. Kuznetsov teaches Fluid Mechanics I (MAE 308) and Heat Transfer (MAE 310). He complements the fundamental treatment with videos showing different effects and a lot of modern topics, like a discussion on why biological cells dehydrate when they freeze and the wonderful properties of superfluid liquid helium.

Dr. Kuznetsov’s students, like himself, are more than anything else obsessed with modeling fluid-thermal systems, which fosters a stimulating research environment. In fact, Dr. Kuznetsov’s graduate students, after first working with him, are often surprised and pleased to discover that he treats them as colleagues. They enjoy an atmosphere of stimulating discussions on competing ideas. The biotechnology focus of the research also makes the subject particularly interesting.

Outside of work, Dr. Kuznetsov spends time with his family.



Mechanical Engineering

Mechanical Engineering Research Institute, Russian Academy of Sciences


Applied Mathematics

Moscow State University


Mechanical Engineering

Bauman Moscow State Technical University

Research Description

Dr. Kuznetsov's long term goal is to further the advancement of modeling fluid-thermal systems. Presently, Dr. Kuznetsov is developing models of electrically charged monolith filters capable of capturing viruses and he is developing a mechanistic model of neuron deterioration in Alzheimer patients. In MAE, Dr. Kuznetsov collaborates with Dr. Roberts and Dr. Ro.


Simulating reversibility of dense core vesicles capture in en passant boutons: Using mathematical modeling to understand the fate of dense core vesicles in en passant boutons
Kuznetsov, I. A., & Kuznetsov, A. V. (2018), Journal of Biomechanical Engineering, 140(5).
How the formation of amyloid plaques and neurofibrillary tangles may be related: A mathematical modelling study
Kuznetsov, I. A., & Kuznetsov, A. V. (2018), Philosophical Transactions of the Royal Society of London. Series A, Mathematical, Physical and Engineering Sciences, 474(2210).
A new hydrodynamic boundary condition simulating the effect of rough boundaries on the onset of Rayleigh-Benard convection
Celli, M., & Kuznetsov, A. V. (2018), International Journal of Heat and Mass Transfer, 116, 581-586.
How dense core vesicles are delivered to axon terminals - a review of modeling approaches
Kuznetsov, I. A., & Kuznetsov, A. V. (2017), Modeling of Microscale Transport in Biological Processes, , 335-352.
Using resampling residuals for estimating confidence intervals of the effective viscosity and Forchheimer coefficient
Kuznetsov, I. A., & Kuznetsov, A. V. (2017), Transport in Porous Media, 119(2), 451-459.
Simulating tubulin-associated unit transport in an axon: Using bootstrapping for estimating confidence intervals of best-fit parameter values obtained from indirect experimental data
Kuznetsov, I. A., & Kuznetsov, A. V. (2017), Philosophical Transactions of the Royal Society of London. Series A, Mathematical, Physical and Engineering Sciences, 473(2201).
Turbulence modeling for flows in wall bounded porous media: An analysis based on direct numerical simulations
Jin, Y., & Kuznetsov, A. V. (2017), Physics of Fluids (Woodbury, N.Y.), 29(4).
Utilization of the bootstrap method for determining confidence intervals of parameters for a model of MAP1B protein transport in axons
Kuznetsov, I. A., & Kuznetsov, A. V. (2017), Journal of Theoretical Biology, 419, 350-361.
What mechanisms of tau protein transport could be responsible for the inverted tau concentration gradient in degenerating axons?
Kuznetsov, I. A., & Kuznetsov, A. V. (2017), Mathematical Medicine and Biology-A Journal of the IMA, 34(1), 125-150.
Biothermal Convection and Nanofluid Bioconvection
Kuznetsov, A. V. (2016), Handbook of Fluid Dynamics, 2nd Edition, .

View all publications via NC State Libraries


PINS# 79616 EMN-15-F-S-07 Developing of advanced mathematical models for simulating moisture management within knitted baselayer fabrics utilizing a novel polyester fabric
Eastman Chemical Company(4/01/17 - 5/15/18)
EAGER: Exploratory Research on DNS Modeling of Turbulent Heat Transfer in Porous Media
National Science Foundation (NSF)(8/15/16 - 7/31/19)
NATO Programme for Security Through Science, The(7/27/11 - 7/31/14)
Simulation of Unsteady Reacting Flows in Pulsejets with Ejectors
National Aeronautics & Space Administration (NASA)(6/01/08 - 9/30/09)
Modeling of Flow Containing Nanoparticles Through Electrostatically Charged Monolith Filters
Defense Threat Reduction Agency (DTRA)(1/31/08 - 12/30/11)
Enhancing Mixing in Micro Volumes of Fluid by Utilizing Bioconvection
NATO Programme for Security Through Science, The(4/18/05 - 12/31/07)