
Dr Kirill Glavatskiy
Lecturer
School of Information and Physical Sciences (Data Science and Statistics)
- Email:kirill.glavatskiy@newcastle.edu.au
- Phone:0240339023
Career Summary
Biography
I specialize in mathematical and computational modelling in the domains of Statistical Physics, Sociophysics, and Chemical Engineering. I investigate how complex patterns emerge from irreversible dynamics of natural, social, industrial systems and vice versa, how the evolution of these systems is driven by their internal structure and the external environment. My aim is to understand collective behavior and self-organization that emerge from individual interactions of a large number of agents. I develop and solve mathematical and data driven models of such phenomena, revealing the origins of their observed behavior and making practical predictions.
Qualifications
- Philosophiae Doctor, Norwegian University of Science and Technology
Keywords
- agent-based modelling
- chemical engineering
- data science
- density functional theory
- dynamical systems
- information thermodynamics
- irreversible thermodynamics
- mathematical modelling
- multiphase systems
- numerical modelling
- physical chemistry
- population mobility
- porous media
- simulations
- sociophysics
- statistical mechanics
- variational optimization
Languages
- Ukrainian (Fluent)
- Norwegian (Working)
- English (Fluent)
Fields of Research
| Code | Description | Percentage |
|---|---|---|
| 460202 | Autonomous agents and multiagent systems | 20 |
| 490206 | Statistical mechanics, physical combinatorics and mathematical aspects of condensed matter | 20 |
| 340609 | Transport properties and non-equilibrium processes | 20 |
| 460207 | Modelling and simulation | 20 |
| 401210 | Microfluidics and nanofluidics | 20 |
Professional Experience
UON Appointment
| Title | Organisation / Department |
|---|---|
| Lecturer | University of Newcastle School of Information and Physical Sciences Australia |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Book (1 outputs)
| Year | Citation | Altmetrics | Link | ||
|---|---|---|---|---|---|
| 2011 |
Glavatskiy K, Multicomponent Interfacial Transport, Springer Berlin Heidelberg (2011)
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Conference (1 outputs)
| Year | Citation | Altmetrics | Link | |||||
|---|---|---|---|---|---|---|---|---|
| 2017 |
Maslechko A, Glavatskiy K, Kulinskii VL, 'Surface tension of molecular liquids: Lattice gas approach', Journal of Molecular Liquids, 235, 119-125 (2017) [E1]
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Journal article (32 outputs)
| Year | Citation | Altmetrics | Link | |||||
|---|---|---|---|---|---|---|---|---|
| 2025 |
Glavatskiy K, 'Local Equilibrium in Transient Heat Conduction', Entropy, 27 (2025) [C1]
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| 2023 |
Evans BP, Glavatskiy K, Harre MS, Prokopenko M, 'The impact of social influence in Australian real estate: market forecasting with a spatial agent-based model', JOURNAL OF ECONOMIC INTERACTION AND COORDINATION, 18, 5-57 (2023) [C1]
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| 2022 |
Glavatskiy K, Kalloniatis AC, 'Fisher Information and synchronisation transitions: A case-study of a finite size multi-network Kuramoto-Sakaguchi system', PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 594 (2022) [C1]
We analyse a Kuramoto¿Sakaguchi dynamics on a two-layer multi-network using the Fisher Information which has been demonstrated in a variety of complex dynamical and the... [more] We analyse a Kuramoto¿Sakaguchi dynamics on a two-layer multi-network using the Fisher Information which has been demonstrated in a variety of complex dynamical and thermodynamic systems to provide a lens on critical behaviour and transitions to chaos. Here we use a case-study, introduced elsewhere and thus providing a baseline, of multi-networks consisting of tree and random graphs with couplings and frequencies set at values in the vicinity of thresholds for locking, metastable and chaotic states. We observe transitions in the two-dimensional space of the frustrations in the cross-network interactions of the multi-layer system. While the Shannon entropy consistently identifies a range of transitions, the Fisher Information detects additional signals corresponding to significant changes in the microscopic dynamics. We argue that Fisher Information provides a single measure to analyse rich coupled dynamics and to detect meaningful transitions in a finite-size system that otherwise require multiple measures to establish. We support this analysis using a novel semi-analytical steady-state ansatz incorporating splay phase parameters, where the stability analysis concurs with key changes in the Fisher Information.
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| 2021 |
Slavko B, Glavatskiy KS, Prokopenko M, 'Revealing configurational attractors in the evolution of modern Australian and US cities', CHAOS SOLITONS & FRACTALS, 148 (2021) [C1]
The spatial structure of modern cities exhibits highly diverse patterns and keeps evolving under numerous constraints and sustainability demands. However, it is unclear... [more] The spatial structure of modern cities exhibits highly diverse patterns and keeps evolving under numerous constraints and sustainability demands. However, it is unclear if there are fundamental physical constraints guiding the evolution of cities. Here, we offer a concise model revealing key invariants within urban forms shaped by human resettlement over the years. In doing so, we assess the heterogeneity and spreading of population density in 25 Australian and 175 US cities. We observe that larger cities tend to form a cluster with low spreading and high heterogeneity, and explain this observation using dynamic properties of the intra-urban migration in these cities. As a result, we report three distinct feasible phases of urban structures: uniform, monocentric, and polycentric, separated by abrupt regime shifts. We demonstrate that transitions between these phases, resulting from the population redistribution, are not necessarily driven by external factors (such as city growth) and can exist even in a closed system. Our analysis reveals that the set of all possible equilibrium configurations ("configurational attractors") form a narrow region in the heterogeneityspreading space, thus explaining the emergence of clustering patterns.
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| 2021 |
Slavko B, Prokopenko M, Glavatskiy KS, 'Diffusive Resettlement: Irreversible Urban Transitions in Closed Systems', ENTROPY, 23 (2021) [C1]
We propose a non-equilibrium framework for modelling the evolution of cities, which describes intra-urban migration as an irreversible diffusive process. We validate th... [more] We propose a non-equilibrium framework for modelling the evolution of cities, which describes intra-urban migration as an irreversible diffusive process. We validate this framework using the actual migration data for the Australian capital cities. With respect to the residential relocation, the population is shown to be composed of two distinct groups, exhibiting different relocation frequencies. In the context of the developed framework, these groups can be interpreted as two components of a binary fluid mixture, each with its own diffusive relaxation time. Using this approach, we obtain longterm predictions of the cities' spatial structures, which define their equilibrium population distribution.
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Open Research Newcastle | ||||||
| 2021 |
Harre MS, Eremenko A, Glavatskiy K, Hopmere M, Pinheiro L, Watson S, Crawford L, 'Complexity Economics in a Time of Crisis: Heterogeneous Agents, Interconnections, and Contagion', SYSTEMS, 9 (2021) [C1]
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Open Research Newcastle | ||||||
| 2021 |
Glavatskiy KS, Prokopenko M, Carro A, Ormerod P, Harré M, 'Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model', SN Business & Economics, 1 (2021) [C1]
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| 2020 |
Slavko B, Glavatskiy K, Prokopenko M, 'City structure shapes directional resettlement flows in Australia', SCIENTIFIC REPORTS, 10 (2020) [C1]
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Open Research Newcastle | ||||||
| 2019 |
Bacchin P, Glavatskiy K, Gerbaud V, 'Interfacially driven transport theory: a way to unify Marangoni and osmotic flows', PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 21, 10114-10124 (2019) [C1]
We show that the solvent behaviour in both diffusio-osmosis and Marangoni flow can be derived from a simple model of colloid-interface interactions. We demonstrate that... [more] We show that the solvent behaviour in both diffusio-osmosis and Marangoni flow can be derived from a simple model of colloid-interface interactions. We demonstrate that the direction of the flow is regulated by a single value of the attractive parameter covering the purely repulsive and attractive-repulsive interaction cases. The proposed universality between diffusio-osmosis and Marangoni flow is extended further to include diffusio-phoresis. In particular, an object immersed to a colloidal solution moves towards the low concentration of the colloidal particles in the case of colloid-interface repulsion and towards the high concentration of the colloidal particles in the case of colloid-interface attraction. The approach combines the methods of fluid dynamics, molecular physics and transport phenomena and provides a tractable explanation of how the colloid-interface interactions affect the momentum balance and the transport phenomena (interfacially driven transport).
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| 2019 |
Slavko B, Glavatskiy K, Prokopenko M, 'Dynamic resettlement as a mechanism of phase transitions in urban configurations', PHYSICAL REVIEW E, 99 (2019) [C1]
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Open Research Newcastle | ||||||
| 2017 |
Glavatskiy KS, Bhatia SK, 'Effect of pore size on the interfacial resistance of a porous membrane', JOURNAL OF MEMBRANE SCIENCE, 524, 738-745 (2017) [C1]
Fluid transport through nanoporous membranes is subject to additional resistance at the membrane interface, a large part of which is due to the difference in thermodyna... [more] Fluid transport through nanoporous membranes is subject to additional resistance at the membrane interface, a large part of which is due to the difference in thermodynamic states of the fluid inside and outside the membrane. The state of the fluid confined within a membrane depends on the size of the nanopores, which results in a corresponding dependence of the interfacial resistance. We investigate here the dependence of the thermodynamic resistance on the radius of the nanopore and the thickness of the pore wall, considering the transport of carbon dioxide and methane through carbon nanotubes of radii between 4¿Å and 50¿Å at room temperature, and a wide range of pressures. We find that the thermodynamic resistance strongly depends on the state of the fluid adsorbed in the membrane, which is determined by the size of the pores and the external pressure. In particular, for narrow micropores the thermodynamic resistance has two pressure regimes, being constant at low pressures and increasing gradually at high pressures. Furthermore, moderate and wide pores allow presence of multiple fluid phases with distinct condensation. In the corresponding pressure range the thermodynamic resistance is subjected to large fluctuations, which are not observed for small pores. Furthermore, our results reveal strong dependence of the thermodynamic resistance on the pore radius for very narrow pores and large pressures, when the state of the fluid inside of the membrane is most different from that of the external bulk fluid, with the resistance increasing with decrease in pore radius. Our results also indicate that analyzing the pore size dependence of the interfacial resistance makes it possible to distinguish the contribution of the thermodynamic resistance from the other sources of resistance to fluid flow through the membrane, in particular, the hydrodynamic resistance and the internal resistance.
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| 2016 |
Glavatskiy KS, Bhatia SK, 'Thermodynamic Resistance to Matter Flow at The Interface of a Porous Membrane', LANGMUIR, 32, 3400-3411 (2016) [C1]
Nanoporous materials are important in industrial separation, but their application is subject to strong interfacial barriers to the entry and transport of fluids. At ce... [more] Nanoporous materials are important in industrial separation, but their application is subject to strong interfacial barriers to the entry and transport of fluids. At certain conditions the fluid inside and outside the nanoporous material can be viewed as a two-phase system, with an interface between them, which poses an excess resistance to matter flow. We show that there exist two kinds of phenomena which influence the interfacial resistance: hydrodynamic effects and thermodynamic effects, which are independent of each other. Here, we investigate the role of the thermodynamic effects in carbon nanotubes (CNTs) and slit pores and compare the associated thermodynmic resistance with that due to hydrodynamic effects traditionally modeled by the established Sampson expression. Using CH4 and CO2 as model fluids, we show that the thermodynamic resistance is especially important for moderate to high pressures, at which the fluid within the CNT or slit pore is in the condensed state. Further, we show that at such pressures the thermodynamic resistance becomes comparable with the internal resistance to fluid transport at length scales typical of membranes used in fuel cells, and of importance in membrane-based separation, and nanofluidics in general.
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| Show 29 more journal articles | ||||||||
Preprint (1 outputs)
| Year | Citation | Altmetrics | Link | ||
|---|---|---|---|---|---|
| 2024 |
Glavatskiy K, Hickie I, Crouse J, Prodan A, Scott J, Merikangas K, et al., 'The effect of sleep-wake behaviors on the onset of mania in youth: a computational agent-based model. (2024)
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Research Supervision
Number of supervisions
Current Supervision
| Commenced | Level of Study | Research Title | Program | Supervisor Type |
|---|---|---|---|---|
| 2024 | PhD |
AI Model Development for B2B Sales Operations. <p><span style="color:black;">Business Finland funded Pata -project (AI enabled customer experiences) aims to enhance the seller-buyer interaction by leveraging artificial intelligence to develop data-based models for better customer experience.</span></p><p><span style="color:black;">The project also focuses on studying salespeople's interaction behavior and emotional skills to improve customer encounter skills and match the right salesperson to each customer. This data can be used to profile customers and target sales campaigns towards potential buyers.</span></p> |
Sales, University of Turku | Consultant Supervisor |
| 2022 | PhD | Agent based modelling of climate change-induced disaster evacuation management. | PhD (Information Technology), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Past Supervision
| Year | Level of Study | Research Title | Program | Supervisor Type |
|---|---|---|---|---|
| 2020 | PhD |
A thermodynamic approach to modelling urban transformations <span class="long-resume abstract">Are there fundamental physical constraints guiding the evolution of cities? Since the influential contribution of Jane Jacobs, “The death and life of American cities”, this question continues to be vigorously debated, and the underlying principles of urbanisation remain elusive. In this thesis, we offer a concise methodology revealing key invariants within urban forms shaped by human resettlement over the years. In attempt to relate the spatial structure of cities to the dynamic properties of human mobility, we introduce a rigorous framework quantifying city evolution. This approach models intra-urban resettlement flows as a collective emergent phenomenon driven by thermodynamic forces. The model also accommodates nonlinear interactions between population dynamics and infrastructure development. We show that our framework is consistent with the most recent residential migration data and explains much of the spatial properties of actual cities in Australia and the USA. In addition, we use this framework to analyse critical phenomena inherent to the process of urban evolution and reveal potential polycentric transitions in the largest Australian and US cities.</span> |
Civil Engineering, The University of Sydney | Co-Supervisor |
| 2018 | Masters |
Bifurcation dynamics in Australian housing market NA |
Civil Engineering, The University of Sydney | Sole Supervisor |
| 2015 | PhD |
Effects of density inhomogeneities and non-locality on nanofluidic flow <span style="font-family:'', blinkmacsystemfont, -apple-system, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Fira Sans', 'Droid Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif;font-size:16px;white-space-collapse:preserve;background-color:#fafafa;">We use Molecular Dynamics computer simulations to investigate the effects of strong density inhomogeneities on shearing flow in unconfined simple atomic fluids. We use a sinusoidal longitudinal force (SLF) to produce periodic, spatially oscillating density inhomogeneities that have periodic cycles of the order of single or few atomic diameters. We use a sinusoidal transverse force (STF) to produce spatially periodic shearing flow. Using the SLF and STF in combination we can produce shearing flow in strongly inhomogeneous fluids. This system is ideal for investigating the coupling relationships that are known to exist between density and velocity gradients. It is ideal because it provides us with full control over the density profiles and because we can easily decompose the periodic density, velocity, temperature and shear pressure profiles into individual Fourier components. <br /><br />Another system for studying strongly inhomogeneous shearing fluids is a nanoconfined system, where a fluid is forced to flow through a nanochannel or nanopore. In these systems, where it is known that the coupling between density and velocity gradients has a significant effect on the fluid hydrodynamics, we do not have control over the density and we cannot easily decompose the flow profiles. This makes the combined STF-SLF method a valuable tool for investigating density-velocity coupling in nanofluidic systems. Using the STF and SLF we are able to probe the non-local density, strain rate and shear pressure response of an atomic fluid to an external body force directly in Fourier space. In this way we can evaluate various linear and nonlinear response functions, which describe the formation of shearing flow and density inhomogeneities in homogeneous, equilibrium fluids when perturbed by external body forces</span> |
Physics, RMIT University | Co-Supervisor |
Dr Kirill Glavatskiy
Position
Lecturer
Data Science and Statistics
School of Information and Physical Sciences
College of Engineering, Science and Environment
Focus area
Data Science and Statistics
Contact Details
| kirill.glavatskiy@newcastle.edu.au | |
| Phone | 0240339023 |
Office
| Room | SR216 |
|---|---|
| Building | Social Science |
| Location | Callaghan Campus University Drive Callaghan, NSW 2308 Australia |
