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Kostia Zuev - Research
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Prospective Students

If you are interested in working with me in one of the research areas described on the right, or have your own project in mind that you would like to discuss, please send me an email to kostia [at] caltech [dot] edu. 

Jenna Birch (U of Liverpool)
Yanhua Chen (U of Liverpool)
Will Cunningham (Northeastern U)
Or Eisenberg (Northeastern U)
Alfredo Garbuño-Inigo (U of Liverpool)
Ashwin Hari (Caltech)
Keegan Mendonca (Caltech → Facebook)
Zhi Ren (Caltech)
Stavros Stavroglou (U of Liverpool)
Michail Vamvakaris (U of liverpool)
Stephen Wu (Caltech → ICM) 

[15] [16]


Ivan Au (U of Liverpool)
James Beck (Caltech)
Michael Beer (U of Hannover)
Ginestra Bianconi (QMUL)
Marián Boguñá (U de Barcelona)
Alexey Bolsinov (Loughborough U)
Alex DiazDelaO (U of Liverpool)
Lambros Katafygiotis (HKUST)
Dima Krioukov (Northeastern U)
Rosario Mantegna (U of Palermo)
Athanasios Pantelous (U of Liverpool)
Fragkiskos Papadopoulos
Kimmo Soramäki (FNA)

[7] [8] [9] [11] [C3]
[E1] [19]
] [16]
[3] [5] [6] [7]
[12] [13] [14] [18]
[10][C2] [17] [20]


Erdös Number
My Erdös number is (at most) 4:


Google Scholar:

Research Areas

My research span various topics in the interdisciplinary areas of Risk, Reliability, and Resilience Engineering.

• Critical Infrastructure Networks
• Cascading Failures in Electric Power Grids
• Traffic and Congestion in Transport Networks
• Resilience-Based Design of Gas Networks
• Optimization of Water Distribution Networks
• Epidemic Processes in Social Networks
• Financial Networks and Systemic Risk
• Failure Propagation in Coupled Networks
• Interdependencies of Critical Infrastructures
• Disaster Resilience and Sustainability
• Structural and Infrastructural Reliability Methods
• Rare Event Simulation Methods
• Estimation of Small Failure Probabilities
• Subset Simulation, Markov Chain Monte Carlo
• Bayesian Inference for Uncertainty Quantification
• Multilayer Networks for Interdependence Modeling
• Agent-Based Modeling and Simulation
• Stochastic Processes and Time-Series Analysis
• Data Science and Network Science for Smart Cities
• Machine Learning for Civil Engineering Applications

Worldwide urbanization and globalization processes make the dependence of our society on infrastructure networks, such as electric power grids, transportation networks, and water and gas distribution networks, absolutely critical. The increased frequency and severity of extreme events due to climate change strengthen the need for these complex networks, spanning cities, countries, and even continents, to be highly reliable and resilient against catastrophic failures. This makes the study of critical infrastructure networks, the enhancement of their reliability and resiliency, and the quantification of the associated risks one of the most challenging and important problems of modern civil engineering and applied science.