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Kostia Zuev - Research
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Prospective Students and Collaborators

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 email me at kostia [at] caltech [dot] edu. 


Students
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)
Zhi Ren (Caltech)
Stavros Stavroglou (U of Liverpool)
Michail Vamvakaris (U of liverpool)
Stephen Wu (Caltech) 

[10]
[19]
[18]
[13]
[15] [16]



[17]
[C2] [20]
[11]


Coauthors
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
 (CUT)
Kimmo Soramäki (FNA)

[7]
[7] [8] [9] [11] [C3]
[E1] [C4]
[12]
[12]
[4]
[15
] [16]
[3] [5] [6] [7]
[12] [13] [14] [18]
[19]
[10][C2] [17] [19] [20]
[14]

[17]

Erdös Number
My Erdös number is (at most) 4:
KZ→Bianconi→Severini→Cameron→Erdös

KZ→Beer→Kreinovich→Blass→Erdös

Citations
Google Scholar:

Research Areas

My research is interdisciplinary. I like to branch out, learn new things, and jump on new problems.

I have written two independent Ph.D. dissertations and published papers being affiliated with departments of mathematics, physics, computer science, and civil engineering. According to Dyson's “birds-and-frogs” classification, I am a frog which occasionally makes very long jumps.

My research interests and expertise are in in the areas of applied probability, computational statistics, and data science with applications to rare events, network science, and quantitative finance.

● Rare Events: Rare Event Simulation, Estimation of Small Probabilities of Rare Events, Structural Reliability, Risk Analysis, Reliability and Resilience of Critical Infrastructure Networks, Cascading Failures.
See, for example: Introduction to Subset Simulation [C1], Rare Event Simulation [C3], Bayesian Post-Processor for Subset Simulation [7], Challenges of Estimating Rare Events in High Dimensions [3], Reliability of Critical Infrastructure Networks [C4], General Network Reliability Problem [11].

● Network Science: Complex Network Models, Network Data Analysis, Network Dynamics, Cascading Processes on Complex Networks, Exponential Random Graphs and Simplicial Complexes, Visibility Graphs, Multilayer Networks, Infrastructure Networks, Financial Networks.
See, for example: Geometric Preferential Attachment [12], Exponential Random Simplicial Complexes [13], Hamiltonian Dynamics of Complex Networks [14], Navigability of Random Geometric Graphs [18].

● Quantitative Finance: Financial Networks, Analysis of Financial Time Series, Causality of Stock Markets, Simulation Methods for Options Pricing, Machine Learning for Trading and Investing, Cryptocurrencies.
See, for example: Causality Networks of Financial Assets [17], Dynamic Analysis of S&P 500, FTSE 100 and EURO STOXX 50 Indices [19], Time Series Analysis of S&P 500 Index using Visibility Graphs [20], Efficient Pricing of Barrier Options [21], Investors' Behavior during Periods of Market Crashes [C2].