Faculty

Institution

Unit

Venue

Konstantinos Spiliopoulos

Professor CAS Math/Stat Director of Statistics

Boston University

Affiliations

College of Arts & Sciences

Mathematics & Statistics

Konstantinos Spiliopoulos is currently serving as a College Of Arts & Sciences Professor CAS Math/Stat Director of Statistics at Boston University.

Honors

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Experiences

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Education

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Konstantinos Spiliopoulos

Boston University

Professor CAS Math/Stat Director of Statistics

You can click a keyword to filter the displayed items

applied mathematics statistics stochastic process machine learning finance multiscale modeling modeling and simulation probability theory computer science empirical finance applied probability mathematical finance mathematical optimization large deviations statistical inference irreversible langevin samplers neural networks multiscale diffusions fluctuation analysis financial stability diffusion process portfolio optimization central limit theorem mean field analysis fractional brownian motion moderate deviations numerical simulations statistical methodology computational statistics financial studies finance research economic dynamics nonlinear science stochastic calculus financial mathematics stochastic differential equations option pricing data normalization financial network analysis variance reduction continuous time stochastic gradient descent importance sampling slow-fast diffusions random environments slow-fast systems scientific computing computational optimization mathematical sciences statistical physics engineering optimization fractional calculus nonlinear phenomena computational finance financial econometrics attractor model optimization constrained optimization pde-constrained optimization information theory theoretical modeling stochastic diffusion search credit markets financial risk management diffusion-based modeling applied mathematical modelling network convergence fractional stochastics volatility modeling bayesian econometrics sequential monte carlo financial system network theory multiscale analysis multiscale phenomena candidate selection computational science statistical analysis econophysics

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Mean Field Limits of Particle-Based Stochastic Reaction-Drift-Diffusion Models *. Nonlinearity (2025)

M HeldmanS A IsaacsonQ LiuK Spiliopoulos

stochastic dynamical systemsstochastic phenomenasystems biologynonlinear processnonlinear systemsdynamical systemsdiffusionnonlinear sciencenonlinear phenomenastochastic processnonlinear analysismean field limitsnonlinear equationsnonlinear dynamics

Stochastic Gradient Descent-Based Inference for Dynamic Network Models With Attractors. Journal of Computational and Graphical Statistics (2025)

Hancong PanXiaojing ZhuCantay CaliskanDino P. ChristensonKonstantinos SpiliopoulosDylan WalkerEric D. Kolaczyk

dynamic network modelschaos theorygraph theoryapplied mathematics

Quantitative Fluctuation Analysis of Multiscale Diffusion Systems via Malliavin Calculus. Stochastic Processes and their Applications (2024)

S. BourguinK. Spiliopoulos

materials sciencequantitative fluctuation analysisdiffusionmalliavin calculusapplied mathematicsapplied physicsmultiscale diffusion systems

Transport Map Unadjusted Langevin Algorithms: Learning and Discretizing Perturbed Samplers. Foundations of Data Science (2024)

Benjamin J. ZhangYoussef M. MarzoukKonstantinos Spiliopoulos

langevin algorithmsperturbed samplersdeep learningapplied mathematicsmachine learning

Disentangling Positive and Negative Partisanship in Social Media Interactions Using a Coevolving Latent Space Network With Attractors Model. Journal of the Royal Statistical Society Series A (Statistics in Society) (2023)

Xiaojing ZhuCantay CaliskanDino P ChristensonKonstantinos SpiliopoulosDylan WalkerEric D Kolaczyk

network theorypolitical sciencesocial influencesocial sciencessocial network analysissocial mediasocial media interactionsstatisticspolitical communicationnetwork analysis

Fluctuation Analysis for Particle-Based Stochastic Reaction–Diffusion Models. Stochastic Processes and their Applications (2023)

M. HeldmanS.A. IsaacsonJ. MaK. Spiliopoulos

applied physicsfluctuation analysisnumerical analysisapplied mathematics

Importance Sampling for Stochastic Reaction–Diffusion Equations in the Moderate Deviation Regime. Stochastic Partial Differential Equations Analysis and Computations (2023)

Ioannis GasteratosMichael SalinsKonstantinos Spiliopoulos

time seriesmoderate deviation regimestochastic reaction-diffusion equationsapplied mathematicsapplied physics

Moderate Deviation Principle for Multiscale Systems Driven by Fractional Brownian Motion. Journal of Theoretical Probability (2023)

Solesne BourguinThanh DangKonstantinos Spiliopoulos

multiscale systemsmoderate deviation principlefractional brownian motionapplied mathematicsprobability theory

Normalization Effects on Deep Neural Networks. Foundations of Data Science (2023)

Jiahui YuKonstantinos Spiliopoulos

machine learningdata normalizationdata sciencenormalization effects

Pde-Constrained Models With Neural Network Terms: Optimization and Global Convergence. Journal of Computational Physics (2023)

Justin SirignanoJonathan MacArtKonstantinos Spiliopoulos

computational optimizationneural network termsmachine learningmodel optimizationmathematical optimizationconstrained optimizationdeep learningpde-constrained optimizationapplied mathematicspde-constrained modelscomputer scienceglobal convergence

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Konstantinos Spiliopoulos

Professor CAS Math/Stat Director of Statistics

Boston University

Affiliations

College of Arts & Sciences

Mathematics & Statistics

Konstantinos Spiliopoulos is currently serving as a College Of Arts & Sciences Professor CAS Math/Stat Director of Statistics at Boston University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Konstantinos Spiliopoulos

Boston University

Professor CAS Math/Stat Director of Statistics

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Mean Field Limits of Particle-Based Stochastic Reaction-Drift-Diffusion Models *. Nonlinearity (2025)

M HeldmanS A IsaacsonQ LiuK Spiliopoulos

Stochastic Gradient Descent-Based Inference for Dynamic Network Models With Attractors. Journal of Computational and Graphical Statistics (2025)

Hancong PanXiaojing ZhuCantay CaliskanDino P. ChristensonKonstantinos SpiliopoulosDylan WalkerEric D. Kolaczyk

dynamic network modelschaos theorygraph theoryapplied mathematics

Quantitative Fluctuation Analysis of Multiscale Diffusion Systems via Malliavin Calculus. Stochastic Processes and their Applications (2024)

S. BourguinK. Spiliopoulos

materials sciencequantitative fluctuation analysisdiffusionmalliavin calculusapplied mathematicsapplied physicsmultiscale diffusion systems

Transport Map Unadjusted Langevin Algorithms: Learning and Discretizing Perturbed Samplers. Foundations of Data Science (2024)

Benjamin J. ZhangYoussef M. MarzoukKonstantinos Spiliopoulos

langevin algorithmsperturbed samplersdeep learningapplied mathematicsmachine learning

Xiaojing ZhuCantay CaliskanDino P ChristensonKonstantinos SpiliopoulosDylan WalkerEric D Kolaczyk

network theorypolitical sciencesocial influencesocial sciencessocial network analysissocial mediasocial media interactionsstatisticspolitical communicationnetwork analysis

Fluctuation Analysis for Particle-Based Stochastic Reaction–Diffusion Models. Stochastic Processes and their Applications (2023)

M. HeldmanS.A. IsaacsonJ. MaK. Spiliopoulos

applied physicsfluctuation analysisnumerical analysisapplied mathematics

Importance Sampling for Stochastic Reaction–Diffusion Equations in the Moderate Deviation Regime. Stochastic Partial Differential Equations Analysis and Computations (2023)

Ioannis GasteratosMichael SalinsKonstantinos Spiliopoulos

time seriesmoderate deviation regimestochastic reaction-diffusion equationsapplied mathematicsapplied physics

Moderate Deviation Principle for Multiscale Systems Driven by Fractional Brownian Motion. Journal of Theoretical Probability (2023)

Solesne BourguinThanh DangKonstantinos Spiliopoulos

multiscale systemsmoderate deviation principlefractional brownian motionapplied mathematicsprobability theory

Normalization Effects on Deep Neural Networks. Foundations of Data Science (2023)

Jiahui YuKonstantinos Spiliopoulos

machine learningdata normalizationdata sciencenormalization effects

Pde-Constrained Models With Neural Network Terms: Optimization and Global Convergence. Journal of Computational Physics (2023)

Justin SirignanoJonathan MacArtKonstantinos Spiliopoulos

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