Ioannis Kevrekidis

Ioannis Kevrekidis

Johns Hopkins University

H-index: 86

North America-United States

About Ioannis Kevrekidis

Ioannis Kevrekidis, With an exceptional h-index of 86 and a recent h-index of 40 (since 2020), a distinguished researcher at Johns Hopkins University, specializes in the field of chemical engineering, applied mathematics.

His recent articles reflect a diverse array of research interests and contributions to the field:

On-manifold projected gradient descent

A recursively recurrent neural network (R2N2) architecture for learning iterative algorithms

Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification

Data-driven and physics informed modeling of Chinese Hamster Ovary cell bioreactors

Staggered grids for multidimensional multiscale modelling

Intelligent Attractors for Singularly Perturbed Dynamical Systems

Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks

Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era

Ioannis Kevrekidis Information

University

Position

___

Citations(all)

30482

Citations(since 2020)

11884

Cited By

22079

hIndex(all)

86

hIndex(since 2020)

40

i10Index(all)

360

i10Index(since 2020)

166

Email

University Profile Page

Johns Hopkins University

Google Scholar

View Google Scholar Profile

Ioannis Kevrekidis Skills & Research Interests

chemical engineering

applied mathematics

Top articles of Ioannis Kevrekidis

Title

Journal

Author(s)

Publication Date

On-manifold projected gradient descent

Frontiers in Computer Science

Aaron Mahler

Tyrus Berry

Tom Stephens

Harbir Antil

Michael Merritt

...

2024/2/14

A recursively recurrent neural network (R2N2) architecture for learning iterative algorithms

SIAM Journal on Scientific Computing

Danimir T Doncevic

Alexander Mitsos

Yue Guo

Qianxiao Li

Felix Dietrich

...

2024/4/30

Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification

arXiv preprint arXiv:2401.16683

Dimitris G Giovanis

Dimitrios Loukrezis

Ioannis G Kevrekidis

Michael D Shields

2024/1/30

Data-driven and physics informed modeling of Chinese Hamster Ovary cell bioreactors

Computers & Chemical Engineering

Tianqi Cui

Tom Bertalan

Nelson Ndahiro

Pratik Khare

Michael Betenbaugh

...

2024/4/1

Staggered grids for multidimensional multiscale modelling

Computers & Fluids

J Divahar

Anthony J Roberts

Trent W Mattner

Judith E Bunder

Ioannis G Kevrekidis

2024/3/15

Intelligent Attractors for Singularly Perturbed Dynamical Systems

arXiv preprint arXiv:2402.15839

Daniel A Serino

Allen Alvarez Loya

JW Burby

Ioannis G Kevrekidis

Qi Tang

2024/2/24

Nonlinear Discrete-Time Observers with Physics-Informed Neural Networks

arXiv preprint arXiv:2402.12360

Hector Vargas Alvarez

Gianluca Fabiani

Ioannis G Kevrekidis

Nikolaos Kazantzis

Constantinos Siettos

2024/2/19

Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era

Journal of Computational Physics

Eleni D Koronaki

Nikolaos Evangelou

Cristina P Martin-Linares

Edriss S Titi

Ioannis G Kevrekidis

2024/6/1

Two novel families of multiscale staggered patch schemes efficiently simulate large-scale, weakly damped, linear waves

Computer Methods in Applied Mechanics and Engineering

J Divahar

Anthony J Roberts

Trent W Mattner

Judith E Bunder

Ioannis G Kevrekidis

2023/8/1

Locating saddle points using gradient extremals on manifolds adaptively revealed as point clouds

Chaos: An Interdisciplinary Journal of Nonlinear Science

A Georgiou

H Vandecasteele

JM Bello-Rivas

I Kevrekidis

2023/12/1

Equation-Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example MO Williams, YM Psarellis, D. Pozharskiy, C. Chong, F. Li, J. Yang

Handbook of Dynamic Data Driven Applications Systems: Volume 2

PG Kevrekidis

IG Kevrekidis

2023/9/14

On equivalent optimization of machine learning methods

arXiv preprint arXiv:2302.09160

William T Redman

Juan M Bello-Rivas

Maria Fonoberova

Ryan Mohr

Ioannis G Kevrekidis

...

2023/2/17

Data-driven control of agent-based models: An equation/variable-free machine learning approach

Journal of Computational Physics

Dimitrios G Patsatzis

Lucia Russo

Ioannis G Kevrekidis

Constantinos Siettos

2023/4/1

Learning Parametric Koopman Decompositions for Prediction and Control

arXiv preprint arXiv:2310.01124

Yue Guo

Milan Korda

Ioannis G Kevrekidis

Qianxiao Li

2023/10/2

Machine learning-assisted crystal engineering of a zeolite

Nature communications

Xinyu Li

He Han

Nikolaos Evangelou

Noah J Wichrowski

Peng Lu

...

2023/5/31

Double diffusion maps and their latent harmonics for scientific computations in latent space

Journal of Computational Physics

Nikolaos Evangelou

Felix Dietrich

Eliodoro Chiavazzo

Daniel Lehmberg

Marina Meila

...

2023/7/15

Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling

arXiv preprint arXiv:2311.00797

Nikolaos Evangelou

Tianqi Cui

Juan M Bello-Rivas

Alexei Makeev

Ioannis G Kevrekidis

2023/11/1

Black and gray box learning of amplitude equations: Application to phase field systems

Physical Review E

Felix P Kemeth

Sergio Alonso

Blas Echebarria

Ted Moldenhawer

Carsten Beta

...

2023/2/16

Implementation and (Inverse Modified) Error Analysis for implicitly-templated ODE-nets

arXiv preprint arXiv:2303.17824

Aiqing Zhu

Tom Bertalan

Beibei Zhu

Yifa Tang

Ioannis G Kevrekidis

2023/3/31

Some of the variables, some of the parameters, some of the times, with some physics known: Identification with partial information

Computers & Chemical Engineering

Saurabh Malani

Tom S Bertalan

Tianqi Cui

José L Avalos

Michael Betenbaugh

...

2023/10/1

See List of Professors in Ioannis Kevrekidis University(Johns Hopkins University)