John Doyle

John Doyle

California Institute of Technology

H-index: 103

North America-United States

About John Doyle

John Doyle, With an exceptional h-index of 103 and a recent h-index of 47 (since 2020), a distinguished researcher at California Institute of Technology, specializes in the field of control theory, systems biology, complex networks, robustness, architecture.

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

Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control

Control for societal-scale challenges: Road map 2030

Predictive control of linear discrete-time Markovian jump systems by learning recurrent patterns

Internal feedback in the cortical perception–action loop enables fast and accurate behavior

Flux exponent control predicts metabolic dynamics from network structure

Internal feedback in biological control: Architectures and examples

Internal feedback in biological control: Diversity, delays, and standard theory

Convex robust performance with structured uncertainties in System Level Synthesis

John Doyle Information

University

Position

___

Citations(all)

95698

Citations(since 2020)

14595

Cited By

85454

hIndex(all)

103

hIndex(since 2020)

47

i10Index(all)

297

i10Index(since 2020)

122

Email

University Profile Page

California Institute of Technology

Google Scholar

View Google Scholar Profile

John Doyle Skills & Research Interests

control theory

systems biology

complex networks

robustness

architecture

Top articles of John Doyle

Title

Journal

Author(s)

Publication Date

Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control

arXiv preprint arXiv:2401.15185

Nikolai Matni

Aaron D Ames

John C Doyle

2024/1/26

Control for societal-scale challenges: Road map 2030

Andrew Alleyne

Frank Allgöwer

Aaron Ames

Saurabh Amin

James Anderson

...

2023/5

Predictive control of linear discrete-time Markovian jump systems by learning recurrent patterns

Automatica

SooJean Han

Soon-Jo Chung

John C Doyle

2023/10/1

Internal feedback in the cortical perception–action loop enables fast and accurate behavior

Proceedings of the National Academy of Sciences

Jing Shuang Li

Anish A Sarma

Terrence J Sejnowski

John C Doyle

2023/9/26

Flux exponent control predicts metabolic dynamics from network structure

Fangzhou Xiao

Jing Shuang Li

John C Doyle

2023

Internal feedback in biological control: Architectures and examples

Anish A. Sarma

Jing Shuang Li

Josefin Stenberg

Gwyneth Card

Elizabeth S. Heckscher

...

2021/10/11

Internal feedback in biological control: Diversity, delays, and standard theory

Josefin Stenberg

Jing Shuang Li

Anish A Sarma

John C Doyle

2021/9/24

Convex robust performance with structured uncertainties in System Level Synthesis

Anish A Sarma

John C Doyle

2022/12/6

v-Analysis: A New Notion of Robustness for Large Systems with Structured Uncertainties

Olle Kjellqvist

John C Doyle

2022/12/6

Distributed robust control for systems with structured uncertainties

Jing Shuang Li

John C Doyle

2022/4/5

Diversity deconstrains component limitations in sensorimotor control

Yorie Nakahira

Quanying Liu

Terrence Sejnowski

John Doyle

2022/10/20

Locality, Delays, and Internal Feedback in Sensorimotor Control Part 2: System Level Synthesis and Architecture

arXiv preprint arXiv:2109.11757

Jing Shuang Li

John C Doyle

2021/9/24

Descending Predictive Feedback: From Optimal Control to the Sensorimotor System

arXiv preprint arXiv:2103.16812

Jing Shuang Li

Anish A Sarma

John C Doyle

2021/3/31

Stability and control of biomolecular circuits through structure

Fangzhou Xiao

Mustafa Khammash

John C Doyle

2021/5/25

Diversity-enabled sweet spots in layered architectures and speed–accuracy trade-offs in sensorimotor control

Proceedings of the National Academy of Sciences

Yorie Nakahira

Quanying Liu

Terrence J Sejnowski

John C Doyle

2021/6/1

A Two-Part Controller Synthesis Approach for Nonlinear Stochastic Systems Perturbed by L\'evy Noise Using Renewal Theory and HJB-Based Impulse Control

arXiv preprint arXiv:2107.10441

SooJean Han

Soon-Jo Chung

2021/7/22

Online robust control of nonlinear systems with large uncertainty

Dimitar Ho

Hoang Le

John Doyle

Yisong Yue

2021/3/18

Control-theoretic immune tradeoffs explain SARS-CoV-2 virulence and transmission variation

bioRxiv

Anish A Sarma

Aartik Sarma

Marie Csete

Peter P Lee

John C Doyle

2021/4/26

Frontiers in scalable distributed control: SLS, MPC, and beyond

Jing Shuang Li

Carmen Amo Alonso

John C. Doyle

2021/5

Systems level model of dietary effects on cognition via the microbiome-gut-brain axis

Michaëlle N Mayalu

Anish Sarma

Fangzhou Xiao

John C Doyle

Richard M Murray

2021/6/29

See List of Professors in John Doyle University(California Institute of Technology)

Co-Authors

H-index: 95
Steven H. Low

Steven H. Low

California Institute of Technology

H-index: 70
Pramod Khargonekar

Pramod Khargonekar

University of California, Irvine

H-index: 61
Andrew Packard

Andrew Packard

University of California, Berkeley

H-index: 54
Bruce A. Francis

Bruce A. Francis

University of Toronto

H-index: 49
Jean Carlson

Jean Carlson

University of California, Santa Barbara

H-index: 41
Fernando Paganini

Fernando Paganini

Universidad ORT Uruguay

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