Faculty

Institution

Unit

Venue

George Cybenko

Professor

Dartmouth College

Affiliations

Faculty of Arts and Sciences

Department of Computer Science

Department of Engineering Sciences—Thayer School of Engineering

George Cybenko is currently serving as a Computer Science Professor at Dartmouth College.

Honors

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Experiences

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Education

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George Cybenko

Dartmouth College

Professor

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Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

QUARL: Quantifying Adversarial Risks in Language Models. Proceedings of the AAAI Symposium Series (2024)

Joshua AckermanGeorge CybenkoPaul LintilhacHenry ScheibleNathaniel D. Bastian

machine learningadversarial machine learningcomputer sciencelanguage modelsadversarial risks

Research Report: Testing and Evaluating Artificial Intelligence Applications. (2024)

Paul LintilhacJoshua AckermanGeorge Cybenko

artificial intelligence applicationsartificial intelligencesystems engineering

Generative Deep Learning for Solutions to Data Deconflation Problems in Information and Operational Technology Networks. (2023)

Roger HallmanJohn MiguelArron LuAlejandro MonjeMohammad AlamGeorge Cybenko

machine learningdeep learninggenerative deep learningdata sciencesystems engineeringdata deconflation problems

Large Language Models for Fuzzing Parsers (Registered Report). (2023)

Joshua AckermanGeorge Cybenko

software testingfuzzingcomputer sciencenatural language processing

Attritable Multi-Agent Learning. (2021)

George CybenkoRoger Hallman

machine learningattritable multi-agent learningartificial intelligencemulti-agent learningcomputer sciencedistributed learning

Formal Languages, Deep Learning, Topology and Algebraicword Problems. (2021)

Joshua AckermanGeorge Cybenko

topologydeep learningalgebraicword problemsapplied mathematics

Inaugural Issue Editorial. High-Confidence Computing (2021)

Xiuzhen ChengWeifeng LvZhipeng Cai

editorial independencepolitical communicationinaugural issue editorialpublic relationspublic spherejournalism

Resilient Distributed Adaptive Cyber‐Defense Using Blockchain. (2021)

George CybenkoRoger Hallman

systems engineeringblockchainresilience

The Data Deconflation Problem: Moving From Classical to Emerging Solutions. (2021)

Roger HallmanGeorge Cybenko

data deconflation problemstatisticsdata sciencetime seriesapplied mathematics

Adaptation and Deception in Adversarial Cyber Operations. (2020)

George Cybenko

adversarial cyber operationscomputer scienceadaptation

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George Cybenko

Professor

Dartmouth College

Affiliations

Faculty of Arts and Sciences

Department of Computer Science

Department of Engineering Sciences—Thayer School of Engineering

George Cybenko is currently serving as a Computer Science Professor at Dartmouth College.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

George Cybenko

Dartmouth College

Professor

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

QUARL: Quantifying Adversarial Risks in Language Models. Proceedings of the AAAI Symposium Series (2024)

Joshua AckermanGeorge CybenkoPaul LintilhacHenry ScheibleNathaniel D. Bastian

machine learningadversarial machine learningcomputer sciencelanguage modelsadversarial risks

Research Report: Testing and Evaluating Artificial Intelligence Applications. (2024)

Paul LintilhacJoshua AckermanGeorge Cybenko

artificial intelligence applicationsartificial intelligencesystems engineering

Generative Deep Learning for Solutions to Data Deconflation Problems in Information and Operational Technology Networks. (2023)

Roger HallmanJohn MiguelArron LuAlejandro MonjeMohammad AlamGeorge Cybenko

machine learningdeep learninggenerative deep learningdata sciencesystems engineeringdata deconflation problems

Large Language Models for Fuzzing Parsers (Registered Report). (2023)

Joshua AckermanGeorge Cybenko

software testingfuzzingcomputer sciencenatural language processing

Attritable Multi-Agent Learning. (2021)

George CybenkoRoger Hallman

machine learningattritable multi-agent learningartificial intelligencemulti-agent learningcomputer sciencedistributed learning

Formal Languages, Deep Learning, Topology and Algebraicword Problems. (2021)

Joshua AckermanGeorge Cybenko

topologydeep learningalgebraicword problemsapplied mathematics

Inaugural Issue Editorial. High-Confidence Computing (2021)

Xiuzhen ChengWeifeng LvZhipeng Cai

editorial independencepolitical communicationinaugural issue editorialpublic relationspublic spherejournalism

Resilient Distributed Adaptive Cyber‐Defense Using Blockchain. (2021)

George CybenkoRoger Hallman

systems engineeringblockchainresilience

The Data Deconflation Problem: Moving From Classical to Emerging Solutions. (2021)

Roger HallmanGeorge Cybenko

data deconflation problemstatisticsdata sciencetime seriesapplied mathematics

Adaptation and Deception in Adversarial Cyber Operations. (2020)

George Cybenko

adversarial cyber operationscomputer scienceadaptation

1
2
3
4
5
48
10 / page

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autonomic computing

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