Faculty

Institution

Unit

Venue

Meeko Oishi

Professor

University of New Mexico

Affiliations

School of Engineering

Electrical & Computer Engineering

Meeko Oishi is currently serving as an Electrical & Computer Engineering Professor at University of New Mexico.

Honors

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Experiences

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Education

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Meeko Oishi

University of New Mexico

Professor

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systems engineering applied mathematics machine learning computer science automatic control control systems aerospace engineering robotics parkinson's disease reachability analysis control engineering aeronautics artificial intelligence assistive technology control system technology physiological measurements control technology stochastic reachability unmanned aerial vehicles motor control control optimization control science chronobiology hybrid systems human-computer interaction kernel methods aerial robotics astronautics object tracking health monitoring stochastic control brain stimulation hilbert space embeddings computational intelligence observability motion control patient monitoring guidance system vestibular system viability kernel obstacle avoidance motion planning kernel distribution embeddings data-driven stochastic reachability fourier transforms neurorehabilitation movement disorders health technology pineal research control design flight control intelligent robotics stochastic hybrid system tracking systems space vehicles data safety melatonin computational techniques motor performance vstol aircraft reachable sets reach-avoid sets schur-based decomposition linear time-invariant systems aircraft nonlinear analysis experimental medicine data security thermal engineering light science sexual selection distributed robotics performance prediction nonlinear control spacecraft attitude control neurostimulation real-time control stochastic process process control

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Assessing the Relationship Between Learning Stages and Prefrontal Cortex Activation in a Psychomotor Task. Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2024)

Kendric R. OrtizJacob G. HunterAdam J. ThorpeMadeleine YuhTahira ReidNeera JainMeeko Oishi

prefrontal cortex activationpsychomotor taskneurosciencehuman factors

Blameless and Optimal Control Under Prioritized Safety Constraints. 2022 American Control Conference (ACC) (2024)

Natalia PavlasekSarah H.Q. LiBehçet AçikmeşeMeeko OishiClaus Danielson

safety constraintsspace explorationaerospace engineeringoptimal control

Characterizing the Effect of Mind Wandering on Partially Autonomous Braking Dynamics. ACM transactions on cyber-physical systems (2024)

Harini SridharGaojian HuangAdam ThorpeMeeko OishiBrandon J. Pitts

computer scienceneurosciencecognitive sciencesystems neurosciencecognitive neurosciencecyberneticscyber-physical systems

Classification of Human Learning Stages via Kernel Distribution Embeddings. IEEE Open Journal of Control Systems (2024)

Madeleine Shuhn-Tsuan YuhKendric Ray OrtizKylie Sue Sommer-KohrtMeeko OishiNeera Jain

control systemscomputer scienceautomatic classificationpattern recognitionclassification methodmachine learningcontrol sciencedata classificationcontrol engineeringsystems engineeringkernel distribution embeddingscontrol system technologyautomatic control

Forward Reachability for Discrete-Time Nonlinear Stochastic Systems via Mixed-Monotonicity and Stochastic Order. arXiv (Cornell University) (2024)

Sivaramakrishnan, VigneshDevonport, Rosalyn A.Arcak, MuratOishi, Meeko M. K.

machine learningstochastic orderapplied mathematics

Open-Loop Chance Constrained Stochastic Optimal Control via the One-Sided Vysochanskij–Petunin Inequality. IEEE Transactions on Automatic Control (2024)

Isabella PaculaMeeko Oishi

computer scienceuncertainty analysisstochastic optimal controlopen-loop chanceautomatic controlone-sided vysochanskij-petunin inequality

Personalized Data-Driven State Models of the Circadian Dynamics in a Biometric Signal. (2024)

Chukwuemeka O. IkeYunshi WenJohn T. WenMeeko M.K. OishiLee K. BrownA. Agung Julius

statisticsmachine learningtime seriesdata-driven predictionbiometric signalneural network (machine learning)data sciencehigh levelphysiological measurementsmachine learning researchrecurrent neural networksdata-driven state modelsbiometricschronobiology

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge With Data-Driven Control. 2022 American Control Conference (ACC) (2024)

Adam J. ThorpeCyrus NearyFranck DjeumouMeeko M. K. OishiUfuk Topcu

computational intelligencecontrol optimizationmachine learningdata sciencephysic aware machine learningsystems engineeringartificial intelligenceapplied mathematicsphysics-informed kernel embeddingskernel methodslearning control

SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks. arXiv (Cornell University) (2024)

Sivaramakrishnan, VigneshKalagarla, Krishna C.Devonport, RosalynPilipovsky, JoshuaTsiotras, PanagiotisOishi, Meeko

computer sciencemachine learningneural networksprobabilistic verificationneural network (machine learning)

Chance Constrained Stochastic Optimal Control for Arbitrarily Disturbed Lti Systems via the One-Sided Vysochanskij-Petunin Inequality. arXiv (Cornell University) (2023)

Priore, ShawnOishi, Meeko

risk managementstochastic optimal controllti systemsdynamical systemsapplied mathematicsone-sided vysochanskij-petunin inequality

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Meeko Oishi

Professor

University of New Mexico

Affiliations

School of Engineering

Electrical & Computer Engineering

Meeko Oishi is currently serving as an Electrical & Computer Engineering Professor at University of New Mexico.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Meeko Oishi

University of New Mexico

Professor

You can click a keyword to filter the displayed items

Video Presentations

Notable Scholarly Works

Notable Federal Grants

Collaborators

Assessing the Relationship Between Learning Stages and Prefrontal Cortex Activation in a Psychomotor Task. Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2024)

Kendric R. OrtizJacob G. HunterAdam J. ThorpeMadeleine YuhTahira ReidNeera JainMeeko Oishi

prefrontal cortex activationpsychomotor taskneurosciencehuman factors

Blameless and Optimal Control Under Prioritized Safety Constraints. 2022 American Control Conference (ACC) (2024)

Natalia PavlasekSarah H.Q. LiBehçet AçikmeşeMeeko OishiClaus Danielson

safety constraintsspace explorationaerospace engineeringoptimal control

Characterizing the Effect of Mind Wandering on Partially Autonomous Braking Dynamics. ACM transactions on cyber-physical systems (2024)

Harini SridharGaojian HuangAdam ThorpeMeeko OishiBrandon J. Pitts

computer scienceneurosciencecognitive sciencesystems neurosciencecognitive neurosciencecyberneticscyber-physical systems

Classification of Human Learning Stages via Kernel Distribution Embeddings. IEEE Open Journal of Control Systems (2024)

Madeleine Shuhn-Tsuan YuhKendric Ray OrtizKylie Sue Sommer-KohrtMeeko OishiNeera Jain

Forward Reachability for Discrete-Time Nonlinear Stochastic Systems via Mixed-Monotonicity and Stochastic Order. arXiv (Cornell University) (2024)

Sivaramakrishnan, VigneshDevonport, Rosalyn A.Arcak, MuratOishi, Meeko M. K.

machine learningstochastic orderapplied mathematics

Open-Loop Chance Constrained Stochastic Optimal Control via the One-Sided Vysochanskij–Petunin Inequality. IEEE Transactions on Automatic Control (2024)

Isabella PaculaMeeko Oishi

computer scienceuncertainty analysisstochastic optimal controlopen-loop chanceautomatic controlone-sided vysochanskij-petunin inequality

Personalized Data-Driven State Models of the Circadian Dynamics in a Biometric Signal. (2024)

Chukwuemeka O. IkeYunshi WenJohn T. WenMeeko M.K. OishiLee K. BrownA. Agung Julius

Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge With Data-Driven Control. 2022 American Control Conference (ACC) (2024)

Adam J. ThorpeCyrus NearyFranck DjeumouMeeko M. K. OishiUfuk Topcu

SAVER: A Toolbox for Sampling-Based, Probabilistic Verification of Neural Networks. arXiv (Cornell University) (2024)

Sivaramakrishnan, VigneshKalagarla, Krishna C.Devonport, RosalynPilipovsky, JoshuaTsiotras, PanagiotisOishi, Meeko

computer sciencemachine learningneural networksprobabilistic verificationneural network (machine learning)

Chance Constrained Stochastic Optimal Control for Arbitrarily Disturbed Lti Systems via the One-Sided Vysochanskij-Petunin Inequality. arXiv (Cornell University) (2023)

Priore, ShawnOishi, Meeko

risk managementstochastic optimal controllti systemsdynamical systemsapplied mathematicsone-sided vysochanskij-petunin inequality

1
2
3
4
5
15
10 / page

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Inseok Hwang

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systems engineering

aerospace engineering

Ming Xin

Institution

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aerospace engineering

automatic control

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Institution

University of California, Santa Cruz

robust control

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assistive robot

Evangelos Theodorou

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intelligent control

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unmanned aerial vehicle

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