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Kumar Akash · Study

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Kumar Akash

6 works· latest 2020· 2 institutionscluster: provisionalORCID 0000-0003-2807-0943

h-index6

i106

Citations528

Works here6

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Most cited in this library

A Classification Model for Sensing Human Trust in Machines Using EEG and GSR2018 · 159 citations
Computational Modeling of the Dynamics of Human Trust During Human–Machine Interactions2018 · 101 citations
Real-Time Sensing of Trust in Human-Machine Interactions**This material is based upon work supported by the National Science Foundation under Award No. 1548616. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.2016 · 84 citations
Human Trust-Based Feedback Control: Dynamically Varying Automation Transparency to Optimize Human-Machine Interactions2020 · 72 citations
Dynamic modeling of trust in human-machine interactions2017 · 56 citations

Works

6 shown

Human Trust-Based Feedback Control: Dynamically Varying Automation Transparency to Optimize Human-Machine Interactions

IEEE Control Systems·2020·4 authors·Open access

72citations

Improving Human-Machine Collaboration Through Transparency-based Feedback – Part I: Human Trust and Workload Model

IFAC-PapersOnLine·2019·4 authors·Open access

56citations

A Classification Model for Sensing Human Trust in Machines Using EEG and GSR

ACM Transactions on Interactive Intelligent Systems·2018·4 authors·Open access

159citations

Computational Modeling of the Dynamics of Human Trust During Human–Machine Interactions

IEEE Transactions on Human-Machine Systems·2018·4 authors

101citations

Dynamic modeling of trust in human-machine interactions

Proceedings of the ... American Control Conference/Proceedings of the American Control Conference·2017·4 authors·other

56citations

Real-Time Sensing of Trust in Human-Machine Interactions**This material is based upon work supported by the National Science Foundation under Award No. 1548616. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

IFAC-PapersOnLine·2016·4 authors·Open access

84citations