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Mary L. Cummings

Mary L. Cummings

D-Index & Metrics

Computer Science

D-Index
36
Citations
5728
World Ranking
11236
National Ranking
4642

Overview

Mary L. Cummings is affiliated with Duke University in the United States. Their research spans multiple fields, primarily focused on engineering and psychology, with an emphasis on the interaction between humans and automation in safety-critical environments.

The scientist has contributed extensively to the study of human-automation interaction and safety, occupational health and safety research, as well as traffic and road safety. Other notable topics include air traffic management and optimization, autonomous vehicle technology and safety, ethics and social impacts of AI, and aerospace and aviation technology.

Mary L. Cummings has published research in several frequent venues, including:

  • IEEE Transactions on Intelligent Vehicles
  • AIAA Scitech 2020 Forum
  • International Journal of Human-Computer Studies
  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting
  • arXiv (Cornell University)

They have collaborated frequently with scholars such as Songpo Li, Ben Bauchwitz, Haibei Zhu, Vishwa Alaparthy, and Wanyi Chen.

Recent papers include:

  • Rethinking the Maturity of Artificial Intelligence in Safety-Critical Settings (2021) published in AI Magazine
  • Safety Implications of Variability in Autonomous Driving Assist Alerting (2021) published in IEEE Transactions on Intelligent Transportation Systems
  • Assessing the impact of autonomy and overconfidence in UAV first-person view training (2021) published in Applied Ergonomics
  • Acoustic Detection of Drones through Real-time Audio Attribute Prediction (2020) published in AIAA Scitech 2020 Forum
  • Subjectivity in the Creation of Machine Learning Models (2021) published in Journal of Data and Information Quality

In terms of fields of study, their work cuts across engineering with 26 publications and psychology with 13. Within these fields, subfields of particular focus include social psychology, aerospace engineering, safety, risk, reliability and quality, artificial intelligence, and radiological and ultrasound technology.

Best Publications

  • Automation Bias in Intelligent Time Critical Decision Support Systems

    Mary Cummings

  • Automation Architecture for Single Operator, Multiple UAV Command and Control,

    M. L. Cummings;S. Bruni;S. Mercier;P. J. Mitchell

  • Developing operator capacity estimates for supervisory control of autonomous vehicles.

    Mary L. Cummings;Stephanie A. Guerlain

  • Automation and Accountability in Decision Support System Interface Design

    Mary L. Cummings

  • Artificial Intelligence and the Future of Warfare

    Mary ‘Missy’ L. Cummings

  • Boredom and Distraction in Multiple Unmanned Vehicle Supervisory Control

    Mary L. Cummings;C. Mastracchio;Kristopher M. Thornburg;A. Mkrtchyan

  • Predicting Controller Capacity in Supervisory Control of Multiple UAVs

    M.L. Cummings;P.J. Mitchell

  • The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling

    Mary L. Cummings;Andrew S. Clare;Christin Hart

  • Developing performance metrics for the supervisory control of multiple robots

    Jacob W. Crandall;M. L. Cummings

  • The need for command and control instant message adaptive interfaces: lessons learned from Tactical Tomahawk human-in-the-loop simulations.

    Mary L. Cummings

  • Collaborative Human–Automation Decision Making

    Mary L. Cummings;Sylvain Bruni

  • The Impact of Human–Automation Collaboration in Decentralized Multiple Unmanned Vehicle Control

    M. L. Cummings;J. P. How;A. Whitten;O. Toupet

  • Predicting Operator Capacity for Supervisory Control of Multiple UAVs

    Mary L. Cummings;Carl E. Nehme;Jacob W. Crandall;Paul J. Mitchell

  • Modeling Workload Impact in Multiple Unmanned Vehicle Supervisory Control

    B Donmez;C Nehme;M L Cummings

  • Effects of Single Versus Multiple Warnings on Driver Performance

    Mary L. Cummings;Ryan M. Kilgore;Enlie Wang;Louis Tijerina

  • Identifying Predictive Metrics for Supervisory Control of Multiple Robots

    J.W. Crandall;M.L. Cummings

  • Designing an Interactive Local and Global Decision Support System for Aircraft Carrier Deck Scheduling

    Jason Christopher Ryan;M. L. Cummings;Nicholas Roy;Ashis Banerjee

  • Generating Requirements for Futuristic Hetrogenous Unmanned Systems

    Carl E. Nehme;Stacey D. Scott;M. L. Cummings;Carina Yumi Furusho

  • ASSISTING INTERRUPTION RECOVERY IN SUPERVISORY CONTROL OF MULTIPLE UAVS

    Stacey D. Scott;Stephane Mercier;M. L. Cummings;Enlie Wang

  • Operator Performance and Intelligent Aiding in Unmanned Aerial Vehicle Scheduling

    M.L. Cummings;A.S. Brzezinski;J.D. Lee

Frequent Co-Authors

Miroslav Pajic
Miroslav Pajic Duke University
Kris Hauser
Kris Hauser Duke University
John D. Lee
John D. Lee University of Wisconsin–Madison
Mark Campbell
Mark Campbell Cornell University
Ellen R. Stofan
Ellen R. Stofan Smithsonian Institution
Raja Parasuraman
Raja Parasuraman George Mason University
Mica R. Endsley
Mica R. Endsley SA Technologies (United States)

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