About

Karen Chen is an Associate Professor at NC State's Edward P. Fitts Department of Industrial and Systems Engineering. Her research focuses on areas within health systems engineering, human factors and ergonomics, and supply chain and logistics. She is involved in advancing knowledge and practices in these fields, contributing to the academic and practical understanding of complex systems related to health and human factors.

Research topics

• Electronic engineering
• Composite material
• Materials science
• Engineering
• Optoelectronics
• Telecommunications
• Electrical engineering
• Gerontology
• Medicine
• Internal medicine
• Oncology
• Physics
• Pathology
• Mechanical engineering
• Family medicine

Selected publications

• Examining User Interactions With Signaling Elements in a Virtual Reality Learning Application

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2025-08-11

  articleSenior author

  This preliminary study examined how users leveraged three different types of signaling elements in Scale Worlds, an immersive virtual reality (IVR) application designed to improve size and scale cognition. Signaling elements, which are instructional cues in the form of graphics, colors, sounds, or text in IVR, may improve learning outcomes by enhancing related cognitive processes. However, it is unclear the extent to which learners utilize these signaling elements in practice. A think-aloud protocol was used to examine how participants engaged with signaling elements, with thematic analysis suggesting that numerical measures were a particularly salient cue for conceptualizing the size and scale of entities in IVR. These findings can guide design decisions for future work on educational IVR in the context of size and scale cognition or STEM education, as implementing numerical measures to facilitate mathematical reasoning in IVR environments may bolster learning outcomes related to numeracy and conceptual understanding.

  PublisherDOI

• DATA SCIENCE CAREER PATHWAYS: AN INSTITUTIONAL ECOSYSTEM CASE STUDY

  EDULEARN proceedings · 2025-06-01

  articleSenior author
  PublisherDOI

• Affordable, manageable, practical, and scalable (AMPS) high-yield and high-gain inertial fusion

  ArXiv.org · 2025-04-14

  preprintOpen access

  High-yield inertial fusion offers a transformative path to affordable clean firm power and advanced defense capabilities. Recent milestones at large facilities, particularly the National Ignition Facility (NIF), have demonstrated the feasibility of ignition but highlight the need for approaches that can deliver large amounts of energy to fusion targets at much higher efficiency and lower cost. We propose that pulser-driven inertial fusion energy (IFE), which uses high-current pulsed-power technology to compress targets to thermonuclear conditions, can achieve this goal. In this paper, we detail the physics basis for pulser IFE, focusing on magnetized liner inertial fusion (MagLIF), where cylindrical metal liners compress DT fuel under strong magnetic fields and pre-heat. We discuss how the low implosion velocities, direct-drive efficiency, and scalable pulser architecture can achieve ignition-level conditions at low capital cost. Our multi-dimensional simulations, benchmarked against experiments at the Z facility, show that scaling from 20 MA to 50-60 MA of current enables net facility gain. We then introduce our Demonstration System (DS), a pulsed-power driver designed to deliver more than 60 MA and store approximately 80 MJ of energy. The DS is designed to achieve a 1000x increase in effective performance compared to the NIF, delivering approximately 100x greater facility-level energy gain -- and importantly, achieving net facility gain, or Qf>1 -- at just 1/10 the capital cost. We also examine the engineering requirements for repetitive operation, target fabrication, and chamber maintenance, highlighting a practical roadmap to commercial power plants.

  PublisherOA PDFDOI

• Human Factors Extended Reality Showcase

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2025-07-23

  article1st authorCorresponding

  The Human Factors Extended Reality (XR) Showcase is an annual, interactive hands-on demonstration session of XR technologies and applications. Attendees can walk to different stations to experience the applications while the presenter explains. The 12 interactive demonstration stations highlight the integration of XR technologies and other technologies, including haptic devices and artificial intelligence, to enable human factor research and applications that span training, learning, research assessment, and simulations. Aligned with the mission of HFES, the purpose of the XR Showcase is to enable individuals to acquire knowledge about XR applications through interactive demonstrations, increase exposure of XR to the HFES community, support content visualization of interdisciplinary research, and create an exchange forum to support communication and collaboration.

  PublisherDOI

• Affordable, manageable, practical, and scalable (AMPS) high-yield and high-gain inertial fusion

  Physics of Plasmas · 2025-09-01 · 11 citations

  articleOpen access

  High-yield inertial fusion offers a transformative path to affordable, clean, firm power and advanced defense capabilities. Recent milestones at large facilities, particularly the National Ignition Facility (NIF), have demonstrated the feasibility of ignition but highlight the need for approaches that can deliver large amounts of energy to fusion targets at much higher efficiency and lower cost. We propose that pulser-driven inertial fusion energy (IFE), which uses high-current pulsed-power technology to compress targets to thermonuclear conditions, can achieve this goal. In this paper, we detail the physics basis for pulser IFE, focusing on magnetized liner inertial fusion, where cylindrical metal liners compress DT fuel under strong magnetic fields and preheat. We discuss how the low implosion velocities, direct-drive efficiency, and scalable pulser architecture can achieve ignition-level conditions at low capital cost. Our multi-dimensional simulations, benchmarked against experiments at the Z facility, show that scaling from 20 to 50–60 MA of current enables net facility gain. We then introduce our Demonstration System (DS), a pulsed-power driver designed to deliver more than 60 MA and store approximately 80 MJ of energy. The DS is designed to achieve a 1000× increase in effective performance compared to the NIF, delivering approximately 100× greater facility-level energy gain—and importantly, achieving net facility gain, or Qf>1—at just 1/10 the capital cost. We also examine the engineering requirements for repetitive operation, target fabrication, and chamber maintenance, highlighting a practical roadmap to commercial power plants.

  PublisherOA PDFDOI

• Mental Models of Gestural Interaction for Information Processing in Virtual Reality

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2025-07-16

  articleSenior author

  Virtual reality (VR) provides an immersive medium for information processing. Gestures offer a natural and intuitive means of translating cognitive processes into physical actions, making them a promising interaction method to support information processing in VR. However, how gestures reflect and map abstract cognitive tasks to physical interactions remains underexplored. To address this gap, this study explored the mental models by which end-users design gestural interactions to support information processing in VR. Using a gesture elicitation method, 8 participants created 445 gestures representing 19 cognitive processes in Bloom’s taxonomy. Five categories of mental models were identified: linguistic-symbolic, spatial-manipulative, metaphoric, social-conventional, and traditional graphical user interface-derived. Furthermore, the study found that the cognitive process categories affected the mental model adoption, with higher-order cognitive processes prompting more human-like interaction. These findings suggest the potential for developing more natural interactions for cognitive tasks and offer guidance for designing gestural interactions in VR.

  PublisherDOI

• Measuring Size and Scale: The Development and Validation of the Assessment of Size and Scale Cognition (ASSC)

  Research in Science Education · 2025-06-26 · 1 citations

  articleOpen accessSenior author

  “Scale, proportion, and quantity” is a crosscutting concept (CCC) identified by the Next Generation Science Standards that underpins disciplinary core ideas across science disciplines. Size and scale cognition is a component of this CCC that research has demonstrated is difficult for students. However, instruments available to assess students’ size and scale cognition are time-intensive, limited in scope, or difficult to replicate. Overcoming these limitations would support the development of tailored instructional supports and facilitate the investigation of student conceptions. This paper describes the development and validation of a novel instrument, the Assessment of Size and Scale Cognition, a computer-based assessment. Task items were developed in alignment with the framework to characterize and scaffold size and scale cognition and guided by already existing instruments. Evidence of validity and reliability was obtained through an iterative process of review among content experts, experts in graphic design and human-computer interaction, and members of the target population. We conducted a pilot test with 518 first-year undergraduate students and used response data to assess psychometric properties. Results suggest this instrument is reliable and can be used to measure students’ size and scale cognition. The iterative refinement of the instrument and stakeholder contributions are discussed.

  PublisherOA PDFDOI

• Human-Centered eXtended Reality for Occupational Applications in the Era of Industry 5.0: Introduction to the Special Issue

  IISE Transactions on Occupational Ergonomics and Human Factors · 2025-06-04

  article
  PublisherDOI

• Privacy-Aware EMG signal synthesis for ergonomic studies using a generative diffusion model

  Biomedical Signal Processing and Control · 2025-11-05

  articleOpen access

  Electromyography (EMG) is an important tool for monitoring muscle activity level during occupational tasks and thereby supporting preventive measures to mitigate work-related musculoskeletal disorders (WMSDs). Machine learning techniques have recently advanced EMG data analysis, enabling improvements in occupational activity recognition and ergonomics assessments. However, these techniques face challenges from limited EMG data availability due to privacy constraints. To address this, our research introduces a U-Net-based diffusion model for synthesizing EMG signals associated with common manual material handling (MMH) tasks. This model aims to preserve the statistical characteristics of original EMG data in the synthesized signals. Evaluation shows that the synthesized data visually resembles the original in both time and frequency domains, capturing similar patterns. Quantitative analysis further demonstrates that the model effectively captures essential EMG features, with statistical testing showing no significant evidence that the original and synthesized data differ in distribution. A classifier trained on real EMG data to identify four types of occupational tasks performs reliably when tested on synthesized EMG signals, demonstrating the feasibility of using EMG data synthesis for activity classification tasks. These findings highlight the effectiveness of the proposed EMG data synthesis method, which addresses privacy concerns and enriches EMG datasets for biomedical and occupational health research.

  PublisherDOI

• Applying Engineering Anthropometry to Mitigate Eye Strain in Virtual Environments

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2025-09-01

  articleSenior author

  This study applies engineering anthropometry and Monte Carlo simulations to define ergonomic guidelines for minimizing vergence-accommodation conflict in virtual environments. Interpupillary distance (IPD) data from three anthropometric datasets (ANSUR I, ANSUR II, CAESAR) were bootstrapped to determine conservative viewing-distance limits accommodating 99% of users. Simulations considered various IPD calibration errors, fixed IPD settings, and focal distances typical of commercial displays. Results established practical zones of comfortable disparity (ZoCD) and vergence to guide virtual interface design.

  PublisherDOI

Recent grants

• Virtual Reality to Improve Students’ Understanding of the Extremes of Scale in STEM

  NSF · $1.3M · 2021–2025

• CRII: CHS: Do virtual behaviors represent reality: Examining human behavioral validity in virtual reality interactions

  NSF · $175k · 2019–2022

Frequent coauthors

• P. H. Hansen

  19 shared

• A. J. Beddall

  Istinye University

  18 shared

• S. A. Olivares Pino

  Istituto Nazionale di Fisica Nucleare, Gruppo Collegato di Udine

  17 shared

• C. C. Ohm

  17 shared

• M. Shimojima

  16 shared

• Mary E. Sesto

  University of Wisconsin–Madison

  15 shared

• Alexander G. Raufi

  John Brown University

  15 shared

• E. Yu. Soldatov

  Universitat de València

  14 shared

Education

• Ph.D., Industrial Engineering

  University of North Carolina at Chapel Hill

  2010

• M.S., Industrial Engineering

  University of North Carolina at Chapel Hill

  2006

• B.S., Industrial Engineering

  University of North Carolina at Charlotte

  2004

Awards & honors

• Girish Gopalakrishnan award-winning workplace improvements