About

Dr. Eric Jing Du is a faculty member at the Engineering School of Sustainable Infrastructure & Environment. The provided page text does not include specific details about his research focus, background, or key contributions. Therefore, there is no available biographical information to summarize.

Research topics

• Computer Science
• Artificial Intelligence
• Engineering
• Simulation
• Human–computer interaction
• Mechanical engineering
• Medicine
• Knowledge management
• Aerospace engineering
• Telecommunications
• Control engineering
• Risk analysis (engineering)

Selected publications

• Launching Successful Datathons: Lessons Learned from Recent ASCE VIMS Datathons

  2024-01-25

  articleCorresponding

  Experiential learning has been an effective educational tool and provides a learning experience to students via “learning by doing.” Different forms of experiential learning practices are available for students in existing curriculums such as internships, field works, gaming/simulations, volunteering, and hackathons. Datathons, a form of hackathons that focus on data, have been effective in the computer science community and have been successfully launched in recent years in the architectural, engineering, construction (AEC) community as well. ASCE Computing Division’s Visualization, Information Modeling, and Simulation (VIMS) Committee has successfully launched datathons for the past couple years. Our experience shows that datathons require a significant thought process during the planning phase and a sound outreach plan for execution of these datathons to bring diversity to the pool of participants. This paper reports on the lessons learned (LL) accumulated over the past years while launching these datathons and aims to help communities from academia and industry for hosting future datathons by leveraging these LL for improved student experience. The lessons learned will be discussed in relation to the planning, data preparation, and outreach phases of datathons.

  PublisherDOI

• ROV Teleoperation based on Sensory Augmentation and Digital Twins

  Offshore Technology Conference · 2023-04-23 · 9 citations

  articleSenior author

  Abstract ROV operations are mainly performed via a traditional control kiosk and limited data feedback methods, such as the use of joysticks and camera view displays equipped on a surface vessel. This traditional setup requires significant personnel on board (POB) time and imposes high requirements for personnel training. This paper proposes a virtual reality (VR) based haptic-visual ROV teleoperation system that can substantially simplify ROV teleoperation and enhance the remote operator's situational awareness. This study leverages the recent development in Mixed Reality (MR) technologies, sensory augmentation, sensing technologies, and closed-loop control, to visualize and render complex underwater environmental data in an intuitive and immersive way. The raw sensor data will be processed with physics engine systems and rendered as a high-fidelity digital twin model in game engines. Certain features will be visualized and displayed via the VR headset, whereas others will be manifested as haptic and tactile cues via our haptic feedback systems. We applied a simulation approach to test the developed system. With our developed system, a high-fidelity subsea environment is reconstructed based on the sensor data collected from an ROV including the bathymetric, hydrodynamic, visual, and vehicle navigational measurements. Specifically, the vehicle is equipped with a navigation sensor system for real-time state estimation, an acoustic Doppler current profiler for far-field flow measurement, and a bio-inspired artificial literal-line hydrodynamic sensor system for near-field small-scale hydrodynamics. Optimized game engine rendering algorithms then visualize key environmental features as augmented user interface elements in a VR headset, such as color-coded vectors, to indicate the environmental impact on the performance and function of the ROV. In addition, augmenting environmental feedback such as hydrodynamic forces are translated into patterned haptic stimuli via a haptic suit for indicating drift-inducing flows in the near field. A pilot case study was performed to verify the feasibility and effectiveness of the system design in a series of simulated ROV operation tasks. ROVs are widely used in subsea exploration and intervention tasks, playing a critical role in offshore inspection, installation, and maintenance activities. The innovative ROV teleoperation feedback and control system will lower the barrier for ROV pilot jobs.

  PublisherDOI

• An eye gaze-aided virtual tape measure for smart construction

  Canadian Journal of Civil Engineering · 2023-05-09 · 1 citations

  article

  In construction, the accurate measurements are important in ensuring the quality of work delivered. Different measuring tools have been developed to help workers conduct accurate measuring. However, they may be subject to manipulation difficulties, such as the need for tap/gesture interaction. This paper proposes a novel eye gaze-aided virtual tape measure framework that provides a hands-free manner for conducting the measurements in construction. This framework consists of three components: data collection for point of interest, sensor calibration, and distance calculation. Its effectiveness is tested by measuring the dimensions of 15 common objects in laboratory and on-site environments and achieves the average absolute and relative errors of 2.4 cm and 4.8%. The absolute errors range from 0.3 to 7.3 cm. A comparison study is conducted to demonstrate its superior performance over iPhone’s Measure application. The results illustrate the feasibility and potential of using the framework to enable measures for smart construction.

  PublisherDOI

• How does perceived usefulness of an exoskeleton change with virtual reality training?

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2023-09-01

  article

  We investigated how novices’ perception of exoskeleton usefulness changes with different types of exposure to an exoskeleton; and when the biomechanical benefits and limitations of potential exoskeleton use are presented to them. Twenty young, healthy participants completed this study. The three types of informational exposures to a back-support exoskeleton (BSE) were: (1) Information-based, (2) Virtual Reality (VR)-based, and (3) hands-on experience (lifting a box using the BSE), where users virtually and physically completed various lifting/lowering tasks set at shoulder, waist, and ankle heights in symmetric and asymmetric positions. After every trial in each exposure, perceived usefulness was obtained. Overall, perceived usefulness ratings generally varied with major task variables (load, lift height, and trunk angle). The VR-based exposure appeared to clarify the specific circumstances under which the BSE was perceived to be useful and reduced extreme biases (positive or negative) that individuals may have developed prior to trying on a BSE.

  PublisherDOI

• Enabling automated facility maintenance from articulated robot Collision-Free designs

  Advanced Engineering Informatics · 2022 · 13 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Simulation
  PublisherDOI

• Sensitivity of Eye-Tracking Measures to Variations in Mental Workload while Learning to Operate a Physically Coupled Robot

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2022-09-01 · 1 citations

  article
  PublisherDOI

• Human‐centered intelligent training for emergency responders

  AI Magazine · 2022 · 19 citations

  • Computer Science
  • Computer Science
  • Human–computer interaction

  Abstract Emergency response (ER) workers perform extremely demanding physical and cognitive tasks that can result in serious injuries and loss of life. Human augmentation technologies have the potential to enhance physical and cognitive work‐capacities, thereby dramatically transforming the landscape of ER work, reducing injury risk, improving ER, as well as helping attract and retain skilled ER workers. This opportunity has been significantly hindered by the lack of high‐quality training for ER workers that effectively integrates innovative and intelligent augmentation solutions. Hence, new ER learning environments are needed that are adaptive, affordable, accessible, and continually available for reskilling the ER workforce as technological capabilities continue to improve. This article presents the research considerations in the design and integration of use‐inspired exoskeletons and augmented reality technologies in ER processes and the identification of unique cognitive and motor learning needs of each of these technologies in context‐independent and ER‐relevant scenarios. We propose a human‐centered artificial intelligence (AI) enabled training framework for these technologies in ER. Finally, how these human‐centered training requirements for nascent technologies are integrated in an intelligent tutoring system that delivers across tiered access levels, covering the range of virtual, to mixed, to physical reality environments, is discussed.

  PublisherOA PDFDOI

• Virtual Telepresence for the Future of ROV Teleoperations: Opportunities and Challenges

  Day 2 Tue, February 22, 2022 · 2022 · 24 citations

  Senior authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Underwater robots, including Remote Operating Vehicles (ROV) and Autonomous Underwater Vehicles (AUV), are currently used to support underwater missions that are either impossible or too risky to be performed by manned systems. In recent years the academia and robotic industry have paved paths for tackling technical challenges for ROV/AUV operations. The level of intelligence of ROV/AUV has increased dramatically because of the recent advances in low-power-consumption embedded computing devices and machine intelligence (e.g., AI). Nonetheless, operating precisely underwater is still extremely challenging to minimize human intervention due to the inherent challenges and uncertainties associated with the underwater environments. Proximity operations, especially those requiring precise manipulation, are still carried out by ROV systems that are fully controlled by a human pilot. A workplace-ready and worker-friendly ROV interface that properly simplifies operator control and increases remote operation confidence is the central challenge for the wide adaptation of ROVs. This paper examines the recent advances of virtual telepresence technologies as a solution for lowering the barriers to the human-in-the-loop ROV teleoperation. Virtual telepresence refers to Virtual Reality (VR) related technologies that help a user to feel that they were in a hazardous situation without being present at the actual location. We present a pilot system of using a VR-based sensory simulator to convert ROV sensor data into human-perceivable sensations (e.g., haptics). Building on a cloud server for real-time rendering in VR, a less trained operator could possibly operate a remote ROV thousand miles away without losing the minimum situational awareness. The system is expected to enable an intensive human engagement on ROV teleoperation, augmenting abilities for maneuvering and navigating ROV in unknown and less explored subsea regions and works. This paper also discusses the opportunities and challenges of this technology for ad hoc training, workforce preparation, and safety in the future maritime industry. We expect that lessons learned from our work can help democratize human presence in future subsea engineering works, by accommodating human needs and limitations to lower the entrance barrier.

  PublisherDOI

• Identifying Early Predictors of Learning in VR-based Drone Training

  Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 2022-09-01 · 9 citations

  article

  The use of small unmanned aerial systems, or drones, has grown rapidly in recent years, but the FAA has no formal requirement for hands-on training. Physical drone training has major limitations, and virtual reality (VR) offers a promising alternative. This study sought to identify early performance markers of learning in VR-based drone training using a physical controller. 14 participants completed a customized VR-based drone training curriculum, while performance metrics, perceptions of workload, and physiological data were collected. Participants were clustered into high and low performers based on a final evaluation task, and separate analyses of variance were conducted to test performance differences between the two groups over time in each training level. We found significant differences in the performance metrics and subjective workload of low and high performers throughout training, suggesting that performance can be predicted early in training and opening the door to future adaptive training systems.

  PublisherDOI

• Human-Centered Intelligent Training for Emergency Responders

  AI Magazine · 2022-03-31 · 8 citations

  articleOpen access

  Emergency response (ER) workers perform extremely demanding physical and cognitive tasks that can result in serious injuries and loss of life. Human augmentation technologies have the potential to enhance physical and cognitive work-capacities, thereby dramatically transforming the landscape of ER work, reducing injury risk, improving ER, as well as helping attract and retain skilled ER workers. This opportunity has been significantly hindered by the lack of high-quality training for ER workers that effectively integrates innovative and intelligent augmentation solutions. Hence, new ER learning environments are needed that are adaptive, affordable, accessible, and continually available for reskilling the ER workforce as technological capabilities continue to improve. This article presents the research considerations in the design and integration of use-inspired exoskeletons and augmented reality technologies in ER processes and the identification of unique cognitive and motor learning needs of each of these technologies in context-independent and ER-relevant scenarios. We propose a human-centered artificial intelligence (AI) enabled training framework for these technologies in ER. Finally, how these human-centered training requirements for nascent technologies are integrated in an intelligent tutoring system that delivers across tiered access levels, covering the range of virtual, to mixed, to physical reality environments, is discussed.

  PublisherOA PDFDOI

Frequent coauthors

• Fei Dai

  16 shared

• Reza Akhavian

  San Diego State University

  16 shared

• Semiha Ergan

  San Diego State University

  16 shared

• Divya Srinivasan

  Imperial College Healthcare NHS Trust

  5 shared

• Alexander Leonessa

  4 shared

• Rohith Karthikeyan

  Texas A&M University

  4 shared

• Ranjana K. Mehta

  University of Wisconsin–Madison

  4 shared

• Qi Zhu

  National Institute of Standards and Technology

  3 shared

Awards & honors

• 2015 Best Paper Award, ASCE Journal of Construction Engineer…
• 2014 Best Paper Award, International Conference on Innovativ…
• 2014 Outstanding Reviewer Award, ASCE Journal of Constructio…