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Lei Chen - IEEE Xplore Author Profile

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Author details

Lei Chen

Publications

39

Citations

1,037

Publications by Year

20162024

Co-Authors:

Md Baitul Al-SadiMin Kyung AnMd Zakirul Alam BhuiyanBiodoumoye George BokoloRobert Brinson

Show All Co-Authors (73)

Lei Chen

Affiliation

Department of Information Technology

Georgia Southern University

Statesboro, GA, USA

Publication Topics

Machine Learning,
Deep Learning,
Long Short-term Memory,
Decision Tree,
F1 Score,
Learning Algorithms,
Recurrent Neural Network,
Short-term Memory,
Confusion Matrix,
Convolutional Neural Network,
Data Frame,
Data Mining

Biography

Lei Chen (M’05–SM’19) received the Ph.D. degree in computer science and software engineering from Auburn University, Auburn, AL, USA, in 2007.,He is currently a tenured Associate Professor and the Graduate Program Director with the Department of Information Technology, Georgia Southern University, Georgia, USA. His research interests include network, information, cloud, and big data security, digital forensics, mobile, handheld, and wireless security.(Based on document published on 17 October 2019).

Publications

39

Citations

1,037

Publications by Year

20162024

Co-Authors:

Md Baitul Al-Sadi
Min Kyung An
Md Zakirul Alam Bhuiyan
Biodoumoye George Bokolo
Robert Brinson

Show All Co-Authors (73)

Author's Published Works

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Showing 1-4 of 4 results

Conferences (2)

Journals (2)

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Peide Huang(4)
Ding Zhao(3)
Mengdi Xu(2)
Yiwen Dong(1)
William Jongwon Han(1)
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA(3)
Columbia University(1)
Tongji University(1)
Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA(1)
Motion and Gait Analysis Lab, Lucile Packard Children's Hospital, Menlo Park, CA, USA(1)
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)(1)
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(1)
IEEE Journal of Biomedical and Health Informatics(1)
IEEE Robotics and Automation Letters(1)
IEEE(4)
Media(1)
Kyoto, Japan(1)
Macau, China(1)
Ablation(1)
Adaptive Sampling(1)
Autonomous Vehicles(1)
Baseline Methods(1)
Beginning Of Episode(1)

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Results

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications

Xilun Zhang;Shiqi Liu;Peide Huang;William Jongwon Han;Yiqi Lyu;Mengdi Xu;Ding Zhao

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

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Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies between simulated and real-world dynamics. Traditional methods like Domain Randomization often fail to capture fine-grained dynamics, limiting their effectiveness for precise control tasks. In this work, we propose a novel approach that dynamically adjusts simulation environment parameters online using in-con...Show More

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications

Xilun Zhang;Shiqi Liu;Peide Huang;William Jongwon Han;Yiqi Lyu;Mengdi Xu;Ding Zhao

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning

Yiwen Dong;Sung Eun Kim;Kornél Schadl;Peide Huang;Wenhao Ding;Jessica Rose;Hae Young Noh

IEEE Journal of Biomedical and Health Informatics

Year: 2024 | Volume: 28, Issue: 12 | Journal Article |

Cited by: Papers (2)

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Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromusculoskeletal disorders such as Parkinson's and stroke. Traditional assessments in gait clinics are infrequent and pose barriers, particularly for disadvantaged populations. Previous efforts have explored sensor-based approaches for in-home gait assessments, yet they face limitations such as visual ...Show More

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning

Yiwen Dong;Sung Eun Kim;Kornél Schadl;Peide Huang;Wenhao Ding;Jessica Rose;Hae Young Noh

IEEE Journal of Biomedical and Health Informatics

Year: 2024 | Volume: 28, Issue: 12 | Journal Article |

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling

Mengdi Xu;Peide Huang;Fengpei Li;Jiacheng Zhu;Xuewei Qi;Kentaro Oguchi;Zhiyuan Huang;Henry Lam;Ding Zhao

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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Evaluating rare but high-stakes events is one of the main challenges in obtaining reliable reinforcement learning policies, especially in large or infinite state/action spaces where limited scalability dictates a prohibitively large number of testing iterations. On the other hand, a biased or inaccurate policy evaluation in a safety-critical system could potentially cause unexpected catastrophic f...Show More

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling

Mengdi Xu;Peide Huang;Fengpei Li;Jiacheng Zhu;Xuewei Qi;Kentaro Oguchi;Zhiyuan Huang;Henry Lam;Ding Zhao

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Year: 2022 | Conference Paper |

Coalitional Fairness of Autonomous Vehicles at a T-Intersection

Diana Gomez;Haohong Lin;Peide Huang;Corey Harper;Ding Zhao

2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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Currently, autonomous vehicles (AVs) generally make decisions in their self-interest instead of the social good. Although humans already commit such actions, a decision made by an AV is directly connected to a company allowing potential unfair actions to occur on a large scale with far worse conse-quences. To explore fairness, this paper analyzes the efficiency and group fairness of AVs' interacti...Show More

Coalitional Fairness of Autonomous Vehicles at a T-Intersection

Diana Gomez;Haohong Lin;Peide Huang;Corey Harper;Ding Zhao

2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2022 | Conference Paper |

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