Weihua Sheng

Weihua Sheng is affiliated with Oklahoma State University in the United States. Their research spans multiple areas within computer science and engineering, with a focus on the intersection of robotics, artificial intelligence, and human-computer interaction.

The main fields of study covered by Weihua Sheng include Computer Science and Engineering, with subfields such as Computer Vision and Pattern Recognition, Civil and Structural Engineering, Artificial Intelligence, Control and Systems Engineering, and Social Psychology. This diverse range indicates a multidisciplinary approach bridging technical development and human-centered applications.

Key topics in their work involve Social Robot Interaction and Human-Robot Interaction (HRI), Technology Use by Older Adults, Context-Aware Activity Recognition Systems, Digital Mental Health Interventions, Human Pose and Action Recognition, Multimodal Machine Learning Applications, and Robotic Path Planning Algorithms. These research areas reflect an emphasis on both developing intelligent systems and addressing societal challenges related to aging and health.

Frequent publication venues for Weihua Sheng include IEEE Robotics and Automation Letters, IEEE Transactions on Automation Science and Engineering, Arabian Journal for Science and Engineering, IEEE Transactions on Intelligent Transportation Systems, and Smart Health. These venues highlight a blend of automation, robotics, transportation, and health-related research.

Weihua Sheng has collaborated extensively with several coauthors including Alex Bishop, Zhidong Su, Fei Liang, Ha Manh, and Barbara W. Carlson. These collaborations have contributed to a consistent stream of publications in their research domains.

Recent significant publications by Weihua Sheng include:

• A lightweight encoder-decoder network for automatic pavement crack detection (2023, Computer-Aided Civil and Infrastructure Engineering)
• Clinical Screening Interview Using a Social Robot for Geriatric Care (2020, IEEE Transactions on Automation Science and Engineering)
• SoHAM: A Sound-Based Human Activity Monitoring Framework for Home Service Robots (2021, IEEE Transactions on Automation Science and Engineering)
• Conversation-Based Medication Management System for Older Adults Using a Companion Robot and Cloud (2021, IEEE Robotics and Automation Letters)
• Negative Emotion Management Using a Smart Shirt and a Robot Assistant (2021, IEEE Robotics and Automation Letters)

The research output shows a balance between theoretical advancements in machine learning and practical applications involving robotic systems tailored to support older adults and healthcare contexts. The work on human activity recognition, social robots, and context-aware systems demonstrates an integration of engineering methods with social and psychological considerations.