Hongan Wang

About

Hongan Wang’s research lies at the intersection of human-computer interaction, computer vision, and assistive technology, with a focus on gesture recognition, hand detection, and robotic systems. Wang is best known for developing STA-GCN, a two-stream graph convolutional network with spatial–temporal attention for hand gesture recognition, which has garnered 59 citations and represents a significant advance in understanding dynamic hand movements. Earlier work includes the design and implementation of a biomimetic robotic fish, showcasing mechanical innovation in robotics. Wang also contributed to joint hand detection and rotation estimation using convolutional neural networks, addressing challenges in uncontrolled environments for applications in robotics and human-computer interaction. More recently, Wang led the development of DailyConnect, a mobile application that pilots situation-based emotional understanding interventions for children with autism spectrum disorder in naturalistic home settings, demonstrating a commitment to socially impactful technology. With a portfolio spanning from foundational vision techniques to applied assistive tools, Wang’s work continues to influence both technical and human-centered domains.

Research Focus

Key Achievements

Top Papers

1. 1
   STA-GCN: two-stream graph convolutional network with spatial–temporal attention for hand gesture recognition

   59 citations · 2020
2. 2
   Design and Implementation of a Biomimetic Robotic Fish

   6 citations · 2009
3. 3
   Joint Hand Detection and Rotation Estimation by Using CNN

   4 citations · 2016
4. 4
   DailyConnect: Piloting Interventions of Situation-Based Emotional Understanding in Naturalistic Home Settings for Children with Autism Spectrum Disorder

   2 citations · 2023

Key Collaborators

Contact & Links