Yong Wang Transforms Data Visualization Into Actionable Insights

When Yong Wang received one of data visualization’s most prestigious early-career honors recently, it capped a journey that started far from any tech hub. Born in a small farming village in southwestern China to parents with little formal education and almost no electronic devices, Wang is now an IEEE member and assistant professor of computing and data science at Nanyang Technological University in Singapore. He explores how data visualization techniques can help people get more from artificial intelligence tools.

“Visualization helps people understand complex ideas,” Wang explains. “If we design these tools well, they can make advanced technologies accessible to everyone.”

The IEEE Computer Society visualization and graphics technical committee awarded him the 2025 Significant New Researcher Award for his work. The honor underscores his rising influence in human-computer interaction and human-AI collaboration , fields that grow more critical as data generation outpaces human comprehension.

Wang grew up in rural Hunan Province, where life was modest. Most families farmed rice, vegetables, and fruit. His parents worked in agriculture, and his father traveled to cities for factory or construction jobs to supplement the family income, making college possible for Wang.

“I’m very grateful to my parents,” he says. “They never attended university, but they strongly supported my education.”

Technology was scarce. Computers were almost nonexistent, and televisions were precious. One summer, Wang and his brother played so many hours of video games on a simple console connected to the family TV that the screen burned out. “My mother was very angry,” he recalls. “At that time, a TV was a very valuable thing.”

Despite never using a laptop or experimenting with electronics as a child, Wang was captivated by the technologies he saw on TV shows. His parents encouraged practical careers like medicine or civil engineering, but he felt drawn to robotics and computing.

“I didn’t really understand what computer science involved,” he says. “But from what I saw on TV, it looked exciting and advanced.”

He enrolled at Harbin Institute of Technology, known for its engineering programs, and majored in automation , a blend of electrical engineering, robotics, and control systems. A university robotics competition proved defining: Wang and his teammates designed a robot that could autonomously navigate obstacles. They placed second, and Wang began seeing engineering as creative and collaborative.

After earning his bachelor’s degree in 2011, he worked briefly as an assistant at the Research Institute of Intelligent Control and Systems at Harbin. In 2014, he became a research intern at Da Jiang Innovation in Shenzhen, China. That experience clarified his future.

“I realized I didn’t enjoy doing repetitive work or simply following instructions,” he says. “I wanted to explore ideas that interested me, and I wanted to conduct research.” That realization pushed him toward graduate school.

Wang earned a master’s degree in pattern recognition and image processing from Huazhong University of Science and Technology in 2016, then a Ph. D. in computer science from Hong Kong University of Science and Technology in 2018. After a postdoctoral stint there, he moved to Singapore in 2020 to join Singapore Management University as an assistant professor. He transferred to Nanyang Technological University in 2024.

His research tackles a challenge facing nearly every business: making sense of massive data volumes. “We live in an era of information explosions,” Wang says. “Huge amounts of data are generated, and it’s difficult for people to interpret all of it to make better business decisions.”

Data visualization turns complex information into images, patterns, and diagrams people can more readily understand. But many visualizations still require manual design by experts, creating a bottleneck. Wang’s solution uses large language models and multimodal systems that generate text, images, video, and sensor data simultaneously, automating parts of the process.

One system his research group developed lets users design complex infographics through natural-language instructions combined with simple interactions like drawing on a touchscreen. It enables nontechnical people to generate visualizations without hiring professional designers.

Another focus is human-AI collaboration. AI systems can analyze data at enormous scale, but people must remain the final decision-makers. Visualization makes the process an AI system uses to reach a result more transparent and understandable, bridging the gap between human intention and complex calculations.

“If people understand how the AI system works,” Wang says, “they can collaborate with it more effectively.”

He recently explored how visualization could help researchers understand quantum computing, a field full of abstract concepts like superposition, where a bit can be in multiple states simultaneously. Visualization tools could help scientists monitor quantum systems and interpret quantum machine-learning models.

Teaching and mentoring remain among the most meaningful parts of Wang’s career. Professional communities like the IEEE Computer Society help him transform early-stage graduate students into independent researchers with solid technical focus. Through conferences, publications, and technical committees, IEEE connects Wang with peers in visualization, AI, and human-computer interaction, helping him share ideas, collaborate, and stay current.

Receiving the Significant New Researcher Award motivates him to keep pushing the field forward. Looking back, the distance between his rural Hunan village and an international research career still feels remarkable. But the journey reflects something larger about his chosen field: “If we build tools that help people understand information, then more people can participate in science and innovation. That’s the real power of visualization.”