Yong Wang Turns Visualization Into Insights

“Visualization helps folks perceive advanced concepts,” Wang says. “If we design these instruments properly, they’ll make superior applied sciences accessible to everybody.”

For his work within the subject, the IEEE Computer Society visualization and graphics technical committee offered him with its 2025 Significant New Researcher Award. The popularity highlights his rising affect in fields together with human-computer interaction and human-AI collaboration—areas turning into extra vital because the world generates extra information than people can simply interpret.

Rising up in rural Hunan

Wang was born in southwestern Hunan Province. China’s financial system was nonetheless growing, and life in his village was modest. Most households in Hunan grew rice, greens, and fruit to assist themselves.

Wang’s mother and father labored in agriculture too, and his father typically traveled to cities to earn cash working in a manufacturing unit or on development jobs. The additional earnings helped assist the household and made it potential for Wang to attend school.

“I’m very grateful to my mother and father,” Wang says. “They by no means attended college, however they strongly supported my schooling.”

“If we construct instruments that assist folks perceive info, then extra folks can take part in science and innovation. That’s the actual energy of visualization.”

Expertise was scarce within the village, he says. Computer systems had been nearly nonexistent, and televisions had been thought-about treasured, costly household possessions.

One childhood reminiscence nonetheless makes him snigger: Throughout a summer time trip, he and his brother spent so many hours taking part in video games on a easy console related to the household’s television that the TV display finally burned out.

“My mom was very offended,” he remembers. “At the moment, a TV was a really beneficial factor.”

He says that regardless of by no means having used a laptop computer or experimenting with digital tools, he was fascinated by the applied sciences he noticed on TV exhibits.

Discovering robotics and engineering

His mother and father inspired a sensible profession similar to medication or civil engineering, however he felt drawn to robotics and computing, he says.

“I didn’t actually perceive what pc science concerned,” he says. “However from what I noticed on TV, it appeared thrilling and superior.”

He enrolled at Harbin Institute of Technology, in northeastern China. The esteemed college is thought for its engineering applications. His main—automation— mixed parts of electrical engineering, robotics, and control systems.

One of many defining experiences of his undergraduate years, he says, was a college robotics competitors. Wang and his teammates designed a robotic able to autonomously navigating round obstacles.

The design was easy in contrast with skilled methods, he acknowledges. However, he says, the expertise was exhilarating. His workforce positioned second, and Wang started to see engineering as each artistic and collaborative.

He graduated with a bachelor’s diploma in 2011 and briefly labored as an assistant on the Research Institute of Intelligent Control and Systems at Harbin.

In 2014 he took a place as a analysis intern working at Da Jiang Innovation in Shenzhen, China.

That have helped him make clear his future, he says: “I spotted I didn’t take pleasure in doing repetitive work or just following directions. I wished to discover concepts that me, and I wished to conduct analysis.” The belief pushed him towards graduate faculty, he says.

Constructing instruments that assist people work with AI

Wang acquired a grasp’s diploma in pattern recognition and image processing from the Huazhong University of Science and Technology, in Wuhan, China, in 2016.

He then enrolled within the pc science Ph.D. program on the Hong Kong University of Science and Technology and earned the diploma in 2018. He remained there as a postdoctoral researcher till 2020, when he moved to Singapore to affix Singapore Management University as an assistant professor of computing and data methods. He moved over to Nanyang Technological University as an assistant professor in 2024.

His analysis focuses on a problem going through practically each enterprise: the best way to make sense of the big quantities of information being generated.

“We stay in an period of knowledge explosions,” Wang says. “Enormous quantities of information are generated, and it’s troublesome for folks to interpret all of it to make higher enterprise selections.”

Information visualization provides an answer by turning advanced info into photos, patterns, and diagrams that individuals can extra readily perceive.

However many visualizations nonetheless should be designed manually by consultants, Wang notes. It’s a time-consuming course of that creates a bottleneck, he says.

His resolution is to make use of large language models and multimodal methods that may generate textual content, photos, video, and sensor information concurrently and automate components of the method.

One system developed by his analysis group lets customers design advanced infographics by natural-language directions mixed with easy interactions similar to drawing on a touchscreen with a finger. It permits nontechnical folks to generate visualizations as a substitute of hiring skilled designers.

One other focus of Wang’s analysis is human-AI collaboration. AI methods can analyze information at monumental scale, however folks nonetheless have to be the ultimate decision-makers, he says.

Visualization helps bridge the hole between human intention and AI’s advanced calculations by making the method an AI system makes use of to achieve a outcome extra clear and comprehensible.

“If folks perceive how the AI system works,” Wang says, “they’ll collaborate with it extra successfully.”

He not too long ago explored how visualization methods might assist researchers perceive quantum computing, a subject the place core ideas—similar to superposition, the place a bit might be in multiple state at a time—are summary. In classical computing, the bit state is binary: It’s both 1 or 0. A quantum bit, or qubit, might be 1, 0, or each. The variations get extra dizzying from there.

Visualization instruments might assist scientists monitor quantum methods and interpret quantum machine-learning fashions, he says.

The significance of IEEE communities

Instructing and mentoring college students stay among the many most significant components of Wang’s profession, he says.

Skilled communities such because the IEEE Computer Society, he says, play a serious function in serving to him remodel early-stage graduate college students not sure of which traces of inquiry they may pursue into impartial researchers with a strong technical focus. By conferences, publications, and technical committees, IEEE connects Wang with different researchers working in visualization, AI, and human-computer interactions, he says.

These connections have helped him share concepts, collaborate, and keep updated on improvements within the analysis group.

Receiving the Important New Researcher award motivates him to proceed pushing the sphere ahead, he says.

Wanting again, he says, the gap between his rural village in Hunan and a world analysis profession nonetheless feels exceptional. However, he says, the journey displays one thing bigger about his chosen subject: “If we construct instruments that assist folks perceive info, then extra folks can take part in science and innovation.

“That’s the actual energy of visualization.”