Yong Wang Turns Visualization Into Insights

“Visualization helps folks perceive advanced concepts,” Wang says. “If we design these instruments properly, they will 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 changing into extra necessary because the world generates extra knowledge than people can simply interpret.

Rising up in rural Hunan

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

Wang’s mother and father labored in agriculture too, and his father usually traveled to cities to earn cash working in a manufacturing unit or on development jobs. The additional revenue helped help the household and made it doable for Wang to attend faculty.

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

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

Know-how 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 snicker: Throughout a summer time trip, he and his brother spent so many hours taking part in video games on a easy console linked to the household’s television that the TV display screen finally burned out.

“My mom was very indignant,” he recollects. “At the moment, a TV was a really helpful factor.”

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

Discovering robotics and engineering

His mother and father inspired a sensible profession corresponding to drugs 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 seemed 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 components 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 staff 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 noticed 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 knowledge methods. He moved over to Nanyang Technological University as an assistant professor in 2024.

His analysis focuses on a problem dealing with almost each enterprise: the right way to make sense of the big quantities of information being generated.

“We reside 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 choices.”

Information visualization affords an answer by turning advanced data into photographs, patterns, and diagrams that individuals can extra readily perceive.

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

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

One system developed by his analysis group lets customers design advanced infographics via natural-language directions mixed with easy interactions corresponding 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 knowledge at monumental scale, however folks nonetheless must 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 succeed in a end result extra clear and comprehensible.

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

He lately explored how visualization strategies might assist researchers perceive quantum computing, a subject the place core ideas—corresponding to superposition, the place a bit might be in a couple of 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 significant function in serving to him remodel early-stage graduate college students uncertain of which strains of inquiry they are going to pursue into impartial researchers with a strong technical focus. Via 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 neighborhood.

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

Wanting again, he says, the space 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 data, then extra folks can take part in science and innovation.

“That’s the actual energy of visualization.”