Yong Wang Turns Visualization Into Insights

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

For his work within the discipline, the IEEE Pc Society visualization and graphics technical committee introduced him with its 2025 Vital New Researcher Award. The popularity highlights his rising affect in fields together with human-computer interplay and human-AI collaboration—areas turning into extra vital 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 facility or on building 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 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 have been nearly nonexistent, and televisions have been thought-about valuable, costly family possessions.

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

“My mom was very indignant,” he remembers. “At the moment, a TV was a really worthwhile 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 reveals.

Discovering robotics and engineering

His mother and father inspired a sensible profession equivalent 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 appeared thrilling and superior.”

He enrolled at Harbin Institute of Expertise, in northeastern China. The esteemed college is thought for its engineering applications. His main—automation— mixed components of electrical engineering, robotics, and management techniques.

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 techniques, he acknowledges. However, he says, the expertise was exhilarating. His workforce positioned second, and Wang started to see engineering as each inventive and collaborative.

He graduated with a bachelor’s diploma in 2011 and briefly labored as an assistant on the Analysis Institute of Clever Management and Programs 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 get pleasure from 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 sample recognition and picture processing from the Huazhong College of Science and Expertise, in Wuhan, China, in 2016.

He then enrolled within the pc science Ph.D. program on the Hong Kong College of Science and Expertise and earned the diploma in 2018. He remained there as a postdoctoral researcher till 2020, when he moved to Singapore to hitch Singapore Administration College as an assistant professor of computing and knowledge techniques. He moved over to Nanyang Technological College as an assistant professor in 2024.

His analysis focuses on a problem dealing with practically each enterprise: how you can make sense of the large quantities of knowledge being generated.

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

Knowledge visualization presents an answer by turning complicated info into pictures, patterns, and diagrams that folks 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 resolution is to make use of massive language fashions and multimodal techniques that may generate textual content, pictures, video, and sensor knowledge concurrently and automate elements of the method.

One system developed by his analysis group lets customers design complicated infographics by natural-language directions mixed with easy interactions equivalent 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 techniques can analyze knowledge at huge scale, however folks nonetheless have to be the ultimate decision-makers, he says.

Visualization helps bridge the hole between human intention and AI’s complicated 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 may assist researchers perceive quantum computing, a discipline the place core ideas—equivalent 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 may assist scientists monitor quantum techniques and interpret quantum machine-learning fashions, he says.

The significance of IEEE communities

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

Skilled communities such because the IEEE Pc Society, he says, play a significant function in serving to him rework early-stage graduate college students uncertain of which strains of inquiry they are going to pursue into impartial researchers with a strong technical focus. By way of 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 Vital 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 global analysis profession nonetheless feels exceptional. However, he says, the journey displays one thing bigger about his chosen discipline: “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.”