Yong Wang Turns Visualization Into Insights

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

Rising up in rural Hunan

Wang was born in in a small farming village in southern China. China’s economic system was nonetheless creating, 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 typically 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 attainable 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 schooling.”

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

Expertise was scarce within the village, he says. Computer systems had been nearly nonexistent, and televisions had been thought of valuable, costly family possessions.

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

“My mom was very indignant,” he recollects. “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 comparable 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 regarded 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 programs.

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

He graduated with a bachelor’s diploma in 2011, after which pursued a grasp’s diploma in sample recognition and picture processing from the Huazhong College of Science and Expertise, in Wuhan, China.

In 2014 he took a place as a analysis intern working at a expertise firm 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 conclusion pushed him towards graduate college, he says.

In 2014 he took a place as a analysis intern working a expertise firm 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 conclusion pushed him towards graduate college, he says.

Constructing instruments that assist people work with AI

He 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 affix Singapore Administration College as an assistant professor of computing and data programs. 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.

He and his college students, collaborators have developed a collection of approaches to advocate or robotically generate applicable visualizations, together with infographics.

It permits nontechnical individuals to create visualizations as a substitute of hiring skilled designers.

One other focus of Wang’s analysis is human-AI collaboration. AI programs can analyze knowledge at huge scale, however individuals nonetheless should 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 individuals perceive how the AI system works,” Wang says, “they’ll collaborate with it extra successfully.”

He just lately explored how visualization methods might assist researchers perceive quantum computing, a discipline the place core ideas—comparable to superposition, the place a bit could 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, could be 1, 0, or each. The variations get extra dizzying from there.

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

The significance of IEEE communities

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

Knowledge visualization gives an answer by turning advanced data into pictures, patterns, and diagrams that folks can extra readily perceive.

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

His answer is to make use of massive language fashions and multimodal programs that may generate textual content, pictures, video, and sensor knowledge 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 comparable to drawing on a touchscreen with a finger. It permits nontechnical individuals to generate visualizations as a substitute of hiring skilled designers.

One other focus of his analysis is human-AI collaboration. AI programs can analyze knowledge at huge scale, however individuals nonetheless should 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 individuals perceive how the AI system works,” he says, “they’ll collaborate with it extra successfully.”

He just lately explored how visualization methods might assist researchers perceive quantum computing, a discipline the place core ideas—comparable to superposition, the place a bit could 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, could be 1, 0, or each. The variations get extra dizzying from there.

Visualization instruments might assist scientists monitor quantum programs 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 Pc Society, he says, play a serious function in serving to him rework early-stage graduate college students not sure of which strains of inquiry they’ll pursue into unbiased 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 Vital New Researcher award motivates him to proceed pushing the sector ahead, he says.

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

“That’s the true energy of visualization.”