How a Young Data Science Researcher Sees our Connected World

Dr. Xin Huang, Assistant Professor at the Department of Computer Science in HKBU, the winner of the President’s Award for Outstanding Performance in Young Researcher 2020-21, is an expert in graph data management. He develops computational algorithms to discover hidden patterns in our highly connected society. His hard works mark his path to success, with a monograph, two co-edited books, and more than 40 papers published in top-tier academic venues, being cited over a thousand times. He received renowned awards on research, including Best Paper Nomination (ACM CIKM, 2020), Early Career Award (RGC, 2020), among others. He also has a big goal of changing the society with his knowledge and expertise.

 

Ways towards a Data Management Expert

As an outstanding researcher, he conducts high-quality research which inspires people surrounding him. “I always tell my students that a huge tree grows from a tiny seed; a nine-storey high terrace comes from baskets of soil piled.” It involves the meaning of being down to earth and working step by step. This motivates him to pay attribution and attention to every detail, taking him from a university student to an outstanding researcher and Assistant Professor at the Department of Computer Science in HKBU.

Dr. Huang has been recognized as a rising star in the field of data management. Behind the glow, his road to success is neither smooth nor plain. One of his research papers on attributed community detection was only approved after being rejected quadruple within two years. Dedication and perseverance last his spirit to address all the potential weaknesses spotted.

 

Joy behind Creating New Knowledge

Despite the obstacles, Dr. Huang still finds: “Happiness comes from research.” He emphasizes that academic research is a connection to the real world. “Utilizing my technical knowledge, I am excited to be able to solve real problems effectively and efficiently.” He is committed to conducting high-quality and impactful research, fostering translational potential and value to institutions, industry, and the community.

Publishing a research paper in his field is by no means easy and could take one to two years, or even longer. But this fast-moving environment embraces Dr. Huang’s interest and ambition to maintain his momentum to create brand-new theories. “I am excited to create new knowledge and to share that with others.”

“To accomplish it, I have to be sensitive to current happenings while foreseeing the potential problems in the future.” Arguably, it is not enough. In the competitive environment, he has to sort the problem out faster than other experts in the same research area. “As others may have similar ideas and submit their work earlier, I need to think quickly and work faster,” he says.

 

Discovering Hidden Patterns behind Social Networks

Each social media user is directly or indirectly “connected’’ in the digital world; they link publicly and privately. How can we dig out the hidden relationship from the digitally connected world? Having a huge curiosity in discovering hidden relationships from the linkage of the social network, Dr. Huang develops highly efficiently algorithms to discover the secrets behind social networks through big data management and community search techniques.

 

In a public relationship, social media users connect each other with different identities, such as friends, group members, and followers (shown in Figure 1). Their relations are revealed when they have similar activities. These bonds help social media sharing contents and advertisements in common. What if the interactions cannot be seen? The private relationship can never be found!

 

Nevertheless, research from Dr. Huang pushes the private bonds to flow on the surface. “Computers label each user by its daily activities,” Dr. Huang said. For instance, one can use “hiking” or “painting” to represent each user (shown as Figure 2) through their activities. Users having consistent keywords means staying connected.

“After linking the users, we can see they are related to each other," Dr. Huang concludes. With the same labels on similar users, the private relationship appears and social network which is interconnected flows out. The private relationship is not intimidating anymore.

 

Research Collaboration with Technology Giant

Dr. Huang’s recent project takes his career to the next level, as he partnered with Baidu researchers on the finding of interdisciplinary talented groups in professional labeled networks. The research findings will be presented at the 47th International Conference on Very Large Data Base (VLDB 2021), a premier annual international forum in data management and database. The developed algorithms can be utilized in many areas, including social media marketing and commercial recommendation. People with similar interests can be linked. Businesses can identify their potential clients. Social media can push similar information to new targets. “It is likely to maximize and broadcast the information on a particular application.”

Dr. Huang’s advanced research pushes data science industry and social media a big step forward. As an outstanding young researcher, Dr. Huang foresees unlimited opportunities in the future digital world.

“New answers are in the field of community discovery,” Dr. Huang highlights. His knowledge, ambition, and desire are his keys to the new digital world.