Any occurrences taking place in any space and time are indeed instantaneously generating colossal amounts of data, which are in turn constituting their own “identities” that can later be detected and interpreted from different perspectives, by virtue of different methodologies in data science.
The sheer volume of data generated, counting in quintillion bytes per day, is basically a treasure trove of information, and the ability to strategically collect, navigate and analyze them can subsequently unleash the potential embedded in different processes and behavioral patterns. Identifying growth areas, spotting loopholes and devising solutions are all conducive to the constant improvement in various aspects of our lives.
Data science, essentially the study and utilization of data, is therefore our tool to understand matters from novel perspectives. Having taken center stage across a gamut of modern technologies, data science helps us translate raw data into actionable solutions.
To constantly develop data science, we need to take the traditional approach towards data and statistics to the next level. Here at SENG, we harness data through performing data processing and mining as well as data analytics and diagnostics. Simultaneously, to maximize our utilization of big data, we actively engage in research activities to refine both data-driven and statistical machine learning processes. Our research is also at the leading edge of burgeoning data-centric technologies such as blockchain, cloud computing, Internet of Things (IoT), and wireless networking.
Advanced data science also powers various aspects within the ambit of financial engineering—ranging from fintech, risk management, financial econometrics, prescriptive and predictive analytics, to logistics management. We also aim at fostering intelligent use of data, which is also the prerequisite for achieving breakthroughs in realms such as bioinformatics and healthcare operations.
As useful as data can be, the collection and unlocking of “clues” embedded in data are simultaneously susceptible to threats such as data theft and privacy invasion. Since data should be utilized with utmost prudence, the enhancement of cybersecurity has also been a challenging yet key aspect that our research has been striving to perfect.
Relevant Faculty Members
|Hao CHEN||Kai CHEN|
|Lei CHEN||Qifeng CHEN||Kwang-Ting Tim CHENG|
|Shing Chi CHEUNG|
|Shuai WANG||Wei WANG|
|Raymond Chi Wing WONG||Dekai WU||Qiang YANG|
|Dit Yan YEUNG||Ke YI||Charles Chuan ZHANG|
|Nevin Lianwen ZHANG|
|Xuan QIU||Richard Hau Yue SO|
|Fugee TSUNG||Xin WANG|
|Rachel ZHANG||Shaohui ZHENG|
Relevant Research Infrastructure
- Big Data Institute
- HKUST-NAVER / LINE AI Laboratory
- HKUST-WeBank Joint Lab
- HKUST-Xunlei Joint Laboratory on Blockchain Technology
- Huawei-HKUST Innovation Laboratory
- WeChat-HKUST Joint Lab on Artificial Intelligence Technology (WHAT LAB)