RMIT University
April 2021 - present
Ph.D. Candidate in School of Computing Technologies, Big Data & Data Management Group
Supervisors: Prof. Zhifeng Bao and Prof. Shane Culpepper
I am currently pursuing the Ph.D. degree at Computing technologies from RMIT University under the surpervison of Prof. Zhifeng Bao and Prof. Shane Culpepper. My research interests include database management, data mining, urban data analytics, and spatial computing.
Ph.D. Candidate in School of Computing Technologies, Big Data & Data Management Group
Supervisors: Prof. Zhifeng Bao and Prof. Shane Culpepper
Master in School of Computer Science
Supervisors: Prof. Lei Duan
GPA: 84.5/100
Bachelor in School of Computer Science, first class honours
GPA: 91.0/100
Intelligent transportation system aims to provide innovative services related to different transportation modes and trajectory planning, which enable riders to have safe, convenient and economic friendly trips. Among a lot of transportation strategies, we aim to study a promising service: ridesharing, which can encourage users with similar itineraries and time schedules to share their trips. Such service can save money, reduce traffic congestion and increase car seat utilization, which can bring win-win benefit among drivers and riders. In our research, we aim to study how to find a bilateral matching between a set of drivers and riders under a series of spatial-temporal constraints dynamicly.
- Collect literature about outlying aspect mining for multi-source temporal data to write a review.
- Discover and visualize customer focus sets between customer reviews of items. Such customer focus sets can be used for online shopping decision support.
- Propose an effective algorithm to discover shared properties of items from online reviews. It measures the item similarity from the user perspective to recommend interesting items for users.
- Study the problem of detecting changed user behaviors from activity data. It discovers the alienation mechanism of user behaviors, which helps to monitor special users like patients with mental illness.
- Propose an effective algorithm to mine outlying sequence patterns for sequence data. It finds the hidden differences among sequence data, which plays an important role in many fields like disease detection.
- Serve as a back-end developer. The specific work is to build the communication between the back-end and the front-end for the query feedback.
- Use data mining techniques to analyze biomedical material data, such as applying frequent pattern mining methods to find some common features of osteoinductive materials.
- Construct a biomedical material knowledge graph from biomedical material literature by using natural language processing techniques.
Sichuan University, China
JAVA (proficient), Python (familiar), C/C++ (familiar), Matlab (basic)
Mandarin Chinese (native), English (fluent)