In October we welcomed four new PhD students to HASP, and we’ve been meeting one each week to learn more about them and their project. This week it’s Yelu He whose PhD will focus on generating synthetic mobility trajectories for privacy-preserving data sharing.
The growth in the availability of fine-grained mobility data has spurred high-impact research findings into the nature of human mobility. There remains significant potential for enhanced understanding of mobility behaviour to help improve the reliability and sustainability of urban transportation systems.
Despite major safeguards in place around the storage and use of fine-grained mobility data, there remain concerns about the risk to individual privacy, and questions about the continued willingness of the public to permit data for use in research.
Yelu’s PhD project will seek to advance the state-of-the-art in synthetic trajectory production through the development of methods that better capture spatial, temporal, and contextual heterogeneity.
She will seek to encode features such as travel mode choice, gender, age, and co-presence in our synthetic models. Furthermore, she will assess how we can account for, or integrate, non-recurrent events, such as travel disruptions, holidays, and weather, in realistically replicating mobility trajectories.
Yelu, tell us a bit about yourself and your background
I’m a first-year PhD student at the Institute for Spatial Data Science in the School of Geography at the University of Leeds. My current research focuses on generating synthetic mobility trajectories for privacy-preserving data sharing. With a background in Resources and Environmental Science, Statistics, and Geographical Information Science and Systems, I gradually developed an interest in urban mobility and geospatial big data.
How did you become interested in data science?
Back then as an undergraduate student, I was introduced to big data for the first time during a GIS course. We read several articles using mobile phone and taxi trajectory data to estimate urban crowd flux or to extract urban functional regions, which sparked my curiosity about human mobility pattern and inspired me about the potential of geospatial big data.
What attracted you to the HASP program?
During one course in my master’s program, my group partner and I collected raw data with GPS trackers and designed a model to identify travel modes based on our trajectory data. That was the first time I had to face the issue of omitting individual information in trajectory data sharing. I began to wonder how important privacy preservation of geospatial data is, especially for mobility trajectory data. Furthermore, with the growing availability of mobility data, I am interested in how we can address concerns about exposing individual privacy when producing and sharing trajectory data. HASP’s objectives of providing high-quality smart data, improving data sharing, and making smart data accessible align with my interest and curiosity.
What are you looking forward to about the PhD?
I am looking forward to exploring the field of synthetic trajectory data generation, as well as deepening my understanding of mobility issues and how data can contribute to improving the health and sustainability of places. I also hope to strengthen my technical skills in geospatial data analysis, big data processing and advanced machine learning algorithms. In addition, I am eager for the opportunity to communicate and collaborate with people from different fields, and to learn more about creating data products. Finally, I wish to develop my abilities in stress and time management.
Do you have plans for the future?
As a new PhD student, I am currently exploring different possibilities. I hope to continue working with geospatial big data and I am interested in roles that combine academic research with practical application. But first and foremost, I plan to focus on learning as much as I can and surviving the PhD journey.
What does a healthy and sustainable place mean to you?
To me, a healthy place is one where people can enjoy interacting with the environment and with each other, both physically and mentally, without concerns about safety, privacy, accessibility or equality. And a sustainable place is one of which services, infrastructure and technology are sustainable, in terms of aspects such as energy, waste, pollution as well as resilience.
