Last update: March 2020 (Please refer to CV for more details)

We are now living in a mobile information era, which is fundamentally changing science and society. My research tackles research questions that arise in the mobile information society from a geographic information science (GIScience) perspective. Specifically, we are mainly interested in

  • the design of human-centered Location Based Services (LBS),
  • the analysis of location based big data (Computational Mobility and Activity Analytics),
  • and the behavioral and social implications of LBS.
Due to the interdisciplinary nature of the research field, we often employ both empirical (e.g., lab/field experiments, and focus groups) and computational methods (e.g., data modelling, data analysis, simulation and prediction).

1. Design of Human-Centered LBS

We are interested in studying how human-centred LBS (typically mobile applications on smartphones or wearable devices) can be developed to better support people’s daily decision-making and activities in space (e.g., navigation/wayfinding, city exploration, mobility, and social interaction).


1.1) Pedestrian Navigation (outdoor/indoor)
We mainly focus on route planning (computing the most appropriate route from A to B) and route communication (conveying route information/directions effectively, e.g., with mobile maps, Augmented Reality, Verbal Instructions).
Main publications:

1.2) Context-awareness and Context-aware recommendation
Context-awareness plays a key role in LBS. We mainly focus on how to identify relevant context parameters, and how to provide context-awareness in LBS, especiall in mobile guides.
Main publications:

2. Computational Mobility and Activitiy Analytics
We are interested in studying the use of LBS and location/activity-sensing technologies to study and model people’s perception of, experiences and behaviour in space (e.g., emotions towards environments, mobility within a city). We are especially interested in how people’s spatial behaviors are influenced by different context (e.g., weather, time, with whom).
The aim is to create a “subjective” layer aggregating subjective layerpeople’s subjective experiences in space, and overlay this layer on top of existing “objective” geospatial data. Mobile crowdsourcing and mining geotagged social media data are very promising for this purpose.  The “subjective” layers can bring benefits not only to LBS/GIScience, but also to other disciplines (e.g., computer science, psychology, urban planning).
Main publications:

3. Behavioral and Social Implications of LBS

We are interested in studying the impact of LBS on both individuals and society, for example, how do LBS influence people’s spatial ability, and the way people interact with each other and their behaviours in space?
subjective layer
My recent work on this aspect focuses on the following questions: a) How do LBS (e.g., navigation systems) influence people’s spatial knowledge acquisition, spatial awareness and spatial ability? Why it happens? b)How can we design LBS that facilitate people’s activities and decision-making without harming their spatial abilities?
Main publications: