I am currently involved in an interdisciplinary research project, MOASIS (Mobility, Activity and Social Interaction Study) as a postdoctoral researcher at the University Research Priority Program 'Dynamics of Healthy Aging' and the Department of Geography, University of Zurich. 

My current research projects include but not limited to:

• Theories and Statistical Methodology Development for Measuring Spatial and Temporal Heterogeneity and Bursty Patterns of Geographic Events;
• Human Mobility Pattern Analysis using Multi-Sensor Datasets including GPS, Accelerometry, Audio data, and Momentary Survey Data;
• Automatic Place Detection and Semantic Trajectory Analysis using Machine Learning;
• Longitudinal and Spatial Analysis of Older Adults' Mental Health and their Socio-Environmental Status.

I'm corrently co-organizing the Special Issue on Mobility, Health, and Place. 

1. Tian, T. & Kim, E.-K. (2021). Multi-Year Spatial Variability of the Impact of Sociodemographic, Behavioural, and Health Factors on Depression of Older Adults, Proceedings of the International Cartographic Association, 4 (106). Web page
2. Kim, E.-K., Fillekes, M. P., Röcke, C., Weibel, R. (2021). Dimensions of GPS-derived Daily Mobility in Older Adults, GIScience 2021 Workshop on Advancing Movement Data Science (AMD’21) online.
3. Fillekes, M. P., Kim, E.-K., Trumpf, R., Zijlstra, W., Giannouli, E., & Weibel, R. (2019). Assessing Older Adults’ Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators. Sensors 19(20), 4551. DOI
4. Fillekes, M. P., Giannouli, E., Kim, E.-K., Zijlstra, W., & Weibel, R. (2019). Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research. International Journal of Health Geographics, 18(1), 17. DOI
5. Shook, E., Bowlick, F., Kemp, K., Ahlqvist, O., Carbajales, P., DiBiase, D., Kim, E.-K., Lathrop, S., Ricker, B., Rickles, P., Rush, J., Swift, J., & Wang, S. (2019). Cyber Literacy for GIScience: Toward Formalizing Geospatial Computing Education. The Professional Geographer, 71(2), 221-238. DOI
6. Kim, E.-K. (2018). Stay-Move Tree for Summarizing Spatiotemporal Trajectories (Short Paper). Raubal, M., Wang, S., Guo, M., Jonietz, D., & Kiefer, P. (Eds.) Proceedings of Spatial Big Data and Machine Learning in GIScience, Workshop at GIScience 2018, Melbourne, Australia, August 2018. DOI
7. Perez, L., Kim, E.-K., & Sengupta, R. (Eds.) (2018). Agent-Based Models and Complexity Science in the Age of Geospatial Big Data. In Balram, S. & Dragicevic, S. (Series Eds.), ‘Advances in Geographic Information Science’ Series, Springer International Publishing. DOI
8. Kim, E.-K. & Jo, H.-H. (2016). Measuring Burstiness for Finite Event Sequences. Physical Review E, 94(3): 032311. DOI

Completed Project

Severin Thürig (2020.07 ~ 2021.09): Master Thesis on "Analysis of the Mobility of Healthy Older Adults: Trajectory Sequence Analysis and Detecting Patterns"

Oliver Eberli (2020.07 ~ 2021.09): Master Thesis on "Mobility, Activity, and Social Interactions in the Daily Lives of Healthy Older Adults: Relation of Mobility and Environments on various Health Aspects"

Yuman He (2020.04 ~ 2021.04): Master Thesis on "Comparison of Feature Engineering Methods and Classifiers for Recognizing Physical Activity Types in Older Adults Using Real-Life IMU and GPS Data"

Elena Ebert (2019.10 ~ 2020.04): Master Thesis on "Comparison and Optimization of Stop-Move Detection Algorithms for GPS Data of Older Adults"

Tian Tian (2018.10 ~ 2019.09): Master Thesis on "Longitudinal Spatial Analysis of the Impact of Sociodemographic Status on Mental and Physical Well-being of the Elderly"

Spring 2021 & Spring 2019

GEO 881: Advanced Spatial Analysis II 

• A course is served for master and doctoral students.
• Lectures and tutorials were redesigned revolving around spatial prediction and spatial machine learning.

Upcoming events

• The 19th International Medical Geography Symposium (IMGS) Special Sessions on 'Mobility, Health, and Place' (MoHeaP) in June 2022 in Edinburgh, UK.

Past events since 2019

• Applied Machine Learning Days (AMLD) 2021, 'AI & Cities' track on December 2, 2021 in Lausanne, Switzerland.
• MoHeaP 2021 Workshop on Mobility, Health, and Place on June 08-23, 2021, 100% Online.
• Applied Machine Learning Days (AMLD) 2020, 'AI & Cities' track on January 25-29, 2020 in Lausanne, Switzerland.
• ML4SEP 2019: The Workshop on Applied Machine Learning for Social & Environmental Problems on UZH Irchel on October 3-4, 2019. 
• ECTQG 2019 Special Sessions, Mobilities and Health: Advances in theoretical and quantitative methods on September 5-9, 2019 in Mondorf-Les-Bains, Luxembourg.
• Peer Mentoring Group "Applied Machine Learning for Social & Environmental Problems (ML4SEP)" in January, 2019 - December, 2020.