Research publications

1. Li, V.O.K., Han, Y., Lam, J.C.K., Zhu, Y., & Bacon-Shone, J. (2018). Air pollution and environmental injustice: Are the socially deprived exposed to more PM 2.5 pollution in Hong Kong?. Environmental Science & Policy, 80, 53-61. (PDF)
2. Sun, C., Li, V.O.K., & Lam, J.C.K. (2018, June). Optimal Citizen-Centric Sensor Placement for Citywide Environmental Monitoring-A Submodular Approach. In 2018 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops) (pp. 1-4). IEEE. (PDF)
3. Sun, C., Yu, Y., Li, V.O.K., & Lam, J.C.K. (2019). Multi-Type Sensor Placements in Gaussian Spatial Fields for Environmental Monitoring. Sensors, 19(1), 189. (PDF)
4. Guo, P., Li, V.O.K., and Lam, J.C.K., “Smart demand response in China: Challenges and drivers,” Elsevier Energy Policy, Vol. 107, Aug 2017, pp. 1 - 10.
5. Zhu, J.Y., Sun, S.C., and Li, V.O.K. “An extended spatio-temporal Granger Causality Model for air quality estimation with heterogeneous urban big data,” accepted for publication, IEEE Trans. on Big Data.
6. Lam, A.Y.S., Leung, K.C., and Li, V.O.K., “Vehicular energy network,” accepted for publication, IEEE Trans. on Transportation Electrification.
7. Guo, T., Guo, B., Ouyang, Y., Yu, Z., Lam, J.C.K., Li, V.O.K., “CrowdTravel: Scenic spot profiling by using heterogeneous crowdsourced data,” accepted for publication, Springer Journal of Ambient Intelligence and Humanized Computing.
8. Guo, P.Y., Zhu, D.Y., Lam, C.K.J., Li, V.O.K., “The Future of Wind Energy Development in China: Drivers and barriers,” in Wind Energy Engineering: A Handbook for Onshore and Offshore Wind Turbines, Elsevier, accepted for publication.
9. Zhu, J. Y., Zheng, Y., Yi, X., and Li, V.O.K. “A Gaussian Bayesian Model to identify spatio-temporal causalities for air pollution based on urban big data,” SmartCity16: The 2nd IEEE INFOCOM Workshop on Smart Cities and Urban Computing, San Francisco, California, USA, April 2016.
10. Zhu, Y., Sun. C., and Li, V.O.K., “Granger-Causality-based air quality estimation with spatio-temporal (S-T) heterogeneous big data,” Proc. IEEE INFOCOM Smart City Workshop, Hong Kong, China, April 2015.

Under review or under preparation

1. Li, V.O.K., Lam, J.C.K., Chen, Y., and Gu, J., “Deep learning model to estimate air pollution using M-BP to fill in missing proxy urban data,” submitted for publication to IEEE Globecom.
2. Yu, Y., Yu, J.J.Q., Li, V.O.K., and Lam, J.C.K., “Missing data recovery with low-rank singular value thresholding for air quality measurements,” submitted for publication to IEEE Globecom.
3. Zhu, J. Y., Zhang, C., Zhi, S., Li, V.O.K., Han, J., and Zheng, Y., “p-Causality: Identifying spatiotemporal causal pathways for air pollutants with urban big data,” submitted for publication to IEEE Trans. on Big Data.
4. Li, V.O.K., Lam, J.C.K., Guo, B., Han, Y, “Big data technologies to overcome the challenges of data collection with a human in the loop,” submitted to Big Data in Medicine: Tools, Transformation and Translation, Cambridge University.
5. Guo, P., Li, V.O.K., Lam, J.C.K., “Customized differential pricing for different electricity user groups,” submitted to International Association for Energy Economics, Austria, 2017.
6. Lam, C.K.J., Li, VOK, Reiner, D., Lee, CW, Chen, Y., and M. Ma., “What predicts government trustworthiness in nuclear safety contingency governance in the United Kingdom?” (in preparation to be submitted to PNAS)