Journal Publications

1. Song, B., and Li, V.O.K., “A revisit of infinite population models for evolutionary algorithms on continuous optimization problems,” accepted for publication, Evolutionary Computation.
2. Yu, J.Q., Hill, D., Li, V.O.K., and Hou, Y., “Synchrophasor recovery and prediction: A graph-based deep learning approach,” accepted for publication, IEEE Internet of Things Journal.
3. Sun, S., Yu, Y., Li, V.O.K., and Lam, J.C.K., “Multi-type sensor placements in Gaussian spatial fields for environmental monitoring,” Sensors, Vol. 19, Jan 2019.
4. Lu, Z., Li, V.O.K., and Shuai, Q.Q., “Price competition of spreaders in profit-maximizing sponsored viral marketing,” IEEE Trans. on Computational Social Systems, Vol. 5, No. 4, Dec 2018, pp. 931 – 941.
5. Guo, P., Lam, J.C.K., and Li, V.O.K., “Drivers of domestic electricity users’ price responsiveness: A novel machine learning approach,” Applied Energy, Vol. 235, pp. 900 – 913.
6. Zhu, J.Y., Zhang, C., Zhang, H., Zhi, S., Li, V.O.K., Han, J., and Zheng, Y. “pg-Causality: Identifying spatiotemporal causal pathways for air pollutants with urban big data,” IEEE Trans. on Big Data, Vol. 4, No. 4, Dec 2018, pp. 571-585.
7. Guo, B., Liu, Y., Wang, L., Li, V.O.K., Lam, J.C.K., and Yu, Z., “Task allocation in spatial crowdsourcing: Current state and future directions,” accepted for publication, IEEE Internet of Things Journal.
8. Jing, Y., Guo, B., Wang, Z., Li, V.O.K., Lam, J.C.K., and Yu, Z., “CrowdTracker: Optimized urban moving object tracking using mobile crowd sensing,” IEEE Internet of Things Journal, Vol. 5, No. 5, Oct 2018, pp. 3452-3463.
9. Bai, R., Lam, J.C.K., and Li, V.O.K., “A review on health cost accounting of air pollution in China,” Environment International, Volume 120, November 2018, pp. 279-294
10. Tong, X., Guo, B., Wang, P., Yu, Z., Lam, J.C.K., and Li, V.O.K., “FreeSense: A robust approach for indoor human detection using Wi-Fi signals,” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 2, No. 3, Sep 2018.

 

Conference Proceedings

1. Han, Y., Lam, J.C.K., and Li, V.O.K., “A Bayesian LSTM Model to evaluate the effects of air pollution control regulations in China,” IEEE International Conference on Big Data, Workshop on Big Data and AI for Air Quality Estimation, Forecasting, and Health Advice, Seattle, Washington, USA, Dec 2018.
2. Lu, Z., Lam, J.C.K., Li, V.O.K., Han, Y., and Gilani, Z., “In search of a better land: Would people move to a country with better air quality? A global survey based on Twitter data,” IEEE International Conference on Big Data, Workshop on Big Data and AI for Air Quality Estimation, Forecasting, and Health Advice, Seattle, Washington, USA, Dec 2018.
3. Fan, Y., Lam, J.C.K., and Li, V.O.K., “Unsupervised domain adaptation with generative adversarial networks for facial expression recognition,” IEEE International Conference on Big Data, Workshop on Big Data and AI for Air Quality Estimation, Forecasting, and Health Advice, Seattle, Washington, USA, Dec 2018.
4. Wang, A., Li, V.O.K., and Lam, J.C.K., “Optimization of urban heating network design using Genetic Algorithm,” IEEE International Conference on Big Data, Workshop on Big Data and AI for Air Quality Estimation, Forecasting, and Health Advice, Seattle, Washington, USA, Dec 2018.
5. Wang, Y., Wu, X.M., Li, Q., Gu, J., Xiang, W., Zhang, L., and Li, V.O.K., “Large margin meta-learning for few-shot classification,” Neural Information Processing Systems (NIPS) Workshop on Meta-Learning, Montreal, Canada, Dec 2018.
6. Chen, Y., Li, V.O.K., Cho, K., and Bowman, S.R., “A stable and effective learning strategy for trainable greedy decoding,” ACL Conference on Empirical Methods in Natural Language Processing (EMNLP), Brussels, Belgium, Oct 2018.
7. Gu, J., Wang, Y., Chen, Y., Li, V.O.K., and Cho, K., “Meta-learning for low-resource neural machine translation,” ACL Conference on Empirical Methods in Natural Language Processing (EMNLP), Brussels, Belgium, Oct 2018.
8. Yang, H., Li, V.O.K., Lam, J.C.K., and Lu, Z., “UMeAir: Predicting momentary happiness towards air quality via machine learning,” WellComp'18: 1st International Workshop on Computing for Well-being, UBICOMP, Singapore, Oct 2018.
9. Fan, Y., Lam, J.C.K., and Li, V.O.K., “Video-based emotion recognition using deeply-supervised neural networks,” Proc. of the 20th ACM International Conference on Multimodal Interaction, Boulder, Colorado, USA, Oct 2018. (The model described in this paper won the Third Place in the EmotiW 2018 Challenge.)
10. Fan, Y., Lam, J.C.K., and Li, V.O.K., “Multi-region ensemble convolutional neural network for facial expression recognition,” European Neural Network Society 27th International Conference on Artificial Neural Networks, Rhodes, Greece, Oct 2018.
11. Cao, M., Shuai Q. and Li, V.O.K., “Navigation-based traffic signal control in intelligent transportation systems,” Proc. IEEE Globecom, Abu Dhabi, United Arab Emirates, Dec 2018.
12. Sun, S., Yu, Y., Li, V.O.K., and Lam, J.C.K., “Optimal multi-type sensor placements in Gaussian spatial fields for environmental monitoring,” Proc. IEEE International Smart Cities Conference (ISC2 2018), Kansas City, MO, USA, Sept 2018.
13. Gu, J., Hassan, H., Devlin, J., Universal neural machine translation for extremely low resource languages,” Proc. The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), New Orleans, Louisiana, USA, June 2018.