Journal Articles

• Lin, Y., Wang, M., Goes, F.S., Tan, K., Zandi, P., Hyde, T., Weinberger, D.R., Potash, J.B., Kleinman, J.E. and Jaffe, A.E., Han, S., “Integrating brain methylome with GWAS for psychiatric risk gene discovery”. bioRxiv, p.440206, 2018.
• Lin, Y., Afsha, S., Rajadhyaksha, A., Potash, J. and Han, S., “A machine learning approach to predicting autism risk genes: Validation of known genes and discovery of new candidates”. bioRxiv, p.463547, 2018.
• Lin, Y., Huang, S., Simon, G.E., and Liu, S., “Cost-effectiveness analysis for prognostic-based depression monitoring”, IIE transactions on Healthcare System Engineering, 9: 1-19, 2019.
• Lin, Y., Liu, S., and Huang, S., “Selective Sensing of A Heterogeneous Population of Units with Dynamic Health Conditions”, IIE Transactions, 50(12):1076-88, 2018.
• Lin, Y., Huang, S., Simon, G.E., and Liu, S., “Data-based Decision Rules to Personalize Depression Follow-up”, Scientific Reports, 5064, 2018.
• Lin, Y., Liu, K., Byon, E., Liu, S., and Huang, S., “A Collaborative Learning Framework for Estimating Many Individualized Regression Models in A Heterogeneous Population”, IEEE Transactions on Reliability, 99: 1-14, 2017.
• Li, M., Lin, Y., Huang, S., and Crossland, C., “The Use of Sparse Inverse Covariance Estimation for Relationship Detection and Hypothesis Generation in Strategic Management”, Strategic Management Journal, 37: 86-97, 2016.
• Lin, Y., Huang, S., Simon, G.E., and Liu, S., “Analysis of Depression Trajectory Patterns using Collaborative Learning”, Mathematical Biosciences, 282: 191-203, 2016.
• Lin, Y., Qian, X., Krischer, J., Vehik, K., Lee, H.S. and Huang, S, “A Rule-Based Prognostic Model for Type 1 Diabetes by Identifying and Synthesizing Baseline Profile Patterns”, PLOS one, 9(6): e91095, 2014.

Conference Papers

• Shah, R., Zhang, S., Lin, Y. and Wu, P., “xSVM: Scalable Distributed Kernel Support Vector Machine Training,” 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, CA, USA, 2019, pp. 155-164.
• Lin, Y., Chen, Z., Cao, C et al., “Collaborative Alert Ranking for Enterprise Security System”, in Conference on Information and Knowledge Management 2018 (CIKM 2018), Oct. 22 - Oct.26, 2018, Turin, Italy. (historical paper acceptance rate < 25%), 2018.
• Dong, B., Chen, Z., Wang, H., Tang, L.A., Zhang, K., Lin, Y., Li, Z., Chen, H., Efficient discovery of abnormal event sequences in enterprise security systems. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017 Nov 6 (pp. 707-715).
• Lin, Y., Liu, S., and Huang, S., “A Longitudinal Pattern Based Prognostic Model for Depression Monitoring via Rule-based Method”, In 38th Annual Meeting of the Society for Medical Decision Making (SMDM), Oct 23 - Oct 24, 2016, Vancouver, CA. (Abstract), 2016.
• Lin, Y., Liu, S., and Huang, S., “Adaptive Monitoring of Depression Patient Population: A Selective Sensing Approach”, In 38th Annual Meeting of the Society for Medical Decision Making (SMDM), Oct 23 - Oct 24, 2016, Vancouver, CA. (Abstract), 2016.
• Lin, Y., Huang, S., and Liu, S., “Analysis of Depression Trajectory Patterns Using Collaborative Learning”, In 37th Annual Meeting of the Society for Medical Decision Making (SMDM), Oct 18 - Oct 21, 2015, St. Louis, MO. (Abstract: invited for oral presentation), 2015.
• Lin, Y., Liu, K., Byon, E., Qian, X., and Huang, S., “Domain-knowledge Driven Cognitive Degradation Modeling for Alzheimer’s Disease”, In SIAM International Conference on Data Mining 2015 (SDM 2015), Apr 30 - May 2, 2015, Vancouver, CA. (historical paper acceptance rate < 25%), 2015.

Student under my supervision