Research Output

  1. DeepSeq2Drug: An expandable ensemble end-to-end anti-viral drug repurposing benchmark framework by multi-modal embeddings and transfer learning
    Xie, W., Yu, J., Huang, L., For, L. S., Zheng, Z., Chen, X., Wang, Y., Liu, Z., Peng, C. & Wong, K., Jun 2024, Computers in Biology and Medicine, 175, 108487.
  2. Gaining a Seat at the Table: Enhancing the Attractiveness of Online Lending for Institutional Investors
    Gopal, R. D., Qiao, X., Strub, M. S. & Yang, Z., 5 Apr 2024, Information Systems Research.
  3. Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation
    Chen, N., Yu, J., Liu, Z., Meng, L., Li, X. & Wong, K., 4 Apr 2024, Nucleic Acids Research, gkae210.
  4. Intermittent boundary control for fixed-time stability of reaction-diffusion systems  
    Jia, W., Xie, J., Guo, H. & Wu, Y., Apr 2024, Chaos, Solitons and Fractals, 181, 8 p., 114704.
  5. A distributed route network planning method with congestion pricing for drone delivery services in cities
    He, X., Li, L., Mo, Y., Huang, J. & Qin, S. J., Mar 2024, Transportation Research Part C: Emerging Technologies, 160, 104536.
  6. scGREAT: Transformer-Based Deep-Language Model for Gene Regulatory Network Inference from Single-Cell Transcriptomics
    Wang, Y., Chen, X., Zheng, Z., Huang, L., Xie, W., Wang, F., Zhang, Z., & Wong, K., 28 Feb 2024, iScience.
  7. Invariant Random Forest: Tree-Based Model Solution for OOD Generalization
    LIAO, Y., WU, Q. & YAN, X., 20-27 Feb 2024, The Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024).
  8. Optimal (0,1)-matrix completion with majorization ordered objectives
    Mo, Y., Chen, W., You, K. & Qiu, L., Feb 2024, Automatica, 160, 111430.
  9. Unsupervised Gene-Cell Collective Representation Learning with Optimal Transport
    Yu, J., Chen, N., Gao, M., Li, X. & Wong, K., 20-27 Feb 2024, Proceedings of the 38th AAAI Conference on Artificial Intelligence, Dy, J., Natarajan, S. & Wooldridge, M. (eds.). Washington, DC: AAAI Press, vol. 38, no. 1, p. 356-364. 
  10. Knowledge-Informed Sparse Learning for Relevant Feature Selection and Optimal Quality Prediction
    Liu, Y. & Qin, S. J., Dec 2023, IEEE Transactions on Industrial Informatics, 19, 12, p. 11499-11507 9 p.
  11. Latent Dynamic Networked System Identification with High-Dimensional Networked Data
    Yu, J., Mo, Y. & Qin, S. J., 15 Dec 2023, Proceedings of the IEEE Conference on Decision & Control, 62nd IEEE Conference on Decision and Control (CDC 2023), p. 461-466, Singapore
  12. Probabilistic Reduced-Dimensional Vector Autoregressive Modeling for Dynamics Prediction and Reconstruction with Oblique Projections
    Mo, Y., Yu, J. & Qin, S. J., 15 Dec 2023, Proceedings of the IEEE Conference on Decision & Control, 62nd IEEE Conference on Decision and Control (CDC 2023), p. 7623-7628, Singapore
  13. LncRNA-Top: Controlled Deep Learning Approaches for LncRNA Gene Regulatory Relationship Annotations across Different Platforms
    Xie, W., Chen, X., Zheng, Z., Wang, F., Zhu, X., Lin, Q., Sun, Y., Wong, K., 17 Nov 2023, iScience. 26, 11, 108197.
  14. A novel bidirectional DiPLS based LSTM algorithm and its application in industrial process time series prediction
    Wang, Y., Bao, D. & Qin, S. J., 15 Sep 2023, Chemometrics and Intelligent Laboratory Systems, 240, 104878.
  15. Maximizing Anomaly Detection Performance Using Latent Variable Models in Industrial Systems
    Wang, K., Guo, Z., Mo, Y., Wang, Y. & Yuan, X., 14 Aug 2023, IEEE Transactions on Automation Science and Engineering,
  16. Chromothripsis Detection with Multiple Myeloma Patients Based on Deep Graph Learning
    Yu, J., Chen, N., Zheng, Z., Gao, M., Liang, N. and Wong, K.C., Jul 2023, Bioinformatics, 39, 7, 9 p.btad422.
  17. Compact Dynamic Inner Canonical Correlation Analysis for Nonstationary Dynamic Feature Extraction and Prediction
    Chen, J. & Qin, S. J., 2023, IFAC-PapersOnLine, 22nd World Congress of the International Federation of Automatic Control (IFAC 2023), vol. 56, p. 3190-3196, 9-14 July 2023, Yokohama, Japan
  18. Deep into The Domain Shift : Transfer Learning through Dependence Regularization
    Ma, S., Yuan, Z., Wu, Q., Huang, Y., Hu, X., Leung, C.H., Wang, D. and Huang, Z., Jun 2023, IEEE Transactions on Neural Networks and Learning Systems.
  19. Optimizing Demand Response in Distribution Network with Grid Operational Constraints
    Zhao, T., Zhou, M., Mo, Y., Wang, J.M., Luo, J., Pan, X. and Chen, M., Jun 2023, Proceedings of the 14th ACM International Conference on Future Energy Systems, pp. 299-313.
  20. Limited Fault Data Augmentation with Compressed Sensing for Bearing Fault Diagnosis
    Wang, D., Dong, Y., Wang, H. and Tang, G., May 2023, IEEE Sensors Journal, Vol.23(13), p.14499-14511.
  21. Towards Balanced Representation Learning for Credit Policy Evaluation
    Huang, Y., Leung, C. H., Ma, S., Yuan, Z., Wu, Q., Wang, S., Wang, D., Huang, Z., 25-27 Apr 2023, Proceedings of Machine Learning Research, The 26th International Conference on Artificial Intelligence and Statistics, Ruiz, F., Dy, J. & van de Meent, J. (eds.). PMLR, Vol. 206. p. 3677-3692.
  22. Enabling Single-Cell Drug Response Annotations from Bulk RNA-Seq Using SCAD
    Zheng, Z., Chen, J., Chen, X., Huang, L., Xie, W., Lin, Q., Li, X., Wong, K., 14 Apr 2023, Advanced Science, 10, 11, 2204113.
  23. Commodity momentum: A tale of countries and sectors
    Fan, J.H. and Qiao, X., Mar 2023, Journal of Commodity Markets, 29, p.100315.
  24. AutoSTL : Automated Spatio-Temporal Multi-Task Learning
    Zhang, Z., Zhao, X., Miao, H., Zhang, C., Zhao, H. & Zhang, J., 2023, Proceedings of the AAAI Conference on Artificial Intelligence, The 37th AAAI Conference on Artificial Intelligence. Williams, B., Chen, Y. & Neville, J. (eds.). Washington, DC: AAAI Press, vol. 37, no. 4 p. 4902-4910. 
  25. Machine Learning in Metastatic Cancer Research: Potentials, Possibilities, and Prospects
    Petinrin, O.O., Saeed, F., Toseef, M., Liu, Z., Basurra, S., Muyide, I.O., Li, X., Lin, Q. and Wong, K.C., Mar 2023, Computational and Structural Biotechnology Journal, Vol. 21, p.2454-2470.
  26. A Combinatorial Machine-learning-driven Approach for Predicting Glass Transition Temperature Based on Numerous Molecular DescriptorsLi, D., Dong, C., Chen, Z., Dong, Y. and Liu, J., Mar 2023, Molecular Simulation, 49(6), pp.617-627.
  27. Short-term Forecasting of Origin-destination Matrix in Transit System via a Deep Learning Approach
    He, Y., Zhao, Y. & Tsui, K., Feb 2023, Transportmetrica A: Transport Science, 19(2), p.2033348.
  28. Counter-cyclical Margins for Option Portfolios
    CHEN, Y., WU, Q. & LI, D., Jan 2023, Journal of Economic Dynamics and Control, 146, 104572.
  29. Partial Least Squares, Steepest Descent, and Conjugate Gradient for Regularized Predictive Modeling
    Qin, S.J., Liu, Y. and Tang, S., Dec 2022, AIChE Journal, 69(4), p.e17992.
  30. Time-Varying Online Transfer Learning for Intelligent Bearing Fault Diagnosis With Incomplete Unlabeled Target DataZhou, Y., Dong, Y. and Tang, G., Dec 2022, IEEE Transactions on Industrial Informatics, Vol. 19(6), p. 7733-7741
  31. Sequence-to-Set Generative Models
    Tang, L., Zhou, Y. and Yang, Y., Nov 2022, Advances in Neural Information Processing Systems, 35, pp.14986-14997.
  32. Improving Gaussian Process Emulators with Boundary Information
    Li, Z. and Tan, M.H.Y., Nov 2022, Artificial Intelligence, Big Data and Data Science in Statistics: Challenges and Solutions in Environmetrics, the Natural Sciences and Technology, p. 171-192
  33. Portfolio Choice for Online Loans and Implications for Platforms 
    RD Gopal, X Qiao, MS Strub, Z Yang, Nov 2022, Journal of Commodity Markets
  34. Neuron-Compressed Deep Neural Network and Its Application in Industrial Anomaly Detection
    Wang, K., Yan, C., Mo, Y., Yuan, X., Wang, Y. and Yang, C., Oct 2022, IEEE Transactions on Industrial Informatics, Vol.19(7), p.7914-7924
  35. Reactions’ Descriptors Selection and Yield Estimation Using Metaheuristic Algorithms and Voting Ensemble
    Petinrin, O.O., Saeed, F., Li, X., Ghabban, F. and Wong, K.C., Oct 2022, Computers, Materials and Continua, 70(3), pp.4745-4762.
  36. Risk and Potential: An Asset Allocation Framework with Applications to Robo-Advising
    Cui, X., Li, D., Qiao, X. & Strub, M. S., Sep 2022, Journal of the Operations Research Society of China, 10(3), pp.529-558.
  37. LSTM and Statistical Learning for Dynamic Inferential Modeling with Applications to a 660MW Boiler
    Li, J., Tan, P. and Qin, S.J., Aug 2022, IFAC-PapersOnLine, 55(7), pp.600-605.
  38. Option Pricing via Breakeven Volatility
    Hull, B., Li, A. and Qiao, X., Aug 2022, Financial Analysts Journal, 79(1), pp.99-119.
  39. Performance Evaluation, Factor Models, and Portfolio Strategies : Evidence from Chinese Mutual Funds
    Chi, Y., Liu, Y. and Qiao, X., Aug 2022, The Journal of Portfolio Management, 48(8), pp.159-176.
  40. Subclass-specific Prognosis and Treatment Efficacy Inference in Head and Neck Squamous Carcinoma
    Zheng, Z., Xie, W., Chen, X., Wang, F., Huang, L., Li, X., Lin, Q. & Wong, K., Aug 2022, IEEE Journal of Biomedical and Health Informatics, 26(8), pp.4303-4313.
  41. A Gaussian Process Emulator Based Approach for Bayesian Calibration of a Functional Input
    Li, Z. and Tan, M.H.Y., Jul 2022, Technometrics, 64(3), pp.299-311.
  42. Fractional Calculus & Machine Learning Methods Based Rubber Stress-strain Relationship Prediction
    Li, D., Liu, J., Zhang, Z., Yan, M., Dong, Y. and Liu, J., Jul 2022, Molecular Simulation, 48(10), pp.944-954.
  43. Latent State Space Modeling of High-Dimensional Time Series with a Canonical Correlation Objective
    Yu, J. & Qin, S. J., Jun 2022, IEEE Control Systems Letters, vol. 6, pp. 3469-3474
  44. Latent Vector Autoregressive Modeling and Feature Analysis of High Dimensional and Noisy Data from Dynamic SystemsQin, S. J., Jun 2022, AIChE Journal, 68(6), p.e17703.
  45. A Novel Two-step Sparse Learning Approach for Variable Selection and Optimal Predictive Modeling
    Liu, Y. and Qin, S.J., Jun 2022, IFAC-PapersOnLine, 55(7), pp.57-64.
  46. COVID-19 Effects on Intraday Stock Market Behavior
    Nie, J., Qiao, X. & Yan, S., 2022, Transformations in Banking, Finance and Regulation, vol. 1, World Scientific , pp. 229-252
  47. Mutual Fund Investing in the Chinese A-share Market
    Chi, Y. and Qiao, X., 2022, Handbook of Banking and Finance in Emerging Markets, pp.32-50.
  48. A Machine Learning Framework to Predict the Tensile Stress of Natural Rubber: Based on Molecular Dynamics Simulation DataHuang, Y., Chen, Q., Zhang, Z., Gao, K., Hu, A., Dong, Y., Liu, J. & Cui, L., May 2022, Polymers, 14(9), p.1897.
  49. Reducing Healthcare Disparities Using Multiple Multiethnic Data Distributions with Fine-tuning of Transfer LearningToseef, M., Li, X. & Wong, K., May 2022, Briefings in Bioinformatics, 23(3), p.bbac078.
  50. Fault Diagnosis of Dynamic Processes with Reconstruction and Magnitude Profile Estimation for an Industrial ApplicationLiu, Q., Song, B., Ding, X. and Qin, S.J., Apr 2022, Control Engineering Practice, 121, p.105008.
  51. Human Disease Prediction from Microbiome Data by Multiple Feature Fusion and Deep Learning
    Chen, X., Zhu, Z., Zhang, W., WANG, Y., Wang, F., Yang, J. & Wong, K. C., Apr 2022,  iScience, 25(4), 104081.
  52. Multi-fidelity Gaussian Process Modeling with Boundary Information
    Ye, W. & Tan, M. H. Y., Mar 2022, Applied Stochastic Models in Business and Industry, 38(2), pp.216-239.
  53. Particle Swarm Optimized Gaussian Process Classifier for Treatment Discontinuation Prediction in Multicohort Metastatic Castration-Resistant Prostate Cancer PatientsPetinrin, O. O., Li, X. & Wong, K., Mar 2022, IEEE Journal of Biomedical and Health Informatics, 26(3), p.1309-1317. p.
  54. DeepMotifSyn: A Deep Learning Approach to Synthesize Heterodimeric DNA Motifs
    Lin, J., Huang, L., Chen, X., Zhang, S. and Wong, K.C., Jan 2022, Briefings in Bioinformatics, 23(1), p.bbab334.
  55. EGFI : Drug-drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence InformationHuang, L., Lin, J., Li, X., Song, L., Zheng, Z. and Wong, K.C., Jan 2022, Briefings in Bioinformatics, 23(1), p.bbab451.
  56. A Non-iterative Partial Least Squares Algorithm for Supervised Learning with Collinear Data
    Qin, S. J., Dec 2021, 2021 The 60th IEEE Conference on Decision and Control (CDC) (pp. 3683-3688). IEEE.
  57. Optimal Option Hedging with Policy Gradient
    Xiao, B., Yao, W. & Zhou, X., Dec 2021, 2021 International Conference on Data Mining Workshops (ICDMW) (pp. 1112-1119). IEEE.
  58. Latent Vector Autoregressive Modeling for Reduced Dimensional Dynamic Feature Extraction and Prediction
    Qin, S. J., Dec 2021, 2021 60th IEEE Conference on Decision and Control (CDC) (pp. 3689-3694). IEEE.
  59. Metric Learning Based Vision Transformer for Product Matching
    Huang, L., Shao, W., Wang, F., Xie, W. & Wong, K., Dec 2021,  Neural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part I 28 (pp. 3-13). Springer International Publishing.
  60. A Stable Lasso Algorithm for Inferential Sensor Structure Learning and Parameter Estimation
    Qin, S. J. & Liu, Y., Nov 2021, Journal of Process Control, 107, p. 70-82
  61. Integration of Process Knowledge and Statistical Learning for the Dow Data Challenge Problem
    Qin, S.J., Guo, S., Li, Z., Chiang, L. H., Castillo, I., Braun, B. & Wang, Z., Oct 2021, Computers and Chemical Engineering, 153, 107451.
  62. Early Cancer Detection from Genome-wide Cell-free DNA Fragmentation via Shuffled Frog Leaping Algorithm and Support Vector MachineLiu, L., Chen, X. & Wong, K., Oct 2021, Bioinformatics, 37, 19, p. 3099–3105 7 p.
  63. Deep Learning Credit Risk Modeling
    G Manzo, X Qiao, Sep 2021,  The Journal of Fixed Income
  64. Deep Dynamic Adaptive Transfer Network for Rolling Bearing Fault Diagnosis With Considering Cross-Machine InstanceZhou, Y., Dong, Y., Zhou, H. and Tang, G., Sep 2021, IEEE Transactions on Instrumentation and Measurement
  65. . Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey.
    Liu, L., Chen, X., Petinrin, O. O., Zhang, W., Rahaman, S., Tang, Z. & Wong, K., Jul 2021, Life, 11, 7, 638
  66. Plant-wide Troubleshooting and Diagnosis Using Dynamic Embedded Latent Feature Analysis
    Qin, S.J., Liu, Y. and Dong, Y., Jun 2021, Computers & Chemical Engineering, 152, p.107392.
  67. Extracting a Low-dimensional Predictable Time Series
    Dong, Y., Qin, S.J. and Boyd, S.P., May 2021, Optimization and Engineering, pp.1-26.
  68. . Noninvasive Early Diagnosis of Intestinal Diseases Based on Artificial Intelligence in Genomics and MicrobiomeZhang, W., Chen, X. & Wong, K., Apr 2021, Journal of Gastroenterology and Hepatology (Australia). 36, 4, p. 823-831
  69. Stable Lasso for Model Structure Learning of Inferential Sensor Modeling
    Qin, S.J. and Liu, Y., Jan 2021, IFAC-PapersOnLine, 54(7), pp.228-233.
  70. Adaptive Dynamic Predictive Monitoring Scheme Based on DLV Models
    Dong, Y. and Qin, S.J., Jan 2021, IFAC-PapersOnLine, 54(7), pp.91-96.
  71. On Data Science for Process Systems Modeling, Control and Operations
    Qin, S.J. and Dong, Y., Nov 2020, IFAC-PapersOnLine, 53(2), pp.11325-11331.
  72. Bridging Systems Theory and Data Science: A Unifying Review of Dynamic Latent Variable Analytics and Process MonitoringQin, S.J., Dong, Y., Zhu, Q., Wang, J. and Liu, Q., Oct 2020, Annual Reviews in Control, 50, pp.29-48.
  73. Modeling and Analyzing Impact Factors of Metro Station Ridership : An Approach Based on a General Estimating Equation
    He, Y., Zhao, Y. and Tsui, K. L., 2020, IEEE Intelligent Transportation Systems Magazine, 12, 4, p. 195-207.
  74. Capturing Deep Tail Risk via Sequential Learning of Quantile Dynamics
    Wu, Q. and Yan, X., Dec 2019, Journal of Economic Dynamics and Control, 109, p.103771.

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