Selected Recent Publications

(# indicates student supervision; total over 150 peer-reviewed papers)

Refereed Journals

  1. B Li#, Z Wang#, Z Liu#, Y Tao, C Sha, M He, X Li, "DrugMetric: Quantitative Drug-likeness Scoring Based on Chemical Space Distance," Briefings in Bioinformatics (accepted)
  2. S. Ling#, L. Yan#, R. Mao#, J. Li, H. Xi, F. Wang, X. Li, and M. He, "A Coarse-Fine Collaborative Learning Model for Three Vessel Segmentation in Fetal Cardiac Ultrasound Images," IEEE Journal of Biomedical and Health Informatics (accepted)
  3. Z Wang#, Z Feng, Y Li, B Li#, Y Wang#, C Sha, M He, X Li, "BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation," Briefings in Bioinformatics, 2023.
  4. Y. Zhou#, X. Ma#, D. Wu, and X. Li, "Communication-efficient and Attack-Resistant Federated Edge Learning with Dataset Distillation," IEEE Transactions on Cloud Computing (TCC), 2023.
  5. Y. Li#, D. Zhou, G. Zheng, D. Wu, X. Li, Y. Yuan, "DyScore: A Boosting Scoring Method with Dynamic Properties for Identifying True Binders and Non-binders in Structure-based Drug Discovery," Journal of Chemical Information and Modeling, 2022.
  6. X. Yuan#, L. Ding, L. Zhang, X. Li, and D. Wu, "ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles," IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), Vol. 6 (5), 2022. (2025 IEEE CIS TETCI Outstanding Paper Award)
  7. R. Sun#, X. Yuan#, P. He#, Q. Zhu#, A. Chen#, A. Gregio, D. Oliveira, X. Li, "Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection," IEEE Transactions on Neural Networks and Learning System (TNNLS), 2022.
  8. Mohammad Ali Rezaei, Yanjun Li, Dapeng Oliver Wu, Xiaolin Li, Chenglong Li, "Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction," IEEE Transactions on Computational Biology and Bioinformatics (TCBB), Vol. 19 (1), pp. 407-417, 2022.
  9. R. Sun#, X. Yuan#, M. Botacin, N. Sapountzis, M. Bishop, D. E. Porter, X. Li, A. Gregio, D. Oliveira, "A Praise for Defensive Programming: Leveraging Uncertainty for Effective Malware Mitigation," IEEE Transactions on Dependable and Secure Computing (TDSC), 2020.
  10. Loftus TJ, Filiberto AC, Li Y, Balch J, Cook AC, Tighe PJ, Efron PA, Upchurch GR Jr, Rashidi P, Li X, Bihorac A., "Decision analysis and reinforcement learning in surgical decision-making," Surgery., Vol. 168 (2), pp. 253-266, 2020.
  11. Qile Zhu#, Xiyao Ma#, and Xiaolin Li, "Statistical Learning for Semantic Parsing: A Survey," Big Data Mining and Analytics, Vol. 2 (4), pp. 217-239, December 2019.
  12. Xiaoyong Yuan#, Pan He#, Qile Zhu#, Xiaolin Li, "Adversarial Examples: Attacks and Defenses for Deep Learning," IEEE Transactions on Neural Networks and Learning System (TNNLS), Vol. 30 (9), pp. 2805-2824, September 2019.
  13. A. Bihorac, T. Ozrazgat-Baslanti, A. Ebadi, A. Motaei, M. Madkour, P. M. Pardalos, G. Lipori, W. Hogan, P. A. Efron, F. Moore, L. L. Moldawer, D.Z. Wang, C. E. Hobson, P. Rashidi, X. Li, P. Momcilovic, MySurgeryRisk: Development and Validation of a Machine-Learning Risk Algorithm for Major Complications and Death after Surgery. Annals of Surgery, Vol. 269 (4), pp. 652-662, April 2019.
  14. Laksshman Sundaram#, Hong Gao, Samskruthi Padigepati#, Jeremy McRae, Yanjun Li#, Jack Kosmicki, Nondas Fritzilas, Jörg Hakenberg, AninditaDutta, John Shon, Jinbo Xu, Serafim Batzoglou, Xiaolin Li, Kyle Farh, "Predicting the clinical impact of human mutation with deep neural networks," Nature Genetics, Vol. 50 (8), pp. 1161–1170, 2018.
  15. Kaikai Liu# and Xiaolin Li, "Enhancing Localization Scalability and Accuracy via Opportunistic Sensing," IEEE/ACM Transactions on Networking (TON),Vol. 26 (3), pp. 1517-1530, June 2018.
  16. Qile Zhu#, X. Li, Ana Conesa, and Cécile Pereira, GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text, Bioinformatics, ISCB, Oxford, 2017.
  17. S. Laksshman#, R. Bhat#, V. Viswanath#, X. Li, "DeepBipolar: Identifying Genomic Mutations for Bipolar Disorder via Deep Learning," Human Mutation, Vol. 38 (9), pp. 1217–1224, September 2017.
  18. Roxana Daneshjou, et al, X. Li, et al (30 institutes), "Working toward Precision Medicine: Predicting Phenotypes from Exomes in the Critical Assessment of Genome Interpretation (CAGI) Challenges," Human Mutation, Vol. 38 (9), pp. 1182-1192, Sep. 2017.
  19. K. Liu#, X. Liu#, and X. Li, "Guoguo: Enabling Fine-grained Smartphone Localization via Acoustic Anchors," IEEE Transactions on Mobile Computing (TMC), Vol. 15 (5), pp. 1144-1156, May 2016.
  20. H. Zhao#, M. Pan#, X. Liu#, X. Li, and Y. Fang, "Exploring Fine-Grained Resource Rental Planning in Cloud Computing," IEEE Transactions on Cloud Computing (TCC), Vol. 3 (3), pp. 304-317, Sep. 2015.
  21. K. Liu# and X. Li, "Enabling Context-Aware Indoor Augmented Reality via Smartphone Sensing and Vision Tracking," ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Vol. 12 (1), Oct. 2015.
  22. K. Xu#, Y Guo#, L. Guo#, Y. Fang, and X. Li, "My Privacy My Decision: Control of Photo Sharing on Online Social Networks," IEEE Transactions on Dependable and Secure Computing (TDSC), June 2015.

Refereed Conference Proceedings

  1. Linghui Chen, Xiqiang Dai, Hong Wang, Yuanyuan Cen, Xiaochuan Peng, Hongyu Li and Xiaolin Li, "A Secure and Efficient Sample Filtering Protocol for Massive Data," Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 2020), with the 34th Conference on Neural Information Processing Systems (NeurIPS 2020). 
  2. Fucheng Pan, Dan Meng, Yu Zhang, Hongyu Li and Xiaolin Li, "Secure Federated Feature Selection for Cross-Feature Federated Learning," Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 2020), with the 34th Conference on Neural Information Processing Systems (NeurIPS 2020).
  3. Xiaojuan Wang, Zhihui Fu, Dan Meng, Xiaochuan Peng, Hong Wang, Hongyu Li and Xiaolin Li, "Collusion-free Cross-feature Logistic Regression," Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 2020), with the 34th Conference on Neural Information Processing Systems (NeurIPS 2020).
  4. Da Wei, Dan Meng, Hongyu Li and Xiaolin Li, "Masked Transmitting for Federated Learning," Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 2020), with the 34th Conference on Neural Information Processing Systems (NeurIPS 2020).
  5. Yanlin Zhou#, George Pu#, Xiyao Ma#, Xiaolin Li and Dapeng Wu, "Communication-Efficient Federated Learning via Dataset Distillation," Workshop on Scalability, Privacy, and Security in Federated Learning (NeurIPS-SpicyFL 2020), with the 34th Conference on Neural Information Processing Systems (NeurIPS 2020).
  6. Dan Meng; Hongyu Li; Fan Zhu; Xiaolin Li, "FedMONN: Meta Operation Neural Network for Secure Federated Aggregation,"  the 22nd IEEE International Conference on High Performance Computing and Communications (HPCC 2020).
  7. H. Li, D. Meng, H. Wang, and X. Li, "Knowledge Federation: A Unified and Hierarchical Privacy-Preserving AI Framework," the 11th IEEE International Conference on Knowledge Graph (ICKG 2020).
  8. X. Yuan#, L. Ding, M. Salem, X. Li, D. Wu, "Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks," the 16th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2020).
  9. Q. Zhu#, W. Bi, X. Liu, X. Ma#, X. Li and D. Wu, "A Batch Normalized Inference Network Keeps KL Vanishing Away," the 58th Annual Meeting of the Association for Computational Linguistics,  (ACL 2020).
  10. X. Ma#, Q. Zhu#, Y. Zhou#, X. Li, "Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring," the 34th AAAI Conference on Artificial Intelligence (AAAI 2020). (Oral Presentation) (oral acceptance: 5.9%)
  11. Long Chen, Chujie Lu, Siliang Tang, Jun Xiao, Dong Zhang, Chilie Tan, Xiaolin Li, "Rethinking the Bottom-Up Framework for Query-based Video Localization," the 34th AAAI Conference on Artificial Intelligence (AAAI 2020). (Oral Presentation) (oral acceptance: 5.9%)
  12. X. Yuan#, P. He#, X. Li, D. Wu, "Adaptive Adversarial Attack on Scene Text Recognition," The 8th International Workshop on Security and Privacy in Big Data (BigSecurity 2020), INFOCOM 2020.
  13. Yanlin Zhou#, George Pu#, Fan Lu#, Xiyao Ma#, Xiaolin Li, Runhan Sun, Hsi-Yuan Chen, "Adaptive Tracking and Regulation for Leader-Follower Formation Control using Deep Reinforcement Learning," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019).
  14. Yanjun Li#, Mohammad A. Rezaei, Chenglong Li, Xiaolin Li, "DeepAtom: A Framework for Protein-Ligand Binding Affinity Prediction," IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019).
  15. Xiaoyong Yuan#, Zheng Feng#, Matthew Norton, and Xiaolin Li, "Generalized Batch Normalization: Towards Accelerating Deep Neural Networks," the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019).
  16. X. Ma#, F. Lu#, X. Pan, X. Li, RetailNet: Enhancing Retails of Perishable Products with Multiple Selling Strategies via Pair-Wise Multi-Q Learning, Reinforcement Learning for Real Life Workshop, ICML 2019.
  17. Yanjun Li#, Hengtong Kang#, Ketian Ye#, Shuyu Yin#, and Xiaolin Li, "FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model," Deep Reinforcement Learning Workshop (Oral Presentation) (12 out of over 130 accepted papers) of NIPS 2018.
  18. Qile Zhu#, Zheng Feng#, and Xiaolin Li, "GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model," the 23rd Conference on Empirical Methods in Natural Language Processing (EMNLP 2018).
  19. P. He#, Weilin Huang, Tong He, Qile Zhu#, Yu Qiao, X. Li, "Single Shot Text Detector with Regional Attention," International Conference on Computer Vision (ICCV 2017). (Spotlight Oral) (Acceptance: 45/2143=2.09% for oral; Additionally, 56/2143=2.61% for spotlight)
  20. W Zhang#, J. Fodero#, R. Sengupta#, X. Li, "DeepPositioning:  Intelligent Fusion of Pervasive Magnetic Field and WiFi Fingerprinting for Smartphone Indoor Localization via Deep Learning," the 16th IEEE International Conference on Machine Learning and Applications (ICMLA 2017).
  21.  R. Bhat#, V. Viswanath#, X. Li, "DeepCancer: Detecting Cancer through Gene Expressions via Deep Generative Learning," the 3rd IEEE International Conference on Big Data Intelligence and Computing (DataCom 2017).
  22. Z. Feng#, R. Bhat#, X. Yuan#, D. Freeman, T. Baslanti, A. Bihorac, X. Li, "Intelligent Perioperative System: Towards Real-time Big Data Analytics in Surgery Risk Assessment," the 3rd IEEE International Conference on Big Data Intelligence and Computing (DataCom 2017).
  23. Q. Li#, R. Mohammadi, M. Conti, C. Li#, and X. Li, "GolfEngine: Network Management System for Software Defined Networking," the 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP 2017).
  24. Q. Zhu#, Y. Li#, X. Li, "Character Sequence-to-Sequence Model with Global Attention for Universal Morphological Reinflection," Proceedings of the CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection, in the SIGNLL Conference on Computational Natural Language Learning (CoNLL 2017).
  25. X. Yuan#, C. Li#, X. Li, "DeepDefense: Identifying DDoS Attack via Deep Learning," the 3rd IEEE International Conference on Smart Computing (SmartComp 2017).
  26. R. Sun#, X. Yuan#, A. Lee, Matt Bishop, Donald E. Porter, Xiaolin Li, Andre Gregio and Daniela Oliveira, "The Dose Makes the Poison - Leveraging Uncertainty for Effective Malware Detection," the 15th IEEE Conference on Dependable and Secure Computing (DSC 2017).
  27. R. Bhat#, R. Trevizan#, R. Sengupta#, X. Li, A. Bretas, "Identifying Nontechnical Power Loss via Spatial and Temporal Deep Learning," the 15th IEEE International Conference on Machine Learning and Applications (ICMLA 2016). (Best Paper Award)
  28. K. Liu# and X. Li, "Enhancing Smartphone Indoor Localization via Opportunistic Sensing," the 13th IEEE International Conference on Sensing, Communication and Networking (SECON 2016). (Acceptance: 56/213=26%) (Best Paper Award, 1 in 213 submissions)
  29. X. Yuan#, M. Li#, S. Gaddam#, X. Li, Y. Zhao#, J. Ma#, J. Ge, "DeepSky: Identifying Absorption Bumps via Deep Learning," the 5th IEEE International Congress on Big Data (BigData 2016). (Acceptance: 24%)
  30. K. Liu#, M. Li#, and X. Li, "Hiding Media Data via Shaders: Enabling Private Sharing in the Clouds," the 8th IEEE International Conference on Cloud Computing (CLOUD 2015). (Acceptance: 15%)
  31. Z. Yu#, M. Li#, X. Yang#, H. Zhao#, and X. Li, "Taming Non-Local Stragglers using Efficient Prefetching in MapReduce," IEEE International Conference on Cluster Computing (Cluster 2015). (Acceptance: 38/157=24%)

Books

  1. K. Liu# and X. Li, "Mobile Smart Life via Sensing, Localization, and Cloud Ecosystems,"CRC, 2016.
  2. X. Li and J. Qiu (Eds.), "Cloud Computing for Data Intensive Applications," Springer, 2014(Preface by Microsoft VP Tony Hey and Dennis Gannon).
  3. H. Zhao# and X. Li, "Resource Management in Utility and Cloud Computing," Springer, 2013.
  4. X. Liu# and X. Li, "Location Privacy Protection in Mobile Networks," Springer, 2013.
  5. M. Parashar and X. Li (Eds.), "Advanced Computational Infrastructures for Parallel and Distributed Adaptive Applications," John Wiley and Sons, 2009.