Publications

She has published over 140+ papers in leading venues, including AAAI (15), KDD (13), WWW (9), NeurIPS (5), ICLR (4),  IJCAI (12), ICML (2) and peer-reviewed 

journal including Nature Chemical Biology, Nature Communication, Bioinformatics (3), Cell Patterns (2), and JAMIA (4). 

Her publications receive 11294 citations, h-index 43, and i10-index 92. She also has received multiple research awards, including IMIA Yearbook on Medical 

Informatics Best paper published in 2018, and Winner of the 2016 Parkinson's Disease PPMI Data Challenge, Michael. J. Fox Foundation, 2016.

2025

• [Nature Scientific Data] Tianfan Fu, Jintai Chen, Yaojun Hu, Yingzhou Lu, Yue Wang, Xu Cao, Miao Lin, Hongxia Xu, Jian Wu, Xiao Cao, Jimeng Sun, Lucas Glass, Kexin Huang, and Marinka Zitnik, TrialBench: Multi-Modal AI-Ready Datasets for Clinical Trial Prediction, Nature Scientific Data 2025.

• [ACL 25] Aofei Chang, Le Huang, Alex James Boyd, Parminder Bhatia, Taha Kass-Hout, Cao Xiao, Fenglong Ma, Focus on What Matters: Enhancing Medical Vision-Language Models with Automatic Attention Alignment Tuning, ACL 2025.

• [KDD 25] Longchao Da, Rui Wang, Xiaojian Xu, Parminder Bhatia, Taha Kass-Hout, Hua Wei, Cao Xiao, FlanS - A Foundation Model for Free-Form Language-based Segmentation in Medical Images, KDD 2025

• [CVPR 25] Aishik Konwer, Zhijian Yang, Erhan Bas, Cao Xiao, Prateek Prasanna, Parminder Bhatia, Taha Kass-Hout, Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation, CVPR 2025

• [ICLR 25] Pengcheng Jiang, Cao Xiao, Minhao Jiang, Parminder Bhatia, Taha Kass-Hout, Jimeng Sun, Jiawei Han. Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval, ICLR 2025

• [NAACL 25] Shuyang Yu, Runxue Bao, Parminder Bhatia, Taha Kass-Hout, Jiayu Zhou, Cao Xiao. Dynamic Uncertainty Ranking: Enhancing In-Context Learning for Long-Tail Knowledge in LLMs, NAACL 2025

• [NAACL 25] Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Taha Kass-Hout, Furong Huang, Cao Xiao, Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement, NAACL 2025

• [AAAI 25] Pengcheng Jiang, Cao Xiao, Tianfan Fu, Parminder Bhatia, Taha Kass-Hout, Jimeng Sun, Jiawei Han. Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations, AAAI 2025

2024

• [NeurIPS 24] Pengcheng Jiang, Lang Cao, Cao Xiao, Parminder Bhatia, Jimeng Sun, Jiawei Han. Knowledge Graph Fine-Tuning Upon Open-World Knowledge from Large Language Models, NeurIPS 2024

• [EMNLP 24] Zhepeng Wang, Runxue Bao, Yawen Wu, Jackson Taylor, Cao Xiao, Feng Zheng, Weiwen Jiang, Shangqian Gao, Yanfu Zhang. Unlocking Memorization in Large Language Models with Dynamic Soft Prompting, EMNLP 2024 

• [EMNLP -Findings 24] Junyu Luo, Cao Xiao, Fenglong Ma. Zero-Resource Hallucination Prevention for Large Language Models, EMNLP-Findings 2024 

• [EMNLP -Findings 24] Aofei Chang, Jiaqi Wang, Han Liu, Parminder Bhatia, Cao Xiao, Ting Wang, Fenglong Ma. BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models, EMNLP-Findings 2024 

• [KDD 24] Yuan Zhong, Xiaochen Wang, Jiaqi Wang, Xiaokun Zhang, Yaqing Wang, Mengdi Huai, Cao Xiao, Fenglong Ma. Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models, KDD 2024

• [ACL 24] Xiaochen Wang, Junyu Luo, Jiaqi Wang, Yuan Zhong, Xiaokun Zhang, Yaqing Wang, Parminder Bhatia, Cao Xiao, Fenglong Ma. Unity in Diversity: Collaborative Pre-training Across Multimodal Medical Sources, ACL 2024

• [ICML 24] Mintong Kang, Zhen Lin, Jimeng Sun, Cao Xiao, Bo Li, Rob-FCP: Certifiably Byzantine-Robust Federated Conformal Prediction, ICML 2024

• [IJCAI 24] Zifeng Wang, Chufan Gao, Cao Xiao, Jimeng Sun, MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement, IJCAI 2024.

• [IJCAI 24] Jiaqi Wang , Junyu Luo, Muchao Ye, Xiaochen Wang, Yuan Zhong, Aofei Chang, Guanjie Huang, Ziyi Yin, Cao Xiao, Jimeng Sun and Fenglong Ma. Recent Advances in Predictive Modeling with Electronic Health Records, IJCAI 2024

• [NAACL 24] Lang Cao, Zifeng Wang, Cao Xiao, Jimeng Sun. PILOT: Legal Case Outcome Prediction with Case Law, NAACL 2024

• [NAACL 24] Pengcheng Jiang, Cao Xiao, Zifeng Wang, Parminder Bhatia, Jimeng Sun, Jiawei Han. TriSum: Learning Summarization Ability from Large Language Models. NAACL 2024

• [ICLR 24] Pengcheng Jiang, Cao Xiao, Adam Cross, Jimeng Sun. GraphCare: enhancing healthcare predictions with personalized knowledge graphs. ICLR 2024

• [AAAI 24] Brandon Theodorou, Cao Xiao, Jimeng Sun. ConSequence: Synthesizing Sequences for Electronic Health Record Generation" the 38th AAAI Conference on Artificial Intelligence (AAAI-24).

2023

• • • [EMNLP 23] AutoTrial: Prompting Language Models for Clinical Trial Design. Zifeng Wang, Cao Xiao, and Jimeng Sun. EMNLP 2023.

    • [Nature Communications 23] Synthesize high-dimensional longitudinal electronic health records via hierarchical autoregressive language model. Brandon Theodorou, Cao Xiao, and Jimeng Sun. Nature Communications, 2023

    • [ACM BCB 23] TREEMENT: A Tree-based Memory Network for Patient-Trial Matching. Brandon Theodorou, Cao Xiao,  Jimeng Sun. The 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2023

    • [ACM BCB 23] SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning. Zifeng Wang, Cao Xiao,  Jimeng Sun. The 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2023

    • [ACM BCB 23] FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection. Brandon Theodorou,  Lucas Glass, Cao Xiao, Jimeng Sun. The 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2023

    • [KDD 23] MedLink: De-Identified Patient Health Record Linkage. Zhenbang Wu, Cao Xiao, Jimeng Sun, The 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023.

    • [ ICML 23 ] Fast Online Value-Maximizing Prediction Sets with Conformal Cost Control. Zhen Lin, Shubhendu Trivedi, Cao Xiao, Jimeng Sun, Fortieth International Conference on Machine Learning (ICML), 2023

2022

• • • [ Nature Chemical Biology 22 ] Artificial Intelligence Foundation for Therapeutic Science. Kexin Huang,* Tianfan Fu*, Wenhao Gao*, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik, Nature Chemical Biology, 2022.

    • [NeurIPS 22] Chaoqi Yang, Cheng Qian, Navjot Singh, Cao Xiao, M Brandon Westover, Edgar Solomonik, Jimeng Sun. ATD: Augmenting CP Tensor Decomposition by Self Supervision. The Thirty-sixth Annual Conference on Neural Information Processing Systems, 2021.

    • [COLING 22] Junyu Luo, Junxian Lin, Chi Lin, Cao Xiao, Xinning Gui and Fenglong Ma. Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation. Proceedings of the 29th International Conference on Computational Linguistics (COLING 2022), OCTOBER 12-17, 2022, GYEONGJU, REPUBLIC OF KOREA.

    • [ICLR 22] Tianfan Fu, Wenhao Gao, Cao Xiao, Jacob Yasonik, Connor W Coley, Jimeng Sun. Differentiable scaffolding tree for molecular optimization.

    • [WWW 22] Junyi Gao, Cao Xiao, Lucas Glass and Jimeng Sun. PopNet: Real-Time Population-Level Disease Prediction with Data Latency. The World Wide Web Conference (WWW' 22) (acceptance rate 17.7%).

    • [Cell Patterns] Tianfan Fu, Kexin Huang, Cao Xiao, Lucas M. Glass, Jimeng Sun. HINT: Hierarchical Interaction Network for Clinical Trial Outcome Prediction. Cell Patterns, 2022 (accepted)

    • [AAAI 22] Zhen Lin, Cao Xiao, Lucas Glass, M Brandon Westover, Jimeng Sun. SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models. the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22) (acceptance rate 15%)

2021

• • • [Cell Patterns 21] Kexin Huang*, Cao Xiao*, Lucas M. Glass, Cathy W. Critchlow, Greg Gibson, and Jimeng Sun. “Machine Learning Applications for Therapeutic Tasks with Genomics Data.” Cell Patterns, 2021.

    • [NeurIPS 21] Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik. Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. The Thirty-fifth Annual Conference on Neural Information Processing Systems, 2021.

    • [KDD 21] Tianfan Fu, Cao Xiao, Cheng Qian, Lucas M Glass, Jimeng Sun. Probabilistic and Dynamic Molecule-Disease Interaction Modeling for Drug Discovery. The 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2021), Virtual,  2021.

    • [KDD 21] Chaoqi Yang, Navjot Singh, Cao Xiao, Cheng Qian, Edgar Solomonik, Jimeng Sun. MTC: Multiresolution Tensor Completion from Partial and Coarse Observations. The 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2021), Virtual,  2021.

    • [KDD 21] Fenglong Ma, Muchao Ye, Junyu Luo, Cao Xiao, Jimeng Sun. Tutorial: Advances in Mining Heterogeneous Healthcare Data, KDD, Virtual,  2021.

    • [IJCAI 21] Chaoqi Yang, Cao Xiao, Fenglong Ma, Lucas Glass, Jimeng Sun. SafeDrug: Dual Molecular Graph Encoders for Safe Drug Recommendations, The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), 2021.

    • [IJCAI 21] Chaoqi Yang, Cao Xiao, Lucas Glass, Jimeng Sun.Change Matters: Medication Change Prediction with Recurrent Residual Networks, The 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), 2021.

    • [MLHC 21] Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin, Walter Stewart, Cao Xiao, Jimeng Sun. EVA: Generating longitudinal electronic health records using conditional variational autoencoders. Machine Learning for Healthcare (MLHC' 21).

    • [CIKM 21] Muchao Ye, Suhan Cui, Yaqing Wang, Junyu Luo, Cao Xiao, Fenglong Ma. MedRetriever: Target-Driven Interpretable Health Risk Prediction via Retrieving Unstructured Medical Text, Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM' 21) (acceptance rate 20.6%).

    • [ACL-Findings 21] Junyu Luo, Cao Xiao, Lucas Glass, Jimeng Sun, Fenglong Ma. Fusion: Towards Automated ICD Coding via Feature Compression, Findings of the Association for Computational Linguistics: ACL-IJCNLP, 2021.

    • [Bioinformatics 21] Yue Yu, Kexin Huang, Chao Zhang, Lucas M Glass, Jimeng Sun, Cao Xiao. SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization, Bioinformatics 2021 (Impact factor: 5.61).

    • [MLSys 21] Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu. SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection. Proceedings of Machine Learning and Systems, 2021.

    • [ACM-BCB 21] Tianfan Fu, Cao Xiao, Kexin Huang, Lucas M Glass, Jimeng Sun. SPEAR: self-supervised post-training enhancer for molecule optimization, The 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, 2021.

    • [WWW 21] Chacha Chen, Junjie Liang, Fenglong Ma, Lucas Glass, Jimeng Sun and Cao Xiao. UNITE: Uncertainty-based Health Risk Prediction  Leveraging Multi-sourced Data, The World Wide Web Conference (WWW' 21) (acceptance rate 20.6%).

    • [WWW 21] Nghia Hoang, Shenda Hong, Cao Xiao, Bryan Low and Jimeng Sun. AID: Active Distillation Machine to Leverage Pre-Trained Black-Box Models in Private Data Settings, The World Wide Web Conference (WWW' 21) (acceptance rate 20.6%).

    • [WWW 21] Muchao Ye, Suhan Cui, Yaqing Wang, Junyu Luo, Cao Xiao and Fenglong Ma. MedPath: Augmenting Health Risk Prediction via Medical Knowledge Paths, The World Wide Web Conference (WWW' 21) (acceptance rate 20.6%).

    • [IEEE TKDE 21] Tianfan Fu, Cao Xiao, Lucas M. Glass and Jimeng Sun. MOLER: Incorporate Molecule-Level Reward to Enhance Deep Generative Model for Molecule Optimization, IEEE Transactions on Knowledge and Data Engineering, 2021 (Impact factor: 3.857).

    • [AAAI 21] Tianfan Fu, Cao Xiao, Xinhao Li, Lucas M. Glass, Jimeng Sun. MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021 (acceptance rate 21% (1692/9034))

    • [AAAI 21] Nikos Kargas, Cheng Qian, Nicholas Sidiropoulos, Cao Xiao, Lucas M. Glass, Jimeng Sun. STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021 (acceptance rate 21% (1692/9034))

    • [JAMIA 21] Junyi Gao, Rakshith Sharma, Cheng Qian, Lucas M. Glass, Jeffrey Spaeder, Justin Romberg, Jimeng Sun, and Cao Xiao. STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real-World Evidence, Journal of the American Medical Informatics Association 2021 (Impact factor: 4.29).

2020

• • [Nature Scientific Reports 20] Kexin Huang, Cao Xiao, Lucas M. Glass, Marinka Zitnik, Jimeng Sun. SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks, Scientific Reports, 2020 (Impact factor: 4.259).

  • [Bioinformatics 20] Kexin Huang, Tianfan Fu, Lucas M. Glass, Marinka Zitnik, Cao Xiao,  and Jimeng Sun. DeepPurpose: A Deep Learning Library for Drug-Target Interaction Prediction, Bioinformatics 2020 (Impact factor: 5.61).

  • [BIBM 20] Tianfan Fu, Cao Xiao, Lucas Glass and Jimeng Sun. -MOP: Molecule Optimization with -divergence, International Conference on Bioinformatics and Biomedicine (BIBM) 2020 (acceptance rate 19.4%).

  • [JAMIA 20] Zhi Qiao, Austin Bae, Cao Xiao,  Lucas Glass and Jimeng Sun. FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection, Journal of the American Medical Informatics Association 2020 (Impact factor: 4.29).

  • [IEEE BigData 20] Xiao Qin, Cao Xiao, Tengfei Ma, Tabassum Kakar, Susmitha Wunnava, Xiangnan Kong, Elke Rundensteiner, and Fei Wang. Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding, IEEE International Conference on Big Data 2020 (acceptance rate 15.5%).

  • [Bioinformatics 20] Kexin Huang, Cao Xiao,  Lucas Glass and Jimeng Sun. MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction, Bioinformatics 2020 (Impact factor: 5.61).

  • [CIKM 20] Junyu Luo, Muchao Ye, Cao Xiao, Fenglong Ma. LSAN: Modeling Long-term Dependencies and Short-term Correlations with Hierarchical Attention for Risk Prediction, The 29th ACM International Conference on Information and Knowledge Management (CIKM2020), 2020.

  • [KDD 20] Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun. COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching, The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020), 2020.

  • [KDD 20] Junyu Luo, Muchao Ye, Cao Xiao, Fenglong Ma. HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records, The 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020), 2020.

  • [IJCAI 20] Marinka Zitnik, Cao Xiao, Jimeng Sun. Tutorial: Machine Learning for Drug Discovery, the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020).

  • [Drug Safety 20] Ying Li, Antonio Jimeno Yepes, Cao Xiao. Combining Social Media and FDA Adverse Event Reporting System to Detect Adverse Drug Reactions, Drug Safety, 2020 (Impact factor: 3.526).

  • [Annals of OR 20] Zelda B Zabinsky, Pattamon Dulyakupt, Shabnam Zangeneh-Khamooshi, Cao Xiao, Pengbo Zhang, Seksan Kiatsupaibul, Joseph A Heim. Optimal collection of medical specimens and delivery to central laboratory, Annals of Operations Research, 2020 (Impact factor: 2.583).

  • [Comput. Biol. Med 20] Shenda Hong, Yuxi Zhou, Junyuan Shang, Cao Xiao, Jimeng Sun. Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review, Computers in Biology and Medicine, 2020  (Impact factor: 2.286).

  • [IEEE TKDE 20] Cao Xiao, Trong Nghia Hoang, Shenda Hong, Tengfei Ma and Jimeng Sun. CHEER: Rich Model Helps Poor Model via Knowledge Infusion, IEEE Transactions on Knowledge and Data Engineering, 2020 (Impact factor: 3.857).

  • [JAMIA 20] Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun, Dr. Agent: Clinical Predictive Model via Mimicked Second Opinions, Journal of the American Medical Informatics Association (JAMIA), 2020 (Impact factor: 4.29).

  • [WWW 20] Junyi Gao, Cao Xiao, Yasha Wang, Wen Tang, Lucas M. Glass, Jimeng Sun. StageNet: Stage-Aware Neural Networks for Health Risk Prediction, The World Wide Web Conference (WWW' 20) (acceptance rate 19%).

  • [WWW 20] Siddharth Biswal, Cao Xiao, Lucas M. Glass, Brandon Westover, and Jimeng Sun. CLARA: Clinical Report Auto-completion, The World Wide Web Conference (WWW' 20) (acceptance rate 19%).

  • [WWW 20] Rahul Daggal, Scott Freitas, Cao Xiao, Duen Horng Chau, and Jimeng Sun. REST: Robust and Efficient Neural Networks for Sleep Staging in the Wild, The World Wide Web Conference (WWW' 20) (acceptance rate 19%).

  • [WWW 20] Xingyao Zhang, Cao Xiao, Lucas M. Glass, and Jimeng Sun. DeepEnroll: Patient-Trial Matching with Deep Embedding and Entailment Prediction, The World Wide Web Conference (WWW' 20)(acceptance rate 19%).

  • [AAAI 20] Kexin Huang, Cao Xiao, Nghia Hoang, Lucas Glass and Jimeng Sun. CASTER: Predicting Drug Interaction with Chemical Substructure Representation, AAAI 2020 (acceptance rate 20.6%).

  • [AAAI 20] Tianfan Fu, Cao Xiao, and Jimeng Sun. CORE: Automatic Molecule Optimization using Copy and Refine Strategy, AAAI 2020 (acceptance rate 20.6%).

  • [AAAI 20] Siddharth Biswal, Cao Xiao, Lucas Glass, Elizabeth Milkovits, and Jimeng Sun. Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment, AAAI 2020 (acceptance rate 20.6%).

  • [AAAI 20] Limeng Cui, Siddharth Biswal, Lucas Glass, Greg Lever,  Jimeng Sun, and Cao Xiao. CONAN: Complementary Pattern Augmentation for Rare Disease Detection, AAAI 2020 (acceptance rate 20.6%).

2019

• • [ACM-BCB 19] Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma and Jimeng Sun. PEARL: Prototype Learning via Rule Lists, The 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (acceptance rate 26.1%).

  • [MLHC 19]  Siddharth Biswal, Cao Xiao, Brandon Westover, and Jimeng Sun. EEGtoText: Learning to Write Medical Reports from EEG Recordings, Machine Learning for Healthcare 2019 (acceptance rate 30.9%).

  • [MLHC 19]  Irfan Al-Hussaini , Cao Xiao, Brandon Westover, and Jimeng Sun. SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules, Machine Learning for Healthcare 2019 (acceptance rate 30.9%).

  • [IJCAI 19] Tianfan Fu, Trong Nghia Hoang,  Cao Xiao, and Jimeng Sun. DDL: Deep Dictionary Learning for Predictive Phenotyping, The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019.

  • [IJCAI 19] Junyuan Shang, Tengfei Ma, Cao Xiao, and Jimeng Sun. Pre-training of Graph Augmented Transformers for Medication Recommendation, The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019.

  • [IJCAI 19] Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li and Jimeng Sun. MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals, The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019.

  • [IJCAI 19] Shengda Hong, Cao Xiao, Tengfei Ma, Hongyan Li and Jimeng Sun. RDPD: Rich Data Helps Poor Data via Imitation, The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019.

  • [KDD 19] Fengyi Tang, Cao Xiao, Fei Wang, Jiayu Zhou, Li-wei Lehman. Retaining Privileged Information for Multi-Task Learning, The 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019) (oral paper, acceptance rate: 9.2%), 2019.

  • [KDD 19] Cao Xiao, Jimeng Sun. Tutorial: Data Mining Methods for Drug Discovery and Development, KDD, Anchorage, AK,  2019.

  • [AOR 19] Zelda Zabinsky, S. Zangeneh, Cao Xiao, Pengbo Zhang, P. Dulyakupt, Joe Heim. Optimal Collection of Medical Specimens and Delivery to Central Laboratory, Annals of Operations Research, 2019.

  • [WWW 19] Sungtae An, Cao Xiao, Walter Stewart, and Jimeng Sun. LAVA: Longitudinal Adversarial Attack on Electronic Health Records Data,  The 2019 Web Conference (WWW 2019) (acceptance rate 20%), 2019.

  • [AAAI 19] Junyuan Shang, Cao Xiao, Tengfei Ma, Hongyan Li and Jimeng Sun. GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination, The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019) (acceptance rate 16.2%), 2019.

  • [CRI 19] Ying Li, Cao Xiao. Developing a Data-driven Medication Indication Knowledge Base using a Large Scale Medical Claims Database, AMIA 2019 Informatics Summit.

  • [Nature Scientific Reports 19] Xi Zhang, Jian Liang, Cao Xiao, Yize Zhao, Harini Sarva, Claire Henchcliffe, Fei Wang. Data-Driven Subtyping of Parkinson's Disease Using Longitudinal Clinical Records: A Cohort Study, Nature Scientific Reports, 2019.

  • [IEEE Access 19] Jianqiang Li, Jingchao Sun, Lu Liu, Bo Liu, Cao Xiao, Fei Wang, Improved Maximum Margin Clustering via the Bundle Method, IEEE Access, 2019.

  • [IIE-HSE 19] Cao Xiao, Shupeng Gui, Yu Cheng, Xiaoning Qian, Shuai Huang, and Ji Liu. Learning Longitudinal Planning for Personalized Health Management from Daily Behavioral Data, IIE Transactions on Healthcare Systems Engineering, 2019.

2018

• • [Drug Safety 18] Ying Li, Cao Xiao, Katherine Shen, k. Bannout, W. Wallis and Fei Wang. A Prospective Evaluation Of MCEM Method For Drug Safety Signal Detection In Spontaneous Reporting Systems, in The International Society of Pharmacovigilance Annual Meeting 2018, Drug Safety pp, 2018.

  • [NeurIPS 18] Tengfei Ma, Jie Chen and Cao Xiao. Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders, The Thirty-second Annual Conference on Neural Information Processing Systems, 2018.

  • [NeurIPS 18] Edward Choi, Cao Xiao, Walter Stewart, and Jimeng Sun. MiME: Multilevel Medical Embedding from Electronic Health Records for Predictive Healthcare, The Thirty-second Annual Conference on Neural Information Processing Systems, 2018.

  • [ICDM 18] Inci Baytas, Cao Xiao, Fei Wang, Anil K. Jain and Jiayu Zhou. HHNE: Heterogeneous Hyper-network Embedding,  The IEEE International Conference on Data Mining series (ICDM 2018) (acceptance rate 11.08%), 2018

  • [KDD 18] Edward Choi, Cao Xiao, Jimeng Sun. Tutorial: Deep Learning for Computational Healthcare, KDD, London, UK, 2018.

  • [JAMIA 18] Cao Xiao, Edward Choi, Jimeng Sun, Opportunities and Challenges in Developing Deep Learning Models Using Electronic Health Records Data: a systematic review, Journal of the American Medical Informatics Association (JAMIA), Oct, 2018 (Impact factor: 4.29) {Editor's Choice}.

  • [BIH 18] Kin Ming Puk, Wei Xiang, Shouyi Wang, Cao Xiao, W. Art Chaovalitwongse, Tara M. Madhyastha, Thomas J. Grabowski. Uncovering Dynamic Functional Connectivity of Parkinson's Disease Using Topological Features and Sparse Group Lasso, 2018 International Conference on Brain Informatics and Health (BIH 18') .

  • [IJCAI 18] Tengfei Ma, Cao Xiao, Jiayu Zhou and Fei Wang. Drug Similarity Integration Through Multi-view Graph Auto-Encoders,  The 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate 20.4%), 2018

  • [IJCAI 18] Zhi Qiao, Shiwan Zhao, Cao Xiao, Xiang Li, Yong Qin, Fei Wang. Pairwise-ranking based Collaborative Recurrent Neural Networks for Clinical Event Prediction. The 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate 20.4%), 2018.

  • [PLOS ONE 18] Cao Xiao, Tengfei Ma, Adji Dieng, David Blei, and Fei Wang, Readmission Prediction via Deep Contextual Embedding of Clinical Concepts, PLOS ONE, 2018 (Impact factor: 2.806) (best paper for the IMIA yearbook 2019) .

  • [ICLR 18] Jie Chen, Tengfei Ma, and Cao Xiao. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling, International Conference on Learning Representations (ICLR 2018), 2018

  • [Nature Scientific Reports 18] Cao Xiao, Ying Li, Inci Baytas, Jiayu Zhou, Fei Wang. An MCEM Framework for Drug Safety Signal Detection and Combination from Heterogeneous Real World Evidence, Scientific Reports 8(1):1806., 2018 (Impact factor: 4.259).

  • [IEEE-TASE 18] Cao Xiao, Yan Jin, Ji Liu, Bo Zeng, and Shuai Huang. Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification, IEEE Transactions on Automation Science and Engineering}, Volume: 15, Issue: 3, 2018 (Impact factor: 3.667) (First runner-up for IEEE-TASE best paper of 2019).

  • [JAMIA (open) 18] Fengyi Tang, Cao Xiao, Fei Wang, Jiayu Zhou, Predictive Modeling in Urgent Care: A Comparative Study of Machine Learning Approaches, Journal of the American Medical Informatics Association Open (JAMIA Open), 2018.

  • [SDM 18] Tengfei Ma*, Cao Xiao*, and Fei Wang. Health-ATM: A Deep Architecture for Multifaceted Patient Health Record Representation and Risk Prediction, The $18$th SIAM International Conference on Data Mining (SDM 2018)} (acceptance rate 23.2%). (* equal contribution)

  • [JHIR 18] Randy Ardywibowo, Shuai Huang, Shupeng Gui, Cao Xiao, Yu Cheng, Ji Liu, Xiaoning Qian. Switching-State Dynamical Modeling of Daily Behavioral Data, Journal of Health Informatics Research, 2018. 

2017

• • [KDD 17] Inci Baytas, Cao Xiao, Xi Zhang, Fei Wang, Anil Jain, and Jiayu Zhou. Patient-subtyping via Time-aware LSTM Networks,  The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017) (Oral, acceptance rate 8.56%)

  • [IEEE-TIP 17] Weining Lu, Yu Cheng, Cao Xiao, Shiyu Chang , Shuai Huang, Bin Liang, and Thomas Huang, Unsupervised Sequential Outlier Detection with Deep Architecture,  IEEE Transactions on Image Processing, Volume: 26, Issue: 9, Sept. 2017 (Impact factor: 5.071).

  • [AMIA 17] Xi Zhang, Jian Liang, Cao Xiao, Yizhe Zhao, and Fei Wang. Subtyping Parkinson’s Disease with Recurrent Neural Network Models, AMIA 2017 Annual Symposium, 2017

  • [IEEE-TBD 17] Cao Xiao, Shouyi Wang, Leon Iasemidis, and Art Chaovalitwongse. An Adaptive Pattern Learning Framework to Personalize Online Seizure Prediction,  IEEE Transactions on Big Data, doi: 10.1109/TBDATA, 2017.

  • [SDM 17] Chao Che*, Cao Xiao*, Jian Liang, Bo Jin, Jiayu Zhou and Fei Wang. An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease, The 17th SIAM International Conference on Data Mining (SDM 2017) (acceptance rate 26%). (* equal contribution)

  • [AAAI 17] Cao Xiao, Ping Zhang, Art Chaovalitwongse, Jianying Hu and Fei Wang. Adverse Drug Reaction Prediction with Symbolic Latent Dirichlet Allocation, The 31st AAAI Conference on Artificial Intelligence (AAAI 2017) (acceptance rate 25%).

  • [AAAI 17] Bo Jin, Haoyu Yang, Cao Xiao, Ping Zhang, and Fei Wang. Multitask Dyadic Prediction and Its Application in Prediction of Adverse Drug-Drug Interaction,  The 31st AAAI Conference on Artificial Intelligence (AAAI 2017) (acceptance rate 25%) .

  • [Drug Safety 17] Cao Xiao, Ying Li, Jiayu Zhou and Fei Wang. An MCEM-MTL Framework for Drug Safety Signal Filtering and Detection in Spontaneous Reporting Systems (abstract), in The International Society of Pharmacovigilance Annual Meeting 2017, Drug Safety 40(10), 2017.

2016 and before

• • [IEEE-SMC 16] Cao Xiao and Art Chaovalitwongse. Optimization Models for Feature Selection of Decomposed Nearest Neighbor. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(2), Jan 2016, 177-184 (Impact factor: 5.131).

  • [IEEE-HMS 16] Cao Xiao, Shouyi Wang , Liying Zheng, Xudong Zhang, and Art Chaovalitwongse. A Patient-Specific Model for Predicting Tibia Soft Tissue Insertions from Bony Outlines Using a Spatial Structure Supervised Learning Framework, IEEE Transactions on Human-Machine Systems, Vol. 46 , No. 5, Oct 2016 (Impact factor: 2.563).

  • [Brain Informatics 16] Cao Xiao, Jesse Bledsoe, Shouyi Wang,  Sonya Mehta, Mageret Semrud-Clikeman, Thomas Grabowski, and Art Chaovalitwongse. An Integrated Feature Ranking and Selection Framework for ADHD Diagnosis, Brain Informatics, Apr 2016, pp 1-11.

  • [JAD 16] Jesse Bledsoe, Cao Xiao, Art Chaovalitwongse, Sonya Mehta, Thomas Grabowski, Mageret Semrud-Clikeman, Steven Pliszka, and David Breiger, Diagnostic Classification of Attention-Deficit/Hyperactivity Disorder vs. Control: Support Vector Machine Classification Using Brief Neuropsychological Assessment, Journal of Attention Disorders, 2016 (Impact factor: 3.668) 

  • [BIH 16] Shouyi Wang, Cao Xiao, Jeff Tsai, Art Chaovalitwongse. A Novel Mutual-Information Guided Sparse Feature Selection Approach for Epilepsy Diagnosis Using Interictal EEG Signals, 2016 International Conference on Brain Informatics and Health (BIH 16') (best student paper runner-up) .

  • [AAAI 16] Shouyi Wang, Kim Kam, Cao Xiao and Art Chaovalitwongse. An Efficient Orthogonal-Polynomial-Based Variant Nearest Neighbor Approach for Highly Nonlinear and Complex Time Series Prediction. In Proceedings of The 30th AAAI Conference on Artificial Intelligence (AAAI 2016) (acceptance rate 26%).

  • [AISec 15] Cao Xiao, David Freeman and Ted Hwa.  Detecting Clusters of Fake Accounts in Online Social Networks. In Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security (AISec 2015).