Ping Wang

• PhD (2021) Virginia Tech (Computer Science)

• SES Committee on Evaluation of Teaching Effectiveness Member
• CS Strategic Planning Commitee Member
• CS Tenure-Track Faculty Searching Committee Member
• CS Graduate Advising Member

• ACL 2024 Program Commitee Member
• Transactions on Neural Networks and Learning Systems (TNNLS) Reviewer
• NAACL 2024 Program Committee Member
• COLING 2024 COLING 2024 Program Committee Member
• AAAI 2024 AAAI 2024 Program Committee Member
• EMNLP 2023 Program Commitee Member
• Journal of Machine Learning Research Reviewer
• Journal of Machine Learning Research (JMLR) Reviewer
• AMIA Annual Symposium 2023 Program Committee Member
• Association for Computational Linguistics (ACL) 2023 Program Committee Member
• NSF Panelist 2023
• AAAI 2023 Program Committee Member
• Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Reviewer
• Transactions on Neural Networks and Learning Systems (TNNLS) Reviewer
• COLING 2022 Area Chair
• Transactions on Knowledge and Data Engineering (TKDE) Reviewer
• Reviewer for ACM Transactions on Knowledge Discovery from Data (TKDD)
• Reviewer for ACM Computing Surveys (CSUR)

• ACM – Association for Computing Machinery (ACM) Member Member
• IEEE – The Institute of Electrical and Electronics Engineers (IEEE) Member Member

Conference Proceeding

1. Lu, C.; Reddy, C. K.; Wang, P.; Ning, Y. (2023). Towards Semi-Structured Automatic ICD Coding via Tree-based Contrastive Learning. Proceedings of the 37th Conference on Neural Information Processing Systems. NeurIPS.
2. Zhang, W.; Zeng, K.; Yang, X.; Shi, T.; Wang, P. (2023). Text-to-ESQ: A Two-Stage Controllable Approach for Efficient Retrieval of Vaccine Adverse Events from NoSQL Database. In Proceedings of the ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB). In Proceedings of the ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (BCB) 2023.
3. Li, T.; Wang, P.; Shi, T.; Bian, Y.; Esakia, A.. Task as Context: A Sensemaking Perspective on Annotating Inter-Dependent Event Attributes with Non-Experts. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP). In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP) 2023.
4. Zhang, W.; Ingale, B.; Shabir, H.; Li, T.; Shi, T.; Wang, P. (2023). Event Detection Explorer: An Interactive Tool for Event Detection Exploration. ACM: In Proceedings of the ACM Conference on Intelligent User Interfaces (IUI).
5. Li, T.; Wang, P.; Shi, T.; Esakia, A. (2022). Exploring the Impact of Sub-Task Inter-Dependency on Crowdsourced Event Annotation. AAAI: The Tenth AAAI Conference on Human Computation and Crowdsourcing.
6. Wang, P.; Shi, T.; Agarwal, K.; Choudhury, S.; Reddy, C. K. (2022). Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes. ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
7. Wang, P.; Agarwal, K.; Ham, C.; Choudhury, S.; Reddy, C. K. (2021). Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks. Proceedings of the Web Conference 2021 (pp. 2946--2957).
8. Shi, T.; Li, L.; Wang, P.; Reddy, C. K. (2020). A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
9. Wang, P.; Shi, T.; Reddy, C. K. (2020). Text-to-sql generation for question answering on electronic medical records. Proceedings of The Web Conference 2020 (pp. 350--361).

Journal Article

1. Lu, C.; Reddy, C. K.; Wang, P.; Nie, D.; Ning, Y. (2023). Multi-Label Clinical Time-Series Generation via Conditional GAN. IEEE Transactions on Knowledge and Data Engineering. IEEE.
   https://ieeexplore.ieee.org/abstract/document/10236560.
2. Shi, T.; Zhang, X.; Wang, P.; Reddy, C. K. (2021). Corpus-level and Concept-based Explanations for Interpretable Document Classification. ACM Transactions on Knowledge Discovery from Data (TKDD). ACM.
3. Shi, T.; Wang, P.; Reddy, C. K. (2020). Deliberate Self-Attention Network with Uncertainty Estimation for Multi-Aspect Review Rating Prediction. arXiv preprint arXiv:2009.09112.
4. Wang, P.; Shi, T.; Reddy, C. K. (2020). Tensor-based Temporal Multi-Task Survival Analysis. IEEE Transactions on Knowledge and Data Engineering. IEEE.
5. Wang, P.; Li, Y.; Reddy, C. K. (2019). Machine learning for survival analysis: A survey. ACM Computing Surveys (CSUR) (6 ed., vol. 51, pp. 1--36). ACM New York, NY, USA.