
Ping Wang
Assistant Professor
Charles V. Schaefer, Jr. School of Engineering and Science
Department of Computer Science
Education
- PhD (2021) Virginia Tech (Computer Science)
Research
Machine learning
Information retrieval
Knowledge discovery
Human-centered AI
Healthcare informatics
Information retrieval
Knowledge discovery
Human-centered AI
Healthcare informatics
General Information
Ping Wang is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology and an affiliated member of The Stevens Institute for Artificial Intelligence (SIAI). She received her Ph.D. from Virginia Tech under the supervision of Dr. Chandan K. Reddy in 2021. Her primary research interests are in the broad area of data mining and machine learning, with a particular focus on healthcare analytics, including clinical question answering, information extraction, graph mining, and survival analysis. She has published papers in leading conferences (e.g., WWW, CIKM, and AAAI) and high-impact journals (e.g., ACM Computing Surveys and IEEE TKDE). She received the NSF CRII award in 2023 and the Amazon Research Award in 2025 to explore reasoning augmented searching on NoSQL databases. She was recognized as the “Research PhD Student of the Year” (one per year) in the Department of Computer Science at Virginia Tech in 2021.
Experience
Pacific Northwest National Laboratory, Research Intern
Virginia Tech, Graduate Research Assistant
Virginia Tech, Graduate Research Assistant
Institutional Service
- SES Committee on Evaluation of Teaching Effectiveness Member
- CS Strategic Planning Commitee Member
- CS Tenure-Track Faculty Searching Committee Member
- CS Graduate Advising Member
Professional Service
- 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)
Appointments
Assistant Professor, Department of Computer Science, Stevens Institute of Technology, 2021 - present
Professional Societies
- ACM – Association for Computing Machinery (ACM) Member Member
- IEEE – The Institute of Electrical and Electronics Engineers (IEEE) Member Member
Grants, Contracts and Funds
NSF CRII: III: Towards Reasoning Augmented Searching for Domain-Specific Knowledge Screening, 06/2023.
Seed grant, Teaching Learning Center, Stevens Institute of Technology, 04/2024
Seed grant, Teaching Learning Center, Stevens Institute of Technology, 04/2024
Selected Publications
Conference Proceeding
- Sood, P.; He, C.; Gupta, D.; Ning, Y.; Wang, P. (2024). Understanding Student Sentiment on Mental Health Support in Colleges Using Large Language Models. Proceedings of the 2024 IEEE International Conference on Big Data. IEEE BigData.
https://www.computer.org/csdl/proceedings-article/bigdata/2024/10826043/23ykBz54h6U. - 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.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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).
- 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).
- 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
- 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. - 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.
- 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.
- Wang, P.; Shi, T.; Reddy, C. K. (2020). Tensor-based Temporal Multi-Task Survival Analysis. IEEE Transactions on Knowledge and Data Engineering. IEEE.
- 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.
Courses
CS 559 Machine Learning
CS 584 Natural Language Processing
CS 584 Natural Language Processing