
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
Natural language processing
Information retrieval and knowledge discovery
Healthcare informatics
Natural language processing
Information retrieval and knowledge discovery
Healthcare informatics
Professional Service
- AAAI 2023 Program Committee Member
- EMNLP 2022 Program Committee Member
- Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Reviewer
- AACL 2022 Program Committee Member
- Transactions on Neural Networks and Learning Systems (TNNLS) Reviewer
- CIKM 2022 Program Committee Member
- COLING 2022 Area Chair
- AMIA Annual Symposium 2022 Program Committee Member
- NSF Panelist 2022
- 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
Selected Publications
Conference Proceeding
- Wang, P. N.; 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. N.; 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. N.; 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. N.; 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).
- Shi, T.; Wang, P. N.; Reddy, C. K. (2019). LeafNATS: An open-source toolkit and live demo system for neural abstractive text summarization. Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL).
- Wang, P. N.; Padthe, K. K.; Vinzamuri, B.; Reddy, C. K. (2016). Crisp: Consensus regularized selection based prediction. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (pp. 1019--1028).
Journal Article
- Shi, T.; Zhang, X.; Wang, P. N.; Reddy, C. K. (2020). A Concept-based Abstraction-Aggregation Deep Neural Network for Interpretable Document Classification. ACM Transactions on Knowledge Discovery from Data (TKDD).
- Shi, T.; Wang, P. N.; Reddy, C. K. (2020). Deliberate Self-Attention Network with Uncertainty Estimation for Multi-Aspect Review Rating Prediction. arXiv preprint arXiv:2009.09112.
- Wang, P. N.; Shi, T.; Reddy, C. K. (2020). Tensor-based Temporal Multi-Task Survival Analysis. IEEE Transactions on Knowledge and Data Engineering. IEEE.
- Wang, P. N.; 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.
- Fard, M. J.; Wang, P. N.; Chawla, S.; Reddy, C. K. (2016). A bayesian perspective on early stage event prediction in longitudinal data. IEEE Transactions on Knowledge and Data Engineering (12 ed., vol. 28, pp. 3126--3139). IEEE.
- Shi, T.; Wang, P. N. (2016). GPView: A program for wave function analysis and visualization. Journal of Molecular Graphics and Modelling (vol. 70, pp. 305--314). Elsevier.
Courses
CS 559 Machine Learning: Fall 2021, Spring 2022