Ping Wang

• PhD (2021) Virginia Tech (Computer Science)

• 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)

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

Conference Proceeding

1. 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.
2. 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).
3. 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).
4. 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).
5. 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).
6. 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

1. 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).
2. 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.
3. Wang, P. N.; Shi, T.; Reddy, C. K. (2020). Tensor-based Temporal Multi-Task Survival Analysis. IEEE Transactions on Knowledge and Data Engineering. IEEE.
4. 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.
5. 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.
6. 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.