Bio

PhD, Purdue 1994

Aidong Zhang is a William Wulf Faculty Fellow and Professor of Computer Science and Biomedical Engineering in the School of Engineering and Applied Sciences at University of Virginia. She is also affiliated with the Data Science Institute at University of Virginia. Her research interests focus on data mining/data science, machine learning, bioinformatics and health informatics.

Awards

  • ACM Fellow 2017
  • SUNY Distinguished Professor 2014
  • UB Distinguished Professor 2012
  • IEEE Fellow 2009
  • National Science Foundation CAREER Award 1998

Research Interests

  • Data Mining
  • Data Science
  • Machine Learning
  • Bioinformatics
  • Health Informatics

Selected Publications

  • Semi-supervised Few-shot Learning for Disease Type Prediction, the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, January 27 – February 1, 2019. Tianle Ma and Aidong Zhang
  • Representation Learning for Treatment Effect Estimation from Observational Data, Thirty-second Conference on Neural Information Processing Systems (NIPS2018), Montréal, Canada, December 3-8, 2018. Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang
  • Concepts-Bridges: Uncovering Conceptual Bridges Based on Biomedical Concept Evolution, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, August 19-23, 2018. Kishlay Jha, Guangxu Xun, Yaqing Wang, Vishrawas Gopalakrishnan, and Aidong Zhang
  • Metric Learning from Probabilistic Labels, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2018), London, UK, August 19-23, 2018. Mengdi Huai, Chenglin Miao, Yaliang Li, Qiuling Suo, Lu Su, and Aidong Zhang
  • Multi-task Sparse Metric Learning on Measuring Patient Similarity Progression, the 2018 IEEE International Conference on Data Mining (ICDM'18), Singapore, November 17-20, 2018. Qiuling Suo, Weida Zhong, Fenglong Ma, Ye Yuan, Mengdi Huai, and Aidong Zhang
  • MuVAN: A Multi-view Attention Network for Multivariate Temporal Data, the 2018 IEEE International Conference on Data Mining (ICDM'18), Singapore, November 17-20, 2018. Ye Yuan, Guangxu Xun, Fenglong Ma, Yaqing Wang, Nan Du, Kebin Jia, Lu Su, and Aidong Zhang
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