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Anthony Rios, Ph.D.

Assistant Professor, Information Systems and Cybersecurity

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Bio

Anthony Rios, Associate Professor in the Department of Information Systems and Cybersecurity, serves as the Founding Director of the Center for Data Science. A recipient of the prestigious NSF CAREER Award, Dr. Rios brings nationally recognized expertise in artificial intelligence, health informatics, natural language processing, and ethical data use. His interdisciplinary leadership has helped establish key partnerships and student-focused initiatives that connect research to real-world applications.

Dr. Anthony Rios is currently an Assistant Professor in the Department of Information Systems and Cyber Security at The University of Texas at San Antonio. Dr. Rios received his Ph.D. in Computer Science from the University of Kentucky in 2018 and his B.S. in Computer Science from Georgetown College in 2011.

His broad multidisciplinary research interests include biomedical and social applications involving machine learning and natural language processing (NLP). He has published numerous refereed technical papers in prestigious venues in NLP and biomedical informatics, including EMNLP, NAACL, AMIA, JAMIA, and Bioinformatics. Dr. Rios also received a distinguished poster finalist award at AMIA 2014 and a best paper finalist award in the best technical paper category at ICHI 2015.

Research Interests

  • Biomedical informatics
  • Computational social science
  • Natural language processing
  • Machine learning

Degrees

  • Ph.D. University of Kentucky
  • B.S. Georgetown College

Publications

  • “Generalizing Biomedical Relation Classification with Neural Adversarial Domain Adaptation,” with Ramakanth Kavuluru, Bioinformatics, Vol. 1, No. 9, 2018.
  • “EMR Coding with Semi-Parametric Multi-Head Matching Networks,” with Ramakanth Kavuluru, Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Volume 1, Vol. 1, 2018, pp. 2081-2091.
  • “Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces,” with Ramakanth Kavuluru, Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018.
  • “Ordinal Convolutional Neural Networks for Predicting RDoC Positive Valence Psychiatric Symptom Severity Scores,” with Ramakanth Kavuluru, Journal of Biomedical Informatics, Vol. 75, 2017, pp. S85-S93.
  • “An Empirical Evaluation of Supervised Learning Approaches in Assigning Diagnosis Codes to Electronic Medical Records,” with Ramakanth Kavuluru and Yuan Lu, Artificial Intelligence in Medicine, Vol. 65, No. 2, 2015, pp.155-166.