Xiao Luo, Ph.D.
Associate Professor of Computer Science
Associate Professor of Electrical and Computer Engineering
| Department |
Computer Science, Electrical and Computer Engineering |
| Office Location |
Caruth Hall 473 |
| Website |
|
Connect
Dr. Xiao Luo earned her Ph.D. in Computer Science with a concentration in natural language processing, information retrieval, and artificial intelligence. She is currently an Associate Professor with joint appointments in Computer Science and Electrical & Computer Engineering. Her research centers on developing generative AI models, natural language processing, and machine learning methods, with applications in healthcare, security, business, and education. Dr. Luo is particularly committed to developing novel multimodal AI systems that enhance healthcare delivery, support personalized education, or improve business management. She has authored more than 125 journal articles, conference papers, and abstracts, and her work has been recognized with Best Paper Awards at the ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB) and the International Conference on Human-Computer Interaction (HCI). She collaborates extensively with multidisciplinary teams across institutions on federally funded projects supported by the NIH, NSF, and industry partners.
Education
Ph.D. in Computer Science, Bachelor of Computer EngineeringTeaching
CS 1340 Introduction to Computing ConceptsResearch
- Large Language Models
- Multimodal AI
- AI for Health
- AI for Business
- Biomedical Informatics
- Health Data Science
Publications
- Xiao Luo, Le Zhou, Kathleen Adelgais, Zhan Zhang, “Assessing the Effectiveness of Automatic Speech Recognition Technology in Emergency Medicine Settings: A Comparative Study of Four AI-powered Engines”, Journal of Healthcare Informatics Research, 2025
- Xiao Luo, Fattah Muhammad Tahabi, Tressica Marc, Laura Ann Haunert, Susan Storey, “Zero-shot learning to extract assessment criteria and medical services from the preventive healthcare guidelines using Large Language Models”, Journal of the American Medical Informatics Association, 2024
- Egil Karlsen, Xiao Luo, Nur Zincir-Heywood, Malcolm Heywood, “Benchmarking Large Language Models for Log Analysis, Security, and Interpretation”, Journal of Network and Systems Management, 2024
- Md. Ahsanul Kabir, Tyler Phillips, Xiao Luo, Mohammad Al Hasan, “ASPER: Attention-based Approach to Extract Syntactic Patterns denoting Semantic Relations in Sentential Context”, Natural Language Processing Journal, 2023
- Neel Jitesh Bhate, Ansh Mittal, Zhe He, Xiao Luo, “Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model”, IEEE International Conference on Big Data, 2023
- Xiao Luo, Priyanka Gandhi, Susan Storey, and Kun Huang, “A Deep Language Model for Symptom Extraction from Clinical Text and Its Application to Extract COVID-19 symptoms from Social Media”, IEEE Journal of Biomedical And Health Informatics, 2022
- Haoran Ding and Xiao Luo, “AGRank: Augmented Graph-based Unsupervised Keyphrase Extraction”, Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and International Joint Conference on Natural Language Processing (AACL-IJCNLP), 2022
- Taotao Jing, Haifeng Xia, Renran Tian, Haoran Ding, Xiao Luo, Joshua Domeyer, Rini Sherony, Zhengming Ding, “InAction: Interpretable Action Decision Making for Autonomous Driving”, European Conference on Computer Vision (ECCV), 2022
- Xiao Luo, Priyanka Gandhi, Susan Storey, Zuoyi Zhang, Zhi Han, and Kun Huang, “A Novel Framework to Analyze the Associations between Symptoms and Cancer Patient Attributes Post Chemotherapy using EHR data”, IEEE Journal of Biomedical and Health Informatics, 2021
- Amirreza Salamat, Xiao Luo, Ali Jafari, “HeteroGraphRec: A Heterogeneous Graph-Based Neural Networks for Social Recommendations”, Knowledge-Based Systems, 2021
- Haoran Ding, Xiao Luo, “AttentionRank: Unsupervised keyphrase Extraction using Self and Cross Attentions”, Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
- Priyanka Gandhi, Xiao Luo, Susan Storey, Zuoyi Zhang, Zhi Han, and Kun Huang, “Identifying Symptom Clusters in Breast Cancer and Colorectal Cancer Patients using EHR Data”, ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) (Best Paper Award), 2019
- Priyanka Gandhi, Xiao Luo, Renran Tian, “Modeling Vehicle-Pedestrian Encountering Risks in the Natural Driving Environment using Machine Learning Algorithms”, International Conference on Human-Computer Interaction (HCI) (Best Paper Award), 2019
Honors and Awards
- Trustees Teaching Award, Indiana University Indianapolis (2021)
- Best Paper Award, ACM BCB conference (2019)
- Best Paper Award, HCI conference (2019)
