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Kun (Amanda) Bu

Kun (Amanda) Bu

Assistant Professor of Data Science
Seaver College
RAC 131
310.506.4831
CV

Biography

Dr. Kun (Amanda) Bu is an Assistant Professor of Data Science. She earned her Ph.D. in Statistics from the University of South Florida, where she also served as a Postdoctoral Scholar. Her research focuses on statistical learning, and data science, with applications in finance, pharmaceutical data mining, and natural language processing. She is passionate about helping students discover the power of statistics, computing, and data science through hands-on learning and real-world applications.

Education

  • Ph.D. in Statistics, University of South Florida

  • M.A. in Statistics, University of South Florida

  • M.S. in Finance, University of Tampa

  • B.A. in Human Resource Management, East Tennessee State University

 

  • Financial NeQTL: A Genomics-Inspired Bayesian Approach to Market Structure Inference, Bu, K. and Kim, J., manuscript completed, under review, 2026.
  • Cardiovascular Risks of COVID-19 Therapeutics: Integrated Analysis of FAERS, Electronic Health Records, and Transcriptomics, Zhu, X., Kuppa, S. A., Umeukeje, G., Morris, R., Bui, L., Bu, K., Zhang, J., Wei, J. and Cheng, F., Pharmaceuticals, 2026.
  • Integration of Image Segmentation with Classical
  • Optimization Theories of Statistics, Kim, J., Jang, J. and Bu, K., JSM Proceedings, 2025.
  • The Association Between Dexmedetomidine and Bradycardia, Morris, R., Kuppa, S., Zhu, X., Bu, K., Han, W. and Cheng, F., Genes, 2025.
  • The Association Between Statin Drugs and Rhabdomyolysis, Morris, R., Bu, K., Han, W., Wood, S., Velez, P., Ward, J., Crescitelli, A. and Martin, M., Genes, 2025.
  • Advancing Text Summarization and Classification: Deep Insights from Transformer-based Statistical Learning, Bu, K., University of South Florida, 2024.
  • Analysis of Literature-Derived Duplicate Records in the FDA Adverse Event Reporting System database, Han, W., Morris, R., Bu, K.*, Zhu, T., Huang, H. and Cheng, F., Canadian Journal of Physiology and Pharmacology, 2024.
  • Comparing the risk of deep vein thrombosis of two combined oral contraceptives, Stalas, J., Morris, R., Bu, K.*, et al., Heliyon, 2024.
  • Comparative Analysis of Sentiment in Original and Summarized Tweets, Bu, K. and Kandethody, R., AIBD, 2024.
  • Exploring Drug-drug Interaction Information from PubMed using Association Rules, Bu, K., Han, W., Morris, R.* and Cheng, F., Chemistry & Biodiversity, 2023.
  • Deception Detection using Random Forest-based Ensemble Learning, Bu, K. and Kandethody, R., ICSTA, 2023.
  • Dysphagia Risk in Patients Prescribed Rivastigmine, Bu, K., Patel, D., Morris, R.*, Han, W., Umeukeje, G., Zhu, T. and Cheng, F., Journal of Alzheimer’s Disease, 2022.
  • The Association Between Use of Rivastigmine and Pneumonia, Morris, R., Umeukeje, G., Bu, K.* and Cheng, F., Journal of Alzheimer’s Disease, 2021.
  • Bradycardia due to Donepezil in Adults, Morris, R., Luboff, H., Jose, R. P., Eckhoff, K., Bu, K., et al., Journal of Alzheimer’s Disease, 2021.
  • Bayesian Reliability Analysis for Optical Media Using Accelerated Degradation Test Data, Bu, K., University of South Florida, 2020.
  • Featured in The Scientist Postdoc Portraits. The Scientist, 2026
  • Innovative Research Award: 35th International Research Awards on Cardiology and Cardiovascular Medicine (Scifax), 2026
  • Editor's Choice Article: Canadian Journal of Physiology and Pharmacology, for the publication on duplicate reports in FAERS, 2025
  • Tharp Endowed Award in Excellent Research and Teaching: University of South Florida, 2024
  • IBM Data Science Professional Certificate: IBM, 2024
  • Top 5% (8th/148) in the NIH DREAM Challenge, 2022
  • Kim, J., Jang, S., & Bu, K. (2025). MRI Image Segmentation: Methods and Evaluation. Joint Statistical Meetings (JSM).
  • Bu, K. (2024). Advancing Classification: Deep Insights from Transformer-Based Statistical Learning. Florida Section of the Mathematical Association of America (FL-MAA) Annual Meeting, Florida Gulf Coast University.
  • Zhu, X., Bu, K., et al. (2023). Pharmacovigilance Signal Detection Using FAERS and Biomedical Literature. International Conference on Intelligent Biology and Medicine (ICIBM).
  • Invited & Departmental Talks
  • Bu, K. (2024). MRI Image Segmentation: Methods and Evaluation. USF Postdoctoral Scholar Lightning Talks.
  • 2026 – U.S. Department of Education SEED Grant Proposal (Under Review)
  • Project: ALLIED Hub: Supporting Educational Excellence through Data-Driven Implementation Science
  • Role: Contributed AI methodology, statistical modeling, implementation evaluation metrics, and data visualization/dashboard design for a multi-institutional collaborative proposal led by Drexel University.
  • 2023 – NIH R03 (Resubmission)
  • Project: Identification of adverse drug events and possible drug–drug interactions of remdesivir as well as the molecular mechanism
  • Role: Contributed statistical analysis, pharmacovigilance methodology, adverse event detection, and computational data analysis in support of the NIH R03 resubmission.
  • 2022 – NIH R03
  • Project: Identification of adverse drug events and possible drug–drug interactions of remdesivir as well as the molecular mechanism
  • Role: Contributed statistical modeling, pharmacovigilance analyses, and computational methods for identifying adverse drug events and potential drug–drug interactions.

Topics

  • Statistical Learning
  • Bayesian Data Analysis
  • Human-Centered AI
  • Machine Learning
  • Natural Language Processing
  • Pharmaceutical Data Mining & Pharmacovigilance
  • Computational Statistics

Courses

  • Programming Principles II
  • Introduction to Machine Learning
  • Statistical Methods I
  • Introductory Statistics I & II
  • Categorical Data Analysis
  • Introduction to Mathematical Statistics