Education

• PhD., Information Sciences, University of Pittsburgh
• M.S., Information Sciences, University of Pittsburgh
• B.B.A, Information Management, National Yunlin University

Experiences

• Associate Professor, National Sun Yat-sen University, 2022/02 - present
• Assistant Professor, National Sun Yat-sen University, 2015/02 - 2022/01
• Senior Data Analyst, Department of Health Policy and Management, University of Pittsburgh
• Senior Programmer, Division of Geriatric Medicine, University of Pittsburgh

Award & Honors

• 傑出校友,雲林科技大學管理學院 2020
• 逸仙新進管理學者獎, 中山大學管理學院, 2016
• Recognition of Services, University of Pittsburgh School of Medicine, 2014
• SAS Certified Statistical Business Analyst, 2013
• Microsoft Certified Technology Specialist, 2009
• SAS Certified Base Programmer, 2007
• Sun Certified Programmer for the Java 2, 2004
• Linux Professional Institute Certification, 2003

Journal Articles

1. S.-Y. Chien, S.-F. Chao, Y. Kang, C. Hsu, M.-H. Yu, and C.-T. Ku,, Understanding Predictive Factors of Dementia for Older Adults: A Machine Learning Approach for Modeling Dementia Influencers, International Journal of Human-Computer Studies, Vol.165, 2022
2. Y. Kang, S.-T. Huang, and P.-H. Wu, Detection of Drug–Drug and Drug–Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests, SN Computer Science, Vol.2, No.4, 2021, pp.299 (Artificial Intelligence for HealthCare, Springer Nature)
3. SM Altawalbeh, CT Thorpe, JC Zgibor, S Kane-Gill, Y Kang, JM Thorpe, Economic Burden Associated with Receiving Inhaled Corticosteroids with Leukotriene Receptor Antagonists or Long-Acting Beta Agonists as Combination Therapy in Older Adults, Journal of managed care & specialty pharmacy, Vol.24, No.5, 2018, pp.478-486
4. C. T Thorpe, N. R. Fowler, K. Harrigan, X. Zhao, Y. Kang, J. T. Hanlon, W. F Gellad, L. J. Schleiden, J. M Thorpe, Racial and Ethnic Differences in Initiation and Discontinuation of Antidementia Drugs by Medicare Beneficiaries, Journal of the American Geriatrics Society, 2016
5. SM Altawalbeh, CT Thorpe, JC Zgibor, S Kane‐Gill, Y Kang, JM Thorpe, Antileukotriene Agents Versus Long‐Acting Beta‐Agonists in Older Adults with Persistent Asthma: A Comparison of Add‐On Therapies, Journal of the American Geriatrics Society, 2016
6. H. Degenholtz, M. Park, Y. Kang, P. Nadash, Variations Among Medicare Beneficiaries Living in Different Settings: Demographics, Health Status, and Service Use., Research on aging, 2015
7. Y. Kang, V. Zadorozhny, Process Monitoring using Maximum Sequence Divergence, Knowledge and Information Systems (KAIS), Vol.48, 2015, pp.81-109
8. H. Degenholtz, Y. Kang, S. Hardy, Chronic Disease and Disability: Primary Care Can Moderate Decline in Physical Function Over Time, Gerontologist, No.53, 2013
9. H. Degenholtz, S. Hardy, P. Nadash, Y. Kang, Use and Cost of Health Care Services for Medicare Beneficiaries in Different Types of Housing, Gerontologist, No.53, 2013
10. H. Degenholtz, S. Hardy, Y. Kang, Chronic Disease and Disability: Longitudinal Analysis of MCBS Data, Gerontologist, No.52, 2012
11. S. Hardy, Y. Kang, S. Studenski, H. Degenholtz, Ability to walk 1/4 mile predicts subsequent disability, mortality, and health care costs, Journal of General Internal Medicine, No.2, 2011

Conference Proceedings

1. Chan Hsu, Chan-Tung Ku, Yuwen Wang, Minchen Hsieh, Jun-Ting Wu, Yunhsiang Hsieh, PoFeng Chang, Yimin Lu, Yihuang Kang, A Teacher-Student Knowledge Distillation Framework for Enhanced Detection of Anomalous User Activity, IEEE 24th International Conference on Information Reuse and Integration for Data Science, Bellevue, WA, USA , 4~ 6 2023
2. Chan Hsu, Wei-Chun Huang, Jun-Ting Wu, Chih-Yuan Li, Yihuang Kang, Toward Transparent Sequence Models with Model-Based Tree Markov Model, 2023 IEEE 6th International Conference on Multimedia Information Processing and Retrieval, Singapore, ~ 2023
3. Y. Kang, Y.-W. Chiu, M.-Y. Lin, F. Su, and S.-T. Huang, Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning, 2021 IEEE 22st International Conference on Information Reuse and Integration for Data Science (IEEE Workshop on AI for HealthCare), Virtual Conference, 2021, pp.342-347 file
4. B. Kuo, Y. Kang, P. Wu, S.-T. Huang, Y. Huang, Discovering Drug-Drug and Drug-Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests, 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IEEE Workshop on AI for HealthCare), Virtual Conference, 2020, pp.385-390
5. Y Kang, IL Cheng, W Mao, B Kuo, PJ Lee, Towards Interpretable Deep Extreme Multi-label Learning, IEEE 20th International Conference on Information Reuse and Integration for Data Science, Los Angeles, CA, USA, 2019 file
6. Y. Kang, KP Lin, IL Cheng, Topic Diffusion Discovery based on Sparseness-constrained Non-negative Matrix Factorization, IEEE 19th International Conference on Information Reuse and Integration for Data Science, Salt Lake City, Utah, USA, 2018 file
7. IL Cheng, SW Chew, Y. Kang, W. Chang, NS Chen, Exploring the Difference in Brain Activities under Three Distinct Tasks: Listening to Music, Gaming, and Learning, 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT), Austin, Texas, USA , 2016
8. Y. Kang, V. Zadorozhny, Process Discovery using Classification Tree Hidden Semi-Markov Model, 2016 IEEE International Conference on Information Reuse and Integration (IRI-DIM), 2016, pp. 361–368, Pittsburgh, PA, 2016 file

National Science Council Projects

1. Accelerating Machine Learning with Expert-in-the-loop: An Application of Precision Dosing, 主持人, 2021-8-1-2022-7-31
2. Towards Fair, Accountable, and Transparent Intelligent Applications: Learning Explainable Multimodal Representation, 主持人, 2020-8-1-2021-7-31
3. Towards Fair, Accountable, and Transparent Intelligent Applications: Learning Explainable Extreme Multi-label Representation, 主持人, 2019-8-1-2020-7-31
4. Towards Fair, Accountable, and Transparent Intelligent Applications: Using Deep Rule Forests, 主持人, 2018-8-1-2019-7-31
5. Emerging Topic Discovery based on Sparseness-constrained Non-negative Matrix Factorization, 主持人, 2017-8-1-2018-7-31
6. Using Distributed Rule-integrated Tree Probabilistic Process Model–Process Discovery from Big Data, 主持人, 2016-8-1-2017-7-31
7. Applying Big Data Analytics to Promote Labor Income, 共同主持人, 2016-6-1-2017-5-31
8. Using Tree-based Probabilistic Process Models—Frequent Process Discovery from Large Healthcare Databases , 主持人, 2015-9-1-2016-8-31

Others

1. 使用者帳號行為異常偵測模型
   -日月光半導體製造股份有限公司委托, 主持人, 2022-9-1-2023-8-31
2. 具備動態資源配置之 MLOps 平台
   -聯華電子股份有限公司委托, 主持人, 2021-7-1-2022-6-30
3. Intelligent Information System of Whole Disease Modeling for Diabetes Care and Policy Evaluation
   -The National Health Research Institutes (NHRI) 委托, 共同主持人, 2018-1-1-2021-12-31
4. Developing Unified Analytics Platforms
   -United Microelectronics Corporation委托, 主持人, 2018-7-1-2020-12-31
5. 消費客群影像辨識模型開發與設計
   -協同數位股份有限公司委托, 主持人, 2019-1--2019-11-
6. The association between drug-drug interactions and cardiovascular events using Tree-based Hidden Semi-Markov Models
   -國立中山大學與高雄醫學大學合作研究計畫委托, 共同主持人, 2017-1-1-2017-12-31
7. Discovering drug-drug interactions induced acute kidney injury using massive data mining techniques
   -NSYSU-KMU Joint Research Project委托, 共同主持人, 2016-1-2-2016-12-31

Undergraduate Program

Graduate Program

Ph.D. Program

Part time MBA

Part time MBA(EC)