Jake Luo, PhD
Associate Professor
Department of Health Informatics and Administration
Department of Computer Science
University of Wisconsin-Milwaukee
Email: JakeLuo [at] uwm.edu
Adjunct Professor
Clinical & Transnational Science Institute of SE WI
Medical College of Wisconsin
Email: zluo [at] mcw.edu
Academic Administrative Services
I am the Director of the Center for Health System Solutions at UWM.
I also serve as the Director of the Health Care Informatics graduate program at the HIA department.
For more information, please see corresponding web site.
Research Topic Areas:
- Big Data and Predictive Analysis
- Natural Language Processing
- Patient-centered Health App Development
- Text Mining and Information Extraction
- Artificial Intelligence and machine learning
Honors & Awards
- CETL Teacher Excellence Award (2023). This award was nominated by students.
- Dean’s Research Award (2019)
- Outstanding Clinical Research Informatics Paper Award Nominated (2014) AMIA.
- Outstanding Reviewer Award (2013) MedInfo 2013.
- Top hottest 25 paper (2012) Journal of Biomedical Informatics.
- Distinguished paper award (2011) AMIA CRI summit.
Research Interests:
Jake Luo’s research interest lies in data-driven predictive analysis using machine learning-based algorithms and technologies, such as data mining, natural language processing and knowledge representation and modelling. He is interested in investigating how these computing technologies can be used to improve health care by discovering new knowledge and providing intelligent decision support for clinicians, medical researchers, patients, and policymakers.
Luo’s active research programs involve developing innovative heath data science technologies for knowledge discovery, adapting machine learning algorithms to enhance clinical data processing, implementing collaborative team science initiatives to improve health services and research, and creating intelligent clinical informatics tools to support evidence-based decision making.
Timeline
Dr. Luo is awarded for two CTSI BERD grant for using AI to advance health care applications
Dr. Jake Luo from the School of Public Health has been awarded two CTSI Pilot BERD Methodology Innovation awards for pioneering research in artificial intelligence and machine learning for healthcare applications.
The first project, “Development of a novel human-in-the-loop explainable artificial intelligence method for clinical decision support,” is a collaboration with Dr. David Friedland from the Medical College of Wisconsin (MCW). This innovative study aims to create an AI system that not only assists in clinical decision-making but also provides clear explanations for its recommendations. The second project, “Explainable hybrid machine learning for atrial fibrillation with electrocardiography and electronic health records,” is a joint effort with Drs. Rodney Sparapani and Patrick Noffke from MCW. This cutting-edge research focuses on developing advanced machine learning techniques to better understand and predict atrial fibrillation, a common heart rhythm disorder.
Jake is awarded for the Teacher’s Excellence Award. (Nominated by students!)
The Center for Excellence in Teaching and Learning (CETL) team awarded Dr. Jake Luo for excellent teaching! This award was nominated by students!
PhD student Mohammad Shalmani won Outsanding Presentation Award at Health Research Symposium
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Dr. Luo is awarded for an AHW grant to improve diagnosis of cardiovascular conditions
Pleased to inform that your proposal, Automating myocardial infarction diagnosis by ECGs with VERITAS software and hybrid learning, has been recommended for funding by AHW.
Teaching Courses
- Big Data Processing in Health Care (Fall)
- Introduction to Health Care Informatics (Spring)
- Graduate Professional Project and Thesis (Fall & Spring)
- Biomedical Informatics Seminar
- Fundamental Programming
- Advanced Programming
Contact:
Email (preferred): jakeluo@uwm.edu
Phone: 414-229-7333
Office: NWQ-B 6460
2025 E Newport Ave
Milwaukee, WI 53211
Student walk-in office hours:
(Please make an appointment through email)
Monday: 1 PM – 4 PM (Fall semester)
Tuesday: 1 PM – 4 PM (Spring semester)