The Biomedical and Health Informatics PhD program prepares individuals to develop and apply informatics theories and tools to solve complex problems across the life sciences and health ecosystem.
The Biomedical and Health Informatics PhD program is built on a core-track model, ensuring that all students develop a strong foundation in biomedical informatics and data science. Core courses provide essential training in analytics, research methods, and foundational informatics concepts. Students will also complete a dissertation research course as a key component of their doctoral training. From this foundation, students choose one of three specialized tracks.
Tracks
Translational bioinformatics
This track prepares students to apply computational tools to analyze biological data, connecting basic science with clinical insights. Coursework includes bioinformatics algorithms, data infrastructure, and applications in genomics and systems biology.
Clinical and health informatics
Students in this track focus on improving healthcare delivery and patient outcomes through informatics. Topics include clinical decision support, healthcare systems engineering, and data-driven approaches to health services research.
Artificial Intelligence in medicine
This advanced track equips students to apply AI in medical contexts. Students explore topics such as machine learning in clinical settings, AI in medical imaging, and the development of intelligent systems for healthcare innovation.
Goal
The goal of the program is to prepare individuals to develop and apply informatics theories and tools to solve complex problems across the life sciences and health ecosystem. As an inherently interdisciplinary field, biomedical and health informatics integrates principles from computer science, statistics, clinical informatics, and bioinformatics. The program emphasizes the analysis and interpretation of complex biological and clinical data, as well as the creation and dissemination of solutions, infrastructure, and algorithms aimed at addressing challenges in human health and disease. Ultimately, it seeks to distill, refine, and consolidate knowledge to advance discovery and innovation in health and life sciences.
Objective
The program aims to train graduate students to bridge the gap between advanced computational techniques, biomedical sciences, and health system science by conducting interdisciplinary research that drives innovation and advances human health. Graduates will be equipped to design and implement novel, data- and science-driven solutions, develop real-world information infrastructure, and carry out rigorous research that deepens our understanding of complex biological systems and health-related challenges. Their work will contribute meaningfully to improving healthcare and patient outcomes. In addition, students will be prepared to navigate the ethical, legal, and social implications of informatics and artificial intelligence, ensuring the responsible and beneficial use of emerging technologies across the life sciences and health ecosystem.
Curriculum
Core courses
- Foundations in Informatics
- Statistical Methods I
- Foundations of Artificial Intelligence in Medicine
- Research Methods and Design
- Privacy, Security, and Ethics
Bioinformatics track courses
- Introduction to Bioinformatics
- Biological Data Management
- Next-Gen Sequencing Data Analysis
- Algorithm in Bioinformatics
Clinical and Health Informatics track courses
- Clinical Operations and Decision Making
- Learning and Knowledge Health Systems
- Technology and Society
- Health Information Systems
Artificial Intelligence in Medicine courses
- AI in Medical Imaging
- AI for Biomedical Signals and Critical Systems
- Large Language Model Development for Medicine
- Integration of AI Systems in Healthcare
Academic requirement
- Four-year U.S. equivalent bachelor’s degree in a STEM discipline
- Statistics, data science, informatics, computer science, or closely related fields
- Degree awarded within the past five years
- A minimum cumulative GPA of 3.0 out of 4.0
- No GRE requirement
Language requirement
Choose one:
- IELTS 6.5
- TOEFL iBT 80
This program is jointly led by:
- Department of Biomedical Informatics and Data Science
- Department of Health Services Administration
- Marnix E. Heersink Institute for Biomedical Innovation
Program Structure and Curriculum Overview
The BHI-PhD follows a core-and-track model.
- Core. All students take the same set of core courses. These cover PhD-level analytics methods together with information, biological, and health-system knowledge.
- Tracks. The program offers three tracks: Bioinformatics, Clinical and Health Informatics, and Artificial Intelligence in Medicine. Each track has six required track courses. The Biomedical and Health Informatics Seminar is listed within each track, but all students attend the same seminar section.
- Electives. Students select approved electives to build depth in their area of interest (see §2.5 and Appendix B).
Research. Students complete dissertation research and may, before the qualifying examination, enroll in optional non-dissertation research as described in §2.6.
Curriculum Overview (students entering with a bachelor's degree)
| Category | Credit Hours |
|---|---|
| General education | 0 |
| Core courses | 20 |
| Track courses | 18 |
| Free electives | 12 |
| Required research / dissertation | 24 |
| Minimum total credit hours required for completion | 74 |
Credit-hour requirements for students entering with a master's degree are described in §3.2.
2.3 Core Courses (20 credit hours)
| Course No. | Course Title | Semester | Credit Hrs | Course Director |
|---|---|---|---|---|
| INFO 705 or INFO 696 | Foundations in Informatics / Introduction to Biomedical Informatics Research | Fall | 3 | Amy Wang |
| BST 621 | Statistical Methods I | Fall | 3 | Jeffery Szychowski |
| HCI 611 | Foundations of Artificial Intelligence in Medicine | Fall | 3 | Sandeep Bodduluri |
| AH 707 | Research Methods and Design | Spring | 3 | Kristine Hearld |
| HI 620 | Privacy, Security, and Ethics | Spring | 3 | Shannon Houser |
| GRD 717 | Principles of Scientific Integrity | Fall/Spring | 3 | Penny Seals |
| GBS 716, GBS 725, GBSC 726, or GRD 709 | Grant Writing / Scientific Writing | Spring | 2 | — |
Track Requirements
Each student completes one track (18 credit hours). Within each track, the four subject courses total 12 credit hours; the Biomedical and Health Informatics Seminar (taken twice) and the track journal club (taken twice) make up the remaining 6 credit hours.
Bioinformatics Track (18 credit hours)
| Course No. | Course Title | Semester | Credit Hrs | Course Director |
|---|---|---|---|---|
| INFO 601 / 701 | Introduction to Bioinformatics | Fall | 3 | Zechen Chong |
| INFO 603 / 703 | Biological Data Management | Spring | 3 | Jake Chen |
| INFO 604 / 704 | Next-Generation Sequencing Data Analysis | Spring | 3 | Jinzhuang Dou |
| INFO 602 / 702 | Algorithms in Bioinformatics | Fall | 3 | Lana Garmire / Jin Chen |
| INFO 691 / 791 | Biomedical and Health Informatics Seminar (twice) | Fall/Spring | 1 × 2 | Amy Wang |
| INFO 693 / 793 | Bioinformatics Journal Club (twice) | Fall | 2 × 2 | Yanfeng Zhang |
Clinical and Health Informatics Track (18 credit hours)
| Course No. | Course Title | Semester | Credit Hrs | Course Director |
|---|---|---|---|---|
| HI 626 / 726, or HI 614 | Health Information Systems / Clinical and Administrative Systems | Spring | 3 | Ryan Allen |
| INFO 627 / 727 | Clinical Operations and Decision Making | Fall | 3 | Jiancheng Ye |
| INFO 628 / 728 | Learning and Knowledge Health Systems | Spring | 3 | Abu Mosa |
| HI 629 / 729, or HI 611 | Technology and Society / Introduction to Health Informatics and Healthcare Delivery | Fall | 3 | Sue Feldman / Akanksha Singh |
| INFO 673 / 773 | Clinical and Health Informatics Journal Club (twice) | Fall | 2 × 2 | Jim Cimino |
| INFO 691 / 791 | Biomedical and Health Informatics Seminar (twice) | Fall/Spring | 1 × 2 | Amy Wang |
Artificial Intelligence in Medicine Track (18 credit hours)
| Course No. | Course Title | Semester | Credit Hrs | Course Director |
|---|---|---|---|---|
| AIM 642 | AI in Medical Imaging | Spring | 3 | Yu Hui (Dean) Fang |
| AIM 643 | AI for Biomedical Signals and Critical Systems | Fall | 3 | Ryan Godwin |
| AIM 645 / 745, or INFO 762 | Large Language Model Development for Medicine / Biomedical Applications of Natural Language Processing | Fall | 3 | Ryan Melvin (INFO 762: John Osborne) |
| HCI 614 | AI Integration in Clinical Workflow | Spring | 3 | Carlos Cardenas |
| INFO 674 / 774 | Artificial Intelligence in Medicine Journal Club (twice) | Fall | 2 × 2 | Rubin Pillay |
| INFO 691 / 791 | Biomedical and Health Informatics Seminar (twice) | Fall/Spring | 1 × 2 | Amy Wang |
Program Electives and Recommended Academic Focus
Students entering with a bachelor's degree choose approved elective courses (a minimum of 12 credit hours) to build depth in their research and career interests. Students entering with a relevant master's degree follow the 56-credit-hour minimum in §3.2 and are not required to complete a separate elective category. Appendix B lists additional approved electives. To take another elective not covered by the policies below or Appendix B, discuss the option with your academic and program advisors.
Any required course in one BHI-PhD track may be taken as an approved elective by a student in a different track, subject to prerequisites. A course may not satisfy both the student's track requirement and elective requirement.
Below are the program's areas of focus with recommended coursework. Students should work with their academic advisors and faculty mentors to tailor an elective plan to their interests.
| Specialty / Academic Focus | Description | Recommended Electives |
|---|---|---|
| Bioinformatics | Comprehensive knowledge and practical skills in leveraging computational methods and infrastructure to analyze biological data and bridge bench research and clinical application. | INFO 710 Programming with Biological Data; INFO 751 Systems Biomedicine of Human Microbiota; BY 633 Advanced Molecular Genetics and Medicine; GBS 708 Basic Genetics and Molecular Biology; BST 622 Statistical Methods II |
| Clinical and Health Informatics | Advanced competencies in translating and applying health-informatics concepts to enhance patient care, clinical decision-making, and healthcare-delivery systems science. | INFO 712 Visual Analytics for Biomedical Research; INFO 762 / CS 762 Biomedical Applications of NLP; CS 716 Big Data Programming; BST 622 Statistical Methods II |
| AI in Medicine | Expertise in applying informatics and artificial intelligence in healthcare. | AIM 747 Explainable AI in Medicine; CS 765 Deep Learning; CS 767 Machine Learning; CS 773 Computer Vision and CNNs; CS 763 Data Mining; CS 760 Artificial Intelligence |
Dissertation and Non-Dissertation Research
| Course No. | Title | Credit Hrs | When |
|---|---|---|---|
| INFO 798 | Non-Dissertation Research | 3 | Optional; may be taken multiple times before passing the qualifying examination |
| INFO 799 | Dissertation Research | 24 minimum | Taken only after formal admission to candidacy; 1–12 credit hours per enrollment |
INFO 798 credit treatment. INFO 798 is optional and repeatable for degree credit. For bachelor's-entry students, INFO 798 credits apply to the 12-credit elective category within the 74-credit minimum; they are not added to the 24-credit INFO 799 research minimum. Master's-entry students have no separate elective requirement, and optional INFO 798 credits do not replace required core, track, or INFO 799 credits.
Apply
Applications open Fall 2026 and will open on August 1, 2025.
Deadlines
Domestic: August 1, 2026
International: December 31, 2025 (closed to applicants)