As health systems increasingly rely on data, artificial intelligence, or AI, and connected digital platforms, Arizona State University is launching a new Master of Science in medical engineering. The stand-alone graduate degree prepares students to design and implement the digital, AI and software-driven medical technologies that are shaping modern clinical care.
Housed in the School of Biological and Health Systems Engineering, the program reflects ASU’s broader commitment to integrating engineering and medicine to address complex health challenges. By bringing engineers into direct collaboration with clinicians, students learn to design and launch medical technologies that function within real clinical environments and improve patient care.
What sets this program apart is not just what students learn, but what they do: Students work directly in clinical environments, identify real unmet needs and develop solutions that can be translated into practice, industry adoption or startup ventures.
Engineering meets medicine
A hallmark of the master’s degree in medical engineering is its close collaboration with ASU Health and the newly established John Shufeldt School of Medicine and Medical Engineering. This partnership embeds clinical perspectives directly into an engineering curriculum focused on digital health care systems, AI-enabled analysis and technology-driven clinical workflows.
The program includes clinical immersion experiences, where students spend time in hospitals and care environments to identify unmet needs, observe workflows and discuss technology gaps with clinicians. These experiences help students define problems in clinical settings and develop solutions that can be translated into practice.
“This program is a direct reflection of ASU’s vision for integrating engineering and medicine in a way that meets the realities of modern health care,” says Heather Clark, director of the School of Biological and Health Systems Engineering and senior associate dean for engineering integration within the medical school. “By focusing on digital health and AI, we are preparing students to design solutions that fit within real clinical workflows and health systems, not just isolated technologies.”
A defining feature of the program is its Foundations in Medicine sequence, a multi-course series designed for engineering and non-clinically trained students. The coursework provides structured exposure to human biology, disease pathology, medical terminology and clinical reasoning, giving students a working understanding of how conditions are diagnosed, treated and managed.
By learning medicine through an engineering lens and building clinical fluency early, students are better equipped to design effective digital and AI-driven solutions that align with the realities of patient care and integrate into health systems. This grounding enables them to collaborate effectively with clinicians and care teams.
“The Foundations in Medicine experience helps students understand how clinicians think and make decisions,” says Assistant Professor Scott Beeman, faculty lead for the master’s degree program in medical engineering. “That perspective is critical for engineers who want to design technologies that truly integrate into clinical practice.”
The Master of Science in medical engineering is created to support students from a wide range of academic backgrounds, including those not traditionally trained as engineers. The program welcomes students with prior training in life sciences, health sciences, medicine and related fields, reflecting the interdisciplinary nature of modern health care innovation.
Built-in foundational engineering coursework — including applied signals and systems, AI for medical applications, and structured engineering learning modules — allows students to become versed in engineering concepts while expanding on their existing expertise. Rather than requiring extensive engineering preparation before entry, the curriculum meets students where they are and guides them toward technical competence.
“Health care innovation depends on people who can bridge disciplines,” Clark says. “We intentionally designed this program so students from different academic pathways can develop a shared engineering and clinical language.”
The curriculum emphasizes applying engineering principles, systems thinking and AI to health care challenges. Core coursework focuses on clinical concepts through the lens of engineering, including systems-level analysis of human physiology, translational pathways for biomedical products, and digital health systems that integrate data science, AI and health information technologies.
The program also includes a dual-cohort learning model, where master’s students learn alongside medical students in select courses. This structure mirrors real-world clinical and innovation teams and helps students develop strong interprofessional communication and collaboration skills early in their training.
“Clinical immersion is the ultimate engineering needs assessment,” Beeman said. “It fundamentally changes how students think about problem definition and solution design.”
From concept to clinic: Translation in a digital health world
Students in the program can also take part in research and industry experiences that emphasize translation and commercialization. Through medically integrated research, industry immersion and a multi-semester capstone sequence, students learn to navigate regulatory environments, data privacy, intellectual property considerations and quality systems while developing and implementing solutions.
Each student team is supported by a mentoring triad comprising a clinical advisor, an ASU engineering faculty member, and an industry or entrepreneurial mentor, who ensure projects are clinically relevant, technically rigorous and commercially informed.
Preparing leaders in digital health
The master’s degree in medical engineering prepares graduates for careers across digital health, AI-enabled diagnostics, health systems innovation, medical software, biotechnology, hospital leadership and entrepreneurship. By combining engineering fundamentals with clinical context and a strong focus on software and data-driven solutions, the program equips students to lead in a rapidly evolving health care landscape.
In these roles, graduates design clinical decision-support tools, develop AI-driven diagnostic platforms and implement digital systems within health care environments.
Ultimately, this program prepares a new type of engineer who understands both the technical and clinical dimensions of health care and can bridge the gap between innovation and implementation. As health systems continue to evolve, they will play a critical role in shaping how care is delivered and improved for patients.
To support prospective students, the program hosts informational webinars where participants can learn more about the curriculum, career pathways and admissions process. Students interested in applying engineering and innovation to the future of health care are encouraged to explore this new graduate pathway.
Emmanuelle Compton contributed to this article.
