Case Western Reserve University

What you'll study

The programme emphasises rigorous, interdisciplinary research into the design, modelling and evaluation of intelligent systems that interact with people. Doctoral candidates pursue an individually tailored course of study that combines foundational systems engineering with specialised topics in human systems engineering and intelligent systems.

• Core systems engineering and research methods: system modelling and analysis, optimisation, stochastic systems, experimental design, advanced statistics and computational methods for system-level evaluation.
• Human-centred and cognitive topics: human factors and ergonomics, cognitive systems engineering, human performance modelling, situation awareness, workload assessment and decision-making under uncertainty.
• Intelligent systems and AI: machine learning for human interaction, explainable AI, adaptive automation, reinforcement learning in human-in-the-loop systems and human–robot interaction.
• Practical tools and environments: sensor and signal processing, wearable and pervasive computing, virtual/augmented reality for training and assessment, data fusion and visualisation techniques for operator support.
• Interdisciplinary electives and domain applications: healthcare systems engineering, transportation and mobility systems, resilient critical infrastructure, socio-technical systems, and policy and ethics for intelligent systems.

Students typically complete advanced coursework in the first year or two, pass a qualifying examination, and then focus on an original research dissertation under the supervision of faculty. Research is carried out in close collaboration with other departments and research centres, and may include experimental studies, computational modelling, and field deployments in applied settings.

Entry requirements

Applicants are expected to hold a bachelor's or master's degree in engineering, computer science, cognitive science, psychology, human factors, or another quantitative discipline. A strong academic record and clear evidence of research aptitude are required.

• Official transcripts demonstrating relevant undergraduate/graduate preparation in mathematics, programming, statistics and domain-relevant coursework.
• A statement of purpose describing research interests, prior research experience and alignment with prospective faculty advisors.
• Curriculum vitae and at least three letters of recommendation from academic or professional referees who can speak to research potential.
• Examples of research output where available (published papers, technical reports, or a research portfolio) and a record of quantitative skills.
• Proof of English language proficiency for international applicants, when required by university regulations.

Admission is competitive and faculty fit is an important factor; applicants should identify potential supervisors whose research interests align with their own.

Career prospects

Graduates of the programme go on to careers across academia, industry and government where human-centred intelligent systems are developed and deployed. Typical roles include:

• University faculty and postdoctoral researchers leading research in human–machine interaction, human factors, systems engineering and AI.
• R&D scientists and engineers in technology companies working on intelligent user interfaces, explainable AI, and human-centred machine learning.
• Human factors and usability specialists in healthcare, aviation, automotive and defence sectors, designing safe and effective socio-technical systems.
• Systems architects and principal engineers responsible for integrating automation and human operators in complex systems.
• Consultants and analysts in safety-critical industries and government laboratories focusing on resilience, risk analysis and human performance.

Graduates are prepared to lead interdisciplinary teams, secure research funding, and translate fundamental research into deployed systems that improve performance, safety and user experience.

Why study at Case Western Reserve University

Case Western Reserve offers an environment conducive to advanced, interdisciplinary research in human systems engineering and intelligent systems. The university provides access to engineering and computer science expertise alongside clinical and domain partners in the Cleveland region, enabling applied research in healthcare, rehabilitation and clinical decision support.

• Interdisciplinary collaboration: opportunities to work with faculty across engineering, computer science, medicine and social sciences, and to engage with local healthcare institutions and industry partners.
• Research infrastructure: dedicated human factors and interactive systems laboratories, virtual reality and simulation facilities, robotics and sensing platforms, and high-performance computing resources.
• Faculty mentorship: small cohorts and close supervision from faculty with expertise in cognitive engineering, AI for human systems, and systems design and evaluation.
• Funding and professional development: opportunities for graduate research and teaching assistantships, industry-sponsored projects, and professional development through seminars and interdisciplinary centres.

The programme is designed for students who want to produce impactful research that bridges theory and practice, and who seek the mentorship and resources required to become leaders in the field of human-centred intelligent systems.