Introduces techniques for constructing mathematical and computational models of biological processes at many levels of organizational scale from genome to whole-tissue. Topics include choice of techniques, quantitative characterization of biological properties, assumptions and model simplification, parameter estimation and sensitivity analysis, model verification and validation and integration of computational modeling w/experimental approaches.Prerequisites: BME 6101, and BME 2104 or BME 7806 (or equivalent).

Applies engineering science, design methods, and system analysis to developing areas and current problems in biomedical engineering. Topics vary by semester.

A year-long research project in biomedical engineering conducted in consultation with a department faculty advisor; usually related to ongoing faculty research. Includes the design, execution, and analysis of experimental laboratory work and computational or theoretical computer analysis of a problem. Requires a comprehensive report of the results. Prerequisite: third- or fourth-year standing, and instructor permission.

In a team, develop, prototype, and conduct verification and validation tests on engineering solutions to clinical challenges, demonstrating concept viability. Formal Design Control, Life Cycle, Risk Analysis, Project Management and Intellectual Property Strategies are introduced. Using Product Development Protocols, prepare a regulatory and implementation pathway analysis for commercialization into clinical practice. Prerequisite: BME 6550 Special Topics: Clinical Technology Continuum of Care

The focus for the course will be establishing a regulatory mindset for students to engage with the Food & Drug Administration, primarily the Center for Medical Devices and Radiological Health. The material covered throughout the semester is presented in a series of lectures, design prompts, exercises, workshops, and reviews. Students will develop their own project(s) and work as individuals and in small groups/teams. Prereq: BME 2000 and BME 2101

This course will provide students with a quantitative framework for identifying and addressing important biological questions at the molecular, cell, and tissue levels. The course will focus on the interplay between methods and logic, with an emphasis on the themes that emerge repeatedly in quantitative experiments.

Students learn foundational principals of advanced research, including hypothesis formulation, experimental design, and statistical methods to assess experimental data as it relates to hypothesis testing. Prerequisites: Previous exposure to statistics and programming in a language such as Python, MATLAB, or R.

Students learn to motivate research, design experiments, analyze/display data, present results for their own research. Receive training in professional skills, including project leadership and management, best practices for collaborative research, and developing resilience. Prereq: BME 6001-6004, or permission by instructor

For master's students.

Master's Research