What is Computational Bioengineering?

Computational Bioengineering combines principles of engineering, biology, and medicine to improve human health using computational approaches. These approaches are applied from atomic resolution up to an entire organ or system of organs, including the following examples that draw from on ongoing research in the department: 

• at atomic resolution, cellular building blocks (e.g., proteins, nucleic acids, lipids, sugars) are simulated to understand their function in healthy cells, and how genetic mutations cause disease, and that can ultimately lead to the design of new therapeutics.
• at the resolution of cells and tissues, computational bioengineers simulate response to injury to understand and facilitate wound healing and design implants.
• at the resolution of organs and organ systems, imaging methods (e.g., CT, MRI) are used to understand the biomechanics and model organs (e.g., lung, heart, brain, etc.).
• across multiple resolutions and time scales, “multi-omics” analysis of large data sets generated from nucleic acid sequencing (DNA and RNA), metabolomics, and etc., are used to help understand the genetic basis of disease mechanisms and design precision treatments.

Given the scope and complexity involved in probing biology across resolutions, this area builds on fundamental disciplines (e.g., mathematics, physics, chemistry, statistics, computer science, engineering) to model, analyze, and understand biological data. This understanding forms the basis for translational biomedical applications that improve human health. Students in Computational Bioengineering will pursue careers in a broad range of fields including:   biomedical software engineering, biomolecular engineering, biotechnology, cell-based therapy development, gene therapies, genetic engineering, computational drug design and/or modeling, medical technologies, biological devices and/or embedded systems, biological sensors, systems and network biology, bioinformatics, computational biology, machine learning, or health informatics.

Computational Bioengineering Curriculum Map 3/20/24 | Machine Learning Course Guide 3/23/24| Sample Four-Year Plan 03/16/24

Computational Bioengineering Academic Advisors

Biomedical Engineering - Program Map: Computational Bioengineering Focus Area

*If ENGR:2995 is not offered in Fall, it can be taken the following Spring. Students who want to take ENGR:2995 and not ENGR:2130 can take ENGR:2730 Computers in Engr in Semester 3 and ENGR:2995 in Semester 4. At least two Focus Area Electives must be from the list of Engineering Topics.

*Computational Bioengineering students can take ENGR:2130 as an Engineering Topic if they have taken ENGR:2995 as an Engineering Core (and vice versa)
**Pre-medicine students should check with their Pre-medicine advisor regarding the need for this course.
§ Offered in academic years with odd fall and even spring semesters
§§ Offered in academic years with even fall and odd spring semesters

Note:  In addition to the four required focus area courses, an additional seven elective courses (21 s.h.) are also required (suggested electives list, minor, or certificate courses).  At least two of these electives (6 s.h.) must be from the list of Engineering Topics.  Electives not listed above may be approved via the Plan of Study form.

Please consult this guide when selecting electives that have machine learning content.

Check MyUI for the current course offerings and pre-/co-requisites.

Check the Computational Bioengineering Curriculum Map and Sample Four-Year Plan links at the top of this page for more details.

Link to previous Computational Bioengineering Focus Area Curriculum Map

Updated 3/23/24