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 Academic Advisors

Biomedical Engineering - Program Map: Computational Bioengineering Focus Area

Semester 1Chem & Lab
Engr MathⅠ MATH:1550 Intro Engr Prob Solving ENGR:1100Rhetoric
Engr Success First Year ENGR:1000
Semester 2Chem II / Lab 
Engr Math Ⅱ MATH:1560Engr Math Ⅲ MATH:2550Physics I / Lab
Intro Engr Computing
BME Forum BME:1010
Semester 3Foundations of Biology / Lab
Engr Math Ⅳ MATH:2560Statics 
Elec Circuits ENGR:2120Thermo ENGR:2130 or
*Intro AI & Mach Learning
BME Prof Seminar BME:2010
Semester 4Human Physiology
HHP:3500 or BME:2260
Quantitative Physiology
BIOS:4120 or
Systems, Instrum,
& Data Acquisition
/ Lab BME:2200
Bioimaging &
Bioinformatics / Lab
Comp in Engr
Semester 5Cell Biology for Engr / Lab
Biomaterials &
Biomechanics / Lab
Intro to Software
Diversity & Inclusion 
Semester 6Focus Area
Elective #1
Focus Area
Elective #2
Focus Area
Elective #3
Be Creative 
Semester 7BME Senior DesignⅠ BME:4910Focus Area
Elective #4
Focus Area
Elective #5
Focus Area
Elective #6
Approved GEC Course 
Semester 8BME Senior Design Ⅱ BME:4920Physics II / Lab
Focus Area
Elective #7
Approved GEC CourseApproved GEC Course 


*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.

ENGR:2730 Computers in EngineeringF/SP: ENGR:1300
ECE:3330 Intro to Software DesignF/SP: ENGR:2730
BME:4310 Computational BiochemistryFP: MATH:1560 or MATH:1860, CHEM:1120
BME:5335 Computational BioinformaticsSP: (ENGR:1300 or CS:5110), (BIOS:4120 or STAT:3510)


Engineering Topics (must choose two)  
BME:5240 Deep Learning in Medical ImagingF

P: ENGR:2995; ECE:5480 recommended

ECE:5330 Graph Algorithms & Combinatorial OptimizationSP: ECE:3330
ECE:5820 Software Engineering Languages & ToolsFP: CS:2820 or ECE:3330
*ENGR:2130 ThermodynamicsAllP: PHYS:1611, CHEM:1110; C: MATH:1560
*ENGR:2995 Intro to AI and Machine LearningSP: ENGR:1300 and sophomore standing; C: MATH:2550
Suggested Electives  
BME:5435 Systems Biology for BMESP: BME:2400, BME:2200
BME:5441 Numerical & Statistical Methods for BioengrF §P: MATH:2560 and MATH:2550
ANTH:2320 Origins of Human Infectious DiseaseF 
BIOL:2512 Fundamental GeneticsAllP: BIOL:1411, BIOL:1412 or PSY:2701, CHEM:1110; Recommended: CHEM:2210
BIOL:3314 GenomicsSP: BIOL:2211 or BIOL:2512 or BIOL:2723
BIOL:3212 Bioinformatics for BeginnersFP: BIOL:2512 or BIOL:2211 or MICR:3170 or
CHEM:5431 Statistical Thermodynamics ⅠS §Recommended: CHEM:4431
CHEM:5436 Electronic Structure & Informatics Chem.See MyUIRecommended: CHEM:4432
CS:3330 AlgorithmsAllP: CS:2210 and CS:2230 (min C-), MATH:1850 or MATH:1550 or MATH:1860 or MATH:1560
CS:5350 Design and Analysis of AlgorithmsSee MyUIP: CS:3330 or CS:5340
ECE:5450 Machine LearningFP: ECE:2400 or BME:2200
ECE:5800 Fundamentals of Software EngineeringF/SP: CS:2820 or ECE:3330
ECE:5995:0001 Cont. Topics in ECE:Applied Machine LearningSP: ECE:2400 or BME:2200
**BIOL:1412 Diversity of Form & FunctionAllP: BIOL:1411 w/min C-
CHEM:2210 Organic Chemistry ⅠAllP: CHEM:1120 w/min C-
CHEM:2220 Organic Chemistry ⅡAllP: CHEM:2210 w/min C-
CHEM:2410 Organic Chemistry LabAllP: CHEM:1120 w/min C-, CHEM:2210 w/min C-; C:
BMB:3110 BiochemistryAllSee MyUI for requirements
BIOL:2512 Fundamental GeneticsAllP: BIOL:1411 w/min C-, BIOL:1412 or PSY:2701 w/min
C-, CHEM:1110; Recommended: CHEM:2210


*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