Students seeking a B.S. degree focus their engineering electives on one of seven subspecialties that incorporates traditional engineering disciplines and biomedical applications. See the Biomedical Engineering Undergraduate website for additional information.
Program Requirements
(See also General Requirements for Departmental Majors.)
The B.S. degree in biomedical engineering requires 129 credits. The courses listed below must either be taken or passed by examination for advanced credit. All courses used to satisfy degree requirements must be taken for a grade (no satisfactory/unsatisfactory grading may be counted). No more than 6 credits of engineering, science, or mathematics courses in which a grade of D was received may be counted.
Code | Title | Credits |
---|---|---|
Basic Sciences 1 | ||
AS.171.101 | General Physics: Physical Science Major I | 4 |
or AS.171.107 | General Physics for Physical Sciences Majors (AL) | |
AS.171.102 | General Physics: Physical Science Major II | 4 |
or AS.171.108 | General Physics for Physical Science Majors (AL) | |
AS.173.111 | General Physics Laboratory I | 1 |
AS.173.112 | General Physics Laboratory II | 1 |
AS.030.101 | Introductory Chemistry I | 3 |
AS.030.102 | Introductory Chemistry II | 3 |
AS.030.105 | Introductory Chemistry Laboratory I | 1 |
AS.030.106 | Introductory Chemistry Laboratory II | 1 |
Mathematics 2 | ||
AS.110.108 | Calculus I (Physical Sciences & Engineering) | 4 |
AS.110.109 | Calculus II (For Physical Sciences and Engineering) | 4 |
AS.110.202 | Calculus III | 4 |
or AS.110.211 | Honors Multivariable Calculus | |
EN.553.291 | Linear Algebra and Differential Equations | 4 |
Select one of the following: | 3-4 | |
Probability & Statistics for the Physical Sciences & Engineering | ||
Probability and Statistics for the Biological Sciences and Engineering | ||
Applied Statistics and Data Analysis | ||
Introduction to Statistics | ||
Monte Carlo Methods | ||
Humanities and Social Sciences | ||
Select courses to form a coherent program, relevant to the student’s goals, with at least one course at the 300-level or higher. 3 | 18 | |
Biomedical Core | ||
EN.580.111 | Biomedical Engineering and Design | 2 |
EN.580.151 | Structural Biology of Cells | 3 |
EN.580.153 | Structural Biology of Cells Laboratory | 1 |
EN.580.221 | Biochemistry and Molecular Engineering | 4 |
EN.580.241 | Statistical Physics | 2 |
EN.580.242 | Biological Models and Simulations | 2 |
EN.580.243 | Linear Signals and Systems | 2 |
EN.580.244 | Nonlinear Dynamics of Biological Systems | 2 |
EN.580.246 | Systems and Controls | 2 |
EN.580.248 | Systems Biology of the Cell | 2 |
EN.580.475 | Biomedical Data Science | 2 |
EN.580.477 | Biomedical Data Science Laboratory | 1 |
EN.580.485 | Computational Medicine: Cardiology | 2 |
EN.580.487 | Computational Medicine: Cardiology Laboratory | 1 |
Select two of the following core electives: 4 | 6 | |
Neuroengineering and Lab | ||
Microphysiological Systems and Laboratory | ||
Cell and Tissue Engineering Lab | ||
Immunoengineering Principles and Applications | ||
Methods in Nucleic Acid Sequencing Lab | ||
Build an Imager | ||
Career Exploration in BME 5 | ||
Focus Area | ||
Select one of the following: | 21 | |
Design 6 | ||
Select at least one of the following design sequences: | 6 | |
Senior Design Research and Senior Design/Research II (This option must be approved by the Materials Science & Engineering Department) | ||
ECE Ideation and Design Lab 7 | ||
ECE Ideation and Design Lab 7 | ||
Project in Design: Pharmacodynamics and Project in Design: Pharmacokinetics | ||
Design Team Health-Tech Project I and Design Team Health-Tech Project II | ||
Design Team Health-Tech Project I and Design Team Health-Tech Project II | ||
Neuro Data Design I and Neuro Data Design II | ||
Introduction to Rehabilitation Engineering and Introduction to Rehabilitation Engineering: Design Lab | ||
or EN.585.717 | Rehabilitation Engineering II | |
Principles of Design of BME Instrumentation and Honors Instrumentation 8 | ||
Precision Care Medicine I and Precision Care Medicine II | ||
Computer Integrated Surgery I and Computer Integrated Surgery II | ||
or EN.601.496 | Computer Integrated Surgery II - Teams | |
Multidisciplinary Engineering Design 1 and | ||
Computer Programming | ||
EN.500.112 | Gateway Computing: JAVA | 3 |
or EN.500.113 | Gateway Computing: Python | |
or EN.500.114 | Gateway Computing: Matlab | |
Free Electives | ||
Select 9 credits from any area. This can include Intersession S/U courses as well as other courses taken for S/U or grade and not used to fulfill another requirement. | 9 |
- 1
Students who receive credit for AP Physics I and/or Physics II will receive a waiver for the laboratory course. This will reduce the required number of credits for Basic Sciences by 1 or 2 credits. Students are still required to complete at least 129 total credits for the degree.
- 2
Students who take an approved math course and receive 3 credits will have a total of 19 credits. Students are still required to complete at least 129 total credits for the degree.
- 3
One course in which ethical and social issues related to technology or medicine is recommended. and at least two semesters of writing-intensive courses, see Writing Requirement.
- 4
These courses cannot be double-counted toward the 21-credit focus area requirement. Courses taken in excess of the 6 credit core elective requirement can be counted in a relevant focus area.
- 5
Career Exploration in BME is a 0-credit self-identified set of career related events (lectures, panels, journal clubs, etc.) beginning in the spring semester of year one and continuing until graduation. Career Exploration is administered through a learning management site; students will be enrolled by the department.
- 6
Each 2-semester sequence must be taken in its entirety.
- 7
Course EN.520.363 (juniors) and EN.580.463 (seniors) must be taken in a fall/spring or spring/fall sequence and for a total of 2 semesters to satisfy the BME design requirement. Students interested in longitudinal involvement may take the course up to 5 times.
- 8
EN.580.571 (2 credits) is offered during the spring semester. Instructor permission required.
Focus Areas
Building on the foundation of the core curriculum, each student is required to take a cohesive sequence of advanced engineering encompassing one of seven Biomedical Engineering focus areas. A student’s choice of focus area is made during the sophomore year and is based on their experience with the Biomedical Engineering Core and how they wish to apply their skill, knowledge, and passion:
Biomedical Data Science—involves the analysis of large-scale biomedical datasets to understand how living systems function. Our academic and research programs in Biomedical Data Science center on developing new data analysis technologies in order to understand disease mechanisms and provide improved health care at lower costs. Our curriculum in Biomedical Data Science trains students to extract knowledge from biomedical datasets of all sizes in order to understand and solve health-related problems. Students collaborate with faculty throughout the schools of Medicine and Engineering to develop novel cloud-based technologies and data analysis methods that will improve our ability to diagnose and treat diseases.
Computational Medicine—aims to advance health care by developing computational models of disease, personalizing these models using data from patients, and applying these models to improve the diagnosis and treatment of disease. We are using these patient models to discover novel risk biomarkers, predict disease progression, design optimal treatments, and identify new drug targets for applications such as cancer, cardiovascular disease, and neurological disorders. Our curriculum in Computational Medicine bridges biology with mathematics, engineering, and computational science. Students develop new solutions in personalized medicine by building computational models of the molecular biology, physiology, and anatomy of human health and disease.
Genomics and Systems Biology—connects the information in our genome and epigenome to the function of biological systems, from cells to tissues and organs. We are developing new computational and experimental methods for systematic analysis of genomes, building models that span length and time scales, and using synthetic biology to design new biomedical systems for human health applications. Our curriculum spans the fields of engineering, computer science, biology, and biostatistics. Students develop tools to understand the genetic, molecular, and cellular behaviors that cause disease.
Imaging and Medical Devices—involves the measurement of spatiotemporal distributions over scales ranging from molecules and cells to organs and whole populations. Grounded in mathematics, physics, and biological systems, our academic and research programs in Imaging & Medical Devices center on data-intensive image analysis and new imaging technologies that include optics, ultrasound, X-ray/CT, MRI, and molecular imaging. Our curriculum in Imaging & Medical Devices spans fundamental development of imaging technologies, incorporation of these technologies into instruments, and translation into the clinic. In addition to collecting anatomical data, students learn to use data analysis and computer simulations to generate functional images that allow physicians to understand organs and tissues from the smallest scale to the systems level.
Immunoengineering—harnesses the power of the immune system to treat diseases such as cancer and promote tissue regeneration and healing. Our curriculum trains students in immunoengineering at the molecular, cellular, and systems levels. Particular emphasis is placed on novel materials and methods to harness the body’s immune system to fight disease, and to promote tissue repair and healing. Students develop new biomaterials, vaccines, therapeutics, and systems to understand immune cell function and guide immune cell behavior.
Neuroengineering—comprises fundamental, experimental, computational, theoretical, and quantitative research aimed at understanding and augmenting brain function in health and disease across multiple spatiotemporal scales. Our curriculum in Neuroengineering trains students to develop and apply new technologies to understand and treat neurological disorders. Students build tools to define, control, enhance, or inhibit neural networks in precise spatial and temporal domains.
Translational Cell and Tissue Engineering—develops and translates advanced technologies to enhance or restore function at the molecular, cellular, and tissue levels. Hopkins BME is leading an effort in translational cell and tissue engineering that bridges discovery, innovation, and translation through basic science, engineering, and clinical endeavors. Our curriculum spans a variety of novel methods that harness the power of cells, materials, and advanced therapeutics to promote tissue repair and to treat disease. Students develop new techniques and biomaterials to guide cell behavior and reconstruct damaged tissues and organs.
Courses in a focus area must be taken for a total of 21 or more credits. At least 15 credits must come from the relevant upper-level engineering course list; a maximum of six credits from the non-upper-level engineering course lists may be used. Please refer to www.bme.jhu.edu/undergraduate/resources.htm for applicable courses designed for each focus area by faculty members with research interests appropriate to the area; all faculty members are active participants in shaping the undergraduate curriculum.
Biomedical Data Science Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.520.344 | Introduction to Digital Signal Processing | 3 |
EN.520.385 | Signals, Systems, & Learning | 3 |
EN.520.412 | Machine Learning for Signal Processing | 3 |
EN.520.414 | Image Processing & Analysis | 3 |
EN.520.415 | Image Process & Analysis II | 3 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.520.447 | Information Theory | 3 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.540.409 | Dynamic Modeling and Control | 4 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.432 | Project in Design: Pharmacokinetics | 3 |
EN.540.468 | Introduction to Nonlinear Dynamics and Chaos | 3 |
EN.553.361 | Introduction to Optimization | 4 |
EN.553.362 | Introduction to Optimization II | 4 |
EN.553.371 | Cryptology and Coding | 4 |
EN.553.385 | Numerical Linear Algebra | 4 |
EN.553.386 | Scientific Computing: Differential Equations | 4 |
EN.553.391 | Dynamical Systems | 4 |
EN.553.400 | Mathematical Modeling and Consulting | 4 |
EN.553.401 | Introduction to Research | 3 |
EN.553.413 | Applied Statistics and Data Analysis | 4 |
EN.553.420 | Introduction to Probability | 4 |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Introduction to Statistics | 4 |
EN.553.433 | Monte Carlo Methods | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.450 | Computational Molecular Medicine | 4 |
EN.553.463 | Network Models in Operations Research | 4 |
EN.553.467 | Deep Learning in Discrete Optimization | 3 |
EN.553.472 | Graph Theory | 4 |
EN.553.488 | Computing for Applied Mathematics | 3 |
EN.553.492 | Mathematical Biology | 3 |
EN.553.493 | Mathematical Image Analysis | 4 |
EN.553.630 | Introduction to Statistics | 4 |
EN.553.720 | Probability Theory I | 4 |
EN.553.721 | Probability Theory II | 4 |
EN.553.730 | Statistical Theory | 4 |
EN.553.731 | Statistical Theory II | 3 |
EN.580.431 | Introduction to Computational Medicine: Imaging | 2 |
EN.580.433 | Introduction to Computational Medicine: The Physiome | 2 |
EN.580.437 | Neuro Data Design I | 4 |
EN.580.438 | Neuro Data Design II | 4 |
EN.580.439 | Models of the Neuron | 4 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.460 | Epigenetics at the Crossroads of Genes and the Environment | 1.5 |
EN.580.462 | Representations of Choice | 3 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.480 | Precision Care Medicine I | 4 |
EN.580.481 | Precision Care Medicine II | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.709 | Sparse Representations in Computer Vision and Machine Learning | 3 |
EN.601.315 | Databases | 3 |
EN.601.318 | Operating Systems | 3 |
EN.601.320 | Parallel Programming | 3 |
EN.601.350 | Genomic Data Science | 3 |
EN.601.402 | Digital Health and Biomedical Informatics | 1 |
EN.601.415 | Databases | 3 |
EN.601.433 | Intro Algorithms | 3 |
EN.601.434 | Randomized and Big Data Algorithms | 3 |
EN.601.443 | Security & Privacy in Computing | 3 |
EN.601.446 | Sketching and Indexing for Sequences | 3 |
EN.601.447 | Computational Genomics: Sequences | 3 |
EN.601.448 | Computational Genomics: Data Analysis | 3 |
EN.601.454 | Augmented Reality | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.456 | Computer Integrated Surgery II | 3 |
EN.601.457 | Computer Graphics | 3 |
EN.601.461 | Computer Vision | 3 |
EN.601.463 | Algorithms for Sensor-Based Robotics | 3 |
EN.601.464 | Artificial Intelligence | 3 |
EN.601.465 | Natural Language Processing | 4 |
EN.601.466 | Information Retrieval and Web Agents | 3 |
EN.601.474 | ML: Learning Theory | 3 |
EN.601.475 | Machine Learning | 3 |
EN.601.476 | Machine Learning: Data to Models | 3 |
EN.601.477 | Causal Inference | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
EN.601.491 | Human-Robot Interaction | 3 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
EN.601.226 | Data Structures | 4 |
EN.601.229 | Computer System Fundamentals | 3 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
EN.601.231 | Automata & Computation Theory | 3 |
AS.110.311 | Methods of Complex Analysis | 4 |
AS.110.405 | Real Analysis I | 4 |
AS.110.421 | Dynamical Systems | 4 |
AS.110.443 | Fourier Analysis | 4 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
Computational Medicine Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.520.315 | Intro. to Bio-Inspired Processing of Audio-Visual Signals | 3 |
EN.520.385 | Signals, Systems, & Learning | 3 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.530.343 | Design and Analysis of Dynamical Systems | 3 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.676 | Locomotion Dynamics & Control | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.432 | Project in Design: Pharmacokinetics | 3 |
EN.553.361 | Introduction to Optimization | 4 |
EN.553.386 | Scientific Computing: Differential Equations | 4 |
EN.553.391 | Dynamical Systems | 4 |
EN.553.420 | Introduction to Probability | 4 |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Introduction to Statistics | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.450 | Computational Molecular Medicine | 4 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.431 | Introduction to Computational Medicine: Imaging | 2 |
EN.580.433 | Introduction to Computational Medicine: The Physiome | 2 |
EN.580.437 | Neuro Data Design I | 4 |
EN.580.438 | Neuro Data Design II | 4 |
EN.580.439 | Models of the Neuron | 4 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.460 | Epigenetics at the Crossroads of Genes and the Environment | 1.5 |
EN.580.462 | Representations of Choice | 3 |
EN.580.480 | Precision Care Medicine I | 4 |
EN.580.481 | Precision Care Medicine II | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.688 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.601.350 | Genomic Data Science | 3 |
EN.601.447 | Computational Genomics: Sequences | 3 |
EN.601.448 | Computational Genomics: Data Analysis | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.456 | Computer Integrated Surgery II | 3 |
EN.601.461 | Computer Vision | 3 |
EN.601.475 | Machine Learning | 3 |
EN.601.476 | Machine Learning: Data to Models | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
EN.601.496 | Computer Integrated Surgery II - Teams | 3 |
EN.601.723 | Advanced Topics in Data-Intensive Computing | 3 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
EN.601.226 | Data Structures | 4 |
EN.601.229 | Computer System Fundamentals | 3 |
EN.601.231 | Automata & Computation Theory | 3 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
Genomics and Systems Biology Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.510.311 | Structure Of Materials | 3 |
EN.510.316 | Biomaterials I | 3 |
EN.510.407 | Biomaterials II: Host response and biomaterials applications | 3 |
EN.510.436 | Biomaterials for Cell Engineering | 3 |
EN.520.315 | Intro. to Bio-Inspired Processing of Audio-Visual Signals | 3 |
EN.520.353 | Control Systems | 4 |
EN.520.385 | Signals, Systems, & Learning | 3 |
EN.520.414 | Image Processing & Analysis | 3 |
EN.520.415 | Image Process & Analysis II | 3 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.520.454 | Control Systems Design | 3 |
EN.520.636 | Feedback Control in Biological Signaling Pathways | 3 |
EN.530.327 | Introduction to Fluid Mechanics | 3 |
EN.530.343 | Design and Analysis of Dynamical Systems | 3 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.414 | Computer-Aided Design | 3 |
EN.530.420 | Robot Sensors/Actuators | 4 |
EN.530.426 | Biofluid Mechanics | 3 |
EN.530.436 | Bioinspired Science and Technology | 3 |
EN.530.445 | Introduction to Biomechanics | 3 |
EN.530.446 | Experimental Methods in Biomechanics | 3 |
EN.530.448 | Biosolid Mechanics | 3 |
EN.540.303 | Transport Phenomena I | 3 |
EN.540.304 | Transport Phenomena II | 4 |
EN.540.409 | Dynamic Modeling and Control | 4 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.432 | Project in Design: Pharmacokinetics | 3 |
EN.553.361 | Introduction to Optimization | 4 |
EN.553.362 | Introduction to Optimization II | 4 |
EN.553.386 | Scientific Computing: Differential Equations | 4 |
EN.553.391 | Dynamical Systems | 4 |
EN.553.400 | Mathematical Modeling and Consulting | 4 |
EN.553.420 | Introduction to Probability | 4 |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Introduction to Statistics | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.450 | Computational Molecular Medicine | 4 |
EN.553.467 | Deep Learning in Discrete Optimization | 3 |
EN.570.351 | Introduction to Fluid Mechanics | 3 |
EN.580.418 | Principles of Pulmonary Physiology | 3 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.431 | Introduction to Computational Medicine: Imaging | 2 |
EN.580.433 | Introduction to Computational Medicine: The Physiome | 2 |
EN.580.439 | Models of the Neuron | 4 |
EN.580.441 | Cellular Engineering | 3 |
EN.580.444 | Biomedical Applications of Glycoengineering | 3 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.454 | Methods in Nucleic Acid Sequencing Lab | 3 |
EN.580.459 | Seminar in Epigenetic Engineering | 1 |
EN.580.460 | Epigenetics at the Crossroads of Genes and the Environment | 1.5 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.471 | Principles of Design of BME Instrumentation | 4 |
EN.580.480 | Precision Care Medicine I | 4 |
EN.580.481 | Precision Care Medicine II | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.571 | Honors Instrumentation | 2 |
EN.580.625 | Structure and Function of the Auditory and Vestibular Systems | 3 |
EN.580.752 | Advanced Topics in Regenerative and Immune Engineering | 4 |
EN.580.688 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.601.350 | Genomic Data Science | 3 |
EN.601.448 | Computational Genomics: Data Analysis | 3 |
EN.601.465 | Natural Language Processing | 4 |
EN.601.475 | Machine Learning | 3 |
EN.601.476 | Machine Learning: Data to Models | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.520.214 | Signals and Systems | 4 |
EN.520.216 | Introduction To VLSI | 3 |
EN.520.230 | Mastering Electronics | 3 |
EN.520.231 | Mastering Electronics Laboratory | 2 |
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
EN.601.226 | Data Structures | 4 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
AS.020.303 | Genetics | 3 |
AS.080.305 | Neuroscience: Cellular and Systems I | 3 |
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
Imaging and medical devices Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.510.311 | Structure Of Materials | 3 |
EN.510.313 | Mechanical Properties of Materials | 3 |
EN.510.314 | Electronic Properties of Materials | 3 |
EN.510.316 | Biomaterials I | 3 |
EN.510.403 | Materials Characterization | 3 |
EN.510.407 | Biomaterials II: Host response and biomaterials applications | 3 |
EN.510.422 | Micro and Nano Structured Materials & Devices | 3 |
EN.510.430 | Biomaterials Lab | 3 |
EN.520.315 | Intro. to Bio-Inspired Processing of Audio-Visual Signals | 3 |
EN.520.340 | Introduction to Mechatronics: Sensing, Processing, Learning and Actuation | 3 |
EN.520.344 | Introduction to Digital Signal Processing | 3 |
EN.520.349 | Microprocessor Lab I | 3 |
EN.520.353 | Control Systems | 4 |
EN.520.414 | Image Processing & Analysis | 3 |
EN.520.415 | Image Process & Analysis II | 3 |
EN.520.417 | Computation for Engineers | 3 |
EN.520.424 | FPGA Synthesis Lab | 3 |
EN.520.427 | Design of Biomedical Instruments and Systems | 3 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.520.433 | Medical Image Analysis | 3 |
EN.520.435 | Digital Signal Processing | 3 |
EN.520.447 | Information Theory | 3 |
EN.520.448 | Electronics Design Lab | 3 |
EN.520.450 | Advanced Micro-Processor Lab | 3 |
EN.520.454 | Control Systems Design | 3 |
EN.520.483 | Bio-Photonics Laboratory | 3 |
EN.520.491 | CAD Design of Digital VLSI Systems I (Juniors/Seniors) | 3 |
EN.520.492 | Mixed-Mode VLSI Systems | 3 |
EN.520.495 | Microfabrication Laboratory | 4 |
EN.520.631 | Ultrasound and Photoacoustic Beamforming | 3 |
EN.520.646 | Wavelets & Filter Banks | 3 |
EN.520.651 | Foundations of Probabilistic Machine Learning | 4 |
EN.530.381 | Engineering Design Process | 3 |
EN.530.414 | Computer-Aided Design | 3 |
EN.530.420 | Robot Sensors/Actuators | 4 |
EN.530.421 | Mechatronics | 3 |
EN.530.424 | Dynamics of Robots and Spacecraft | 3 |
EN.530.441 | Introduction to Biophotonics | 3 |
EN.530.445 | Introduction to Biomechanics | 3 |
EN.530.446 | Experimental Methods in Biomechanics | 3 |
EN.530.468 | Locomotion Mechanics: Fundamentals | 3 |
EN.530.473 | Molecular Spectroscopy and Imaging | 3 |
EN.530.474 | Effective and Economic Design for Biomedical Instrumentation | 4 |
EN.530.646 | Robot Devices, Kinematics, Dynamics, and Control | 4 |
EN.530.672 | Biosensing & BioMEMS | 3 |
EN.540.403 | Colloids and Nanoparticles | 3 |
EN.540.440 | Micro/Nanotechnology: The Science and Engineering of Small Structures | 3 |
EN.553.361 | Introduction to Optimization | 4 |
EN.553.362 | Introduction to Optimization II | 4 |
EN.553.391 | Dynamical Systems | 4 |
EN.553.413 | Applied Statistics and Data Analysis | 4 |
EN.553.420 | Introduction to Probability | 4 |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Introduction to Statistics | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.433 | Monte Carlo Methods | 4 |
EN.553.472 | Graph Theory | 4 |
EN.553.493 | Mathematical Image Analysis | 4 |
EN.553.630 | Introduction to Statistics | 4 |
EN.553.761 | Nonlinear Optimization I | 3 |
EN.553.762 | Nonlinear Optimization II | 3 |
EN.580.425 | Radiology for Engineers | 3 |
EN.580.435 | Applied Bioelectrical Engineering | 3 |
EN.580.456 | Introduction to Rehabilitation Engineering | 3 |
EN.580.457 | Introduction to Rehabilitation Engineering: Design Lab | 3 |
EN.585.717 | Rehabilitation Engineering II | 3 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.471 | Principles of Design of BME Instrumentation | 4 |
EN.580.571 | Honors Instrumentation | 2 |
EN.580.479 | Principles and Applications of Modern X-ray Imaging and Computed Tomography | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.493 | Imaging Instrumentation | 4 |
EN.580.494 | Build an Imager | 3 |
EN.580.678 | Biomedical Photonics I | 4 |
EN.580.689 | Modern Optical Microscopy: Theory and Practice | 3 |
EN.580.740 | Surgery for Engineers | 3 |
EN.580.742 | Neural Implants and Interfaces | 3 |
EN.601.315 | Databases | 3 |
EN.601.415 | Databases | 3 |
EN.601.454 | Augmented Reality | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.456 | Computer Integrated Surgery II | 3 |
EN.601.461 | Computer Vision | 3 |
EN.601.463 | Algorithms for Sensor-Based Robotics | 3 |
EN.601.475 | Machine Learning | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
EN.601.496 | Computer Integrated Surgery II - Teams | 3 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.520.214 | Signals and Systems | 4 |
EN.520.230 | Mastering Electronics | 3 |
EN.520.231 | Mastering Electronics Laboratory | 2 |
EN.530.241 | Electronics & Instrumentation | 3 |
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
EN.601.226 | Data Structures | 4 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
AS.110.405 | Real Analysis I | 4 |
AS.110.443 | Fourier Analysis | 4 |
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
IMMUNoENGINEERING FOCUS AREA
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.510.311 | Structure Of Materials | 3 |
EN.510.312 | Thermodynamics/Materials | 3 |
EN.510.313 | Mechanical Properties of Materials | 3 |
EN.510.314 | Electronic Properties of Materials | 3 |
EN.510.315 | Physical Chemistry of Materials II | 3 |
EN.510.316 | Biomaterials I | 3 |
EN.510.403 | Materials Characterization | 3 |
EN.510.407 | Biomaterials II: Host response and biomaterials applications | 3 |
EN.510.415 | The Chemistry of Materials Synthesis | 3 |
EN.510.422 | Micro and Nano Structured Materials & Devices | 3 |
EN.510.426 | Biomolecular Materials I - Soluble Proteins and Amphiphiles | 3 |
EN.510.430 | Biomaterials Lab | 3 |
EN.510.435 | Mechanical Properties of Biomaterials | 3 |
EN.510.442 | Nanomaterials Lab | 3 |
EN.510.443 | Chemistry and Physics of Polymers | 3 |
EN.520.495 | Microfabrication Laboratory | 4 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.426 | Biofluid Mechanics | 3 |
EN.530.436 | Bioinspired Science and Technology | 3 |
EN.530.445 | Introduction to Biomechanics | 3 |
EN.530.446 | Experimental Methods in Biomechanics | 3 |
EN.540.301 | Kinetic Processes | 4 |
EN.540.303 | Transport Phenomena I | 3 |
EN.540.304 | Transport Phenomena II | 4 |
EN.540.306 | Chemical & Biomolecular Separation | 4 |
EN.540.402 | Metabolic Systems Biotechnology | 3 |
EN.540.403 | Colloids and Nanoparticles | 3 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.422 | Introduction to Polymeric Materials | 3 |
EN.540.432 | Project in Design: Pharmacokinetics | 3 |
EN.540.440 | Micro/Nanotechnology: The Science and Engineering of Small Structures | 3 |
EN.540.465 | Engineering Principles of Drug Delivery | 3 |
EN.540.602 | Metabolic Systems Biotechnology | 3 |
EN.553.386 | Scientific Computing: Differential Equations | 4 |
EN.553.391 | Dynamical Systems | 4 |
EN.553.413 | Applied Statistics and Data Analysis | 4 |
EN.553.420 | Introduction to Probability | 4 |
EN.553.426 | Introduction to Stochastic Processes | 4 |
EN.553.430 | Introduction to Statistics | 4 |
EN.553.436 | Introduction to Data Science | 4 |
EN.553.433 | Monte Carlo Methods | 4 |
EN.553.450 | Computational Molecular Medicine | 4 |
EN.553.492 | Mathematical Biology | 3 |
EN.580.418 | Principles of Pulmonary Physiology | 3 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.441 | Cellular Engineering | 3 |
EN.580.442 | Tissue Engineering | 3 |
EN.580.444 | Biomedical Applications of Glycoengineering | 3 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.453 | Immunoengineering Principles and Applications | 3 |
EN.580.452 | Cell and Tissue Engineering Lab | 3 |
EN.580.464 | Advanced Data Science for Biomedical Engineering | 4 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.454 | Methods in Nucleic Acid Sequencing Lab | 3 |
EN.580.646 | Molecular Immunoengineering | 3 |
EN.580.752 | Advanced Topics in Regenerative and Immune Engineering | 4 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
AS.020.303 | Genetics | 3 |
AS.020.337 | Stem Cells & the Biology of Aging & Disease | 2 |
AS.020.363 | Developmental Biology | 3 |
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
Neuroengineering Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.520.315 | Intro. to Bio-Inspired Processing of Audio-Visual Signals | 3 |
EN.520.344 | Introduction to Digital Signal Processing | 3 |
EN.520.349 | Microprocessor Lab I | 3 |
EN.520.353 | Control Systems | 4 |
EN.520.385 | Signals, Systems, & Learning | 3 |
EN.520.412 | Machine Learning for Signal Processing | 3 |
EN.520.424 | FPGA Synthesis Lab | 3 |
EN.520.432 | Medical Imaging Systems | 3 |
EN.520.445 | Audio Signal Processing | 3 |
EN.520.448 | Electronics Design Lab | 3 |
EN.520.450 | Advanced Micro-Processor Lab | 3 |
EN.520.454 | Control Systems Design | 3 |
EN.520.491 | CAD Design of Digital VLSI Systems I (Juniors/Seniors) | 3 |
EN.520.492 | Mixed-Mode VLSI Systems | 3 |
EN.520.495 | Microfabrication Laboratory | 4 |
EN.530.414 | Computer-Aided Design | 3 |
EN.530.420 | Robot Sensors/Actuators | 4 |
EN.530.421 | Mechatronics | 3 |
EN.530.445 | Introduction to Biomechanics | 3 |
EN.530.446 | Experimental Methods in Biomechanics | 3 |
EN.530.468 | Locomotion Mechanics: Fundamentals | 3 |
EN.530.646 | Robot Devices, Kinematics, Dynamics, and Control | 4 |
EN.530.672 | Biosensing & BioMEMS | 3 |
EN.540.403 | Colloids and Nanoparticles | 3 |
EN.540.440 | Micro/Nanotechnology: The Science and Engineering of Small Structures | 3 |
EN.580.424 | Neuroengineering and Lab | 3 |
EN.580.426 | Neuroengineering: The Neural Control of Movement | 3 |
EN.580.437 | Neuro Data Design I | 4 |
EN.580.438 | Neuro Data Design II | 4 |
EN.580.441 | Cellular Engineering | 3 |
EN.580.442 | Tissue Engineering | 3 |
EN.580.452 | Cell and Tissue Engineering Lab | 3 |
EN.580.456 | Introduction to Rehabilitation Engineering | 3 |
EN.580.457 | Introduction to Rehabilitation Engineering: Design Lab | 3 |
EN.585.717 | Rehabilitation Engineering II | 3 |
EN.580.471 | Principles of Design of BME Instrumentation | 4 |
EN.580.571 | Honors Instrumentation | 2 |
EN.580.488 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.491 | Learning, Estimation and Control | 3 |
EN.580.493 | Imaging Instrumentation | 4 |
EN.580.494 | Build an Imager | 3 |
EN.580.688 | Foundations of Computational Biology and Bioinformatics | 3 |
EN.580.689 | Modern Optical Microscopy: Theory and Practice | 3 |
EN.580.742 | Neural Implants and Interfaces | 3 |
EN.601.455 | Computer Integrated Surgery I | 4 |
EN.601.456 | Computer Integrated Surgery II | 3 |
EN.601.475 | Machine Learning | 3 |
EN.601.482 | Machine Learning: Deep Learning | 4 |
EN.601.496 | Computer Integrated Surgery II - Teams | 3 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.520.214 | Signals and Systems | 4 |
EN.520.216 | Introduction To VLSI | 3 |
EN.520.230 | Mastering Electronics | 3 |
EN.530.254 | Manufacturing Engineering | 3 |
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |
translational cell and tissue Engineering Focus Area
Code | Title | Credits |
---|---|---|
Upper-Level Engineering Courses | ||
EN.510.311 | Structure Of Materials | 3 |
EN.510.312 | Thermodynamics/Materials | 3 |
EN.510.313 | Mechanical Properties of Materials | 3 |
EN.510.314 | Electronic Properties of Materials | 3 |
EN.510.315 | Physical Chemistry of Materials II | 3 |
EN.510.316 | Biomaterials I | 3 |
EN.510.403 | Materials Characterization | 3 |
EN.510.407 | Biomaterials II: Host response and biomaterials applications | 3 |
EN.510.415 | The Chemistry of Materials Synthesis | 3 |
EN.510.422 | Micro and Nano Structured Materials & Devices | 3 |
EN.510.426 | Biomolecular Materials I - Soluble Proteins and Amphiphiles | 3 |
EN.510.430 | Biomaterials Lab | 3 |
EN.510.435 | Mechanical Properties of Biomaterials | 3 |
EN.510.436 | Biomaterials for Cell Engineering | 3 |
EN.510.442 | Nanomaterials Lab | 3 |
EN.510.443 | Chemistry and Physics of Polymers | 3 |
EN.520.495 | Microfabrication Laboratory | 4 |
EN.530.410 | Biomechanics of the Cell | 3 |
EN.530.426 | Biofluid Mechanics | 3 |
EN.530.436 | Bioinspired Science and Technology | 3 |
EN.530.445 | Introduction to Biomechanics | 3 |
EN.530.446 | Experimental Methods in Biomechanics | 3 |
EN.530.448 | Biosolid Mechanics | 3 |
EN.530.468 | Locomotion Mechanics: Fundamentals | 3 |
EN.530.474 | Effective and Economic Design for Biomedical Instrumentation | 4 |
EN.540.301 | Kinetic Processes | 4 |
EN.540.303 | Transport Phenomena I | 3 |
EN.540.304 | Transport Phenomena II | 4 |
EN.540.306 | Chemical & Biomolecular Separation | 4 |
EN.540.402 | Metabolic Systems Biotechnology | 3 |
EN.540.403 | Colloids and Nanoparticles | 3 |
EN.540.414 | Computational Protein Structure Prediction and Design | 3 |
EN.540.421 | Project in Design: Pharmacodynamics | 3 |
EN.540.422 | Introduction to Polymeric Materials | 3 |
EN.540.432 | Project in Design: Pharmacokinetics | 3 |
EN.540.440 | Micro/Nanotechnology: The Science and Engineering of Small Structures | 3 |
EN.540.465 | Engineering Principles of Drug Delivery | 3 |
EN.540.602 | Metabolic Systems Biotechnology | 3 |
EN.553.391 | Dynamical Systems | 4 |
EN.580.418 | Principles of Pulmonary Physiology | 3 |
EN.580.430 | Systems Pharmacology and Personalized Medicine | 4 |
EN.580.435 | Applied Bioelectrical Engineering | 3 |
EN.580.441 | Cellular Engineering | 3 |
EN.580.442 | Tissue Engineering | 3 |
EN.580.444 | Biomedical Applications of Glycoengineering | 3 |
EN.580.447 | Computational Stem Cell Biology | 3 |
EN.580.452 | Cell and Tissue Engineering Lab | 3 |
EN.580.453 | Immunoengineering Principles and Applications | 3 |
EN.580.454 | Methods in Nucleic Acid Sequencing Lab | 3 |
EN.580.456 | Introduction to Rehabilitation Engineering | 3 |
EN.580.457 | Introduction to Rehabilitation Engineering: Design Lab | 3 |
EN.585.717 | Rehabilitation Engineering II | 3 |
EN.580.643 | Advanced Orthopaedic Tissue Engineering | 3 |
EN.580.646 | Molecular Immunoengineering | 3 |
Contact the department advising office for course additions. | ||
200-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
EN.580.212 | Design Team Health-Tech Project II | 3 |
EN.580.298 | Advanded Design Team | 3 |
Non Upper-Level Engineering Courses | ||
A maximum of 3 credits from this list may count in focus area | ||
AS.020.303 | Genetics | 3 |
AS.020.337 | Stem Cells & the Biology of Aging & Disease | 2 |
AS.020.363 | Developmental Biology | 3 |
EN.580.112 | Design Team Health-Tech Project II | 3 |
EN.580.211 | Design Team Health-Tech Project I | 3 |
Students may use a maximum of 3 research credits (courses coded EN.XXX.5XX) as a non-upper-level engineering course. |