# MEng Focus Areas

## Biological/Chemical Engineering

Biological engineering exists at the interface of engineering, biological, and chemical sciences. This interdisciplinary field brings to bear fundamental design principles to both elucidate and modulate the function of biological systems, ranging in scale from molecular to cellular to whole organisms. The bioengineer’s toolbox may include skills such as modeling, big data analysis, genetics, process design, biochemistry, and molecular, micro and cellular biology. By modeling, designing, engineering, and optimizing biological systems, bioengineers and biotechnologists are seeking to tackle key unmet needs in medicine, agriculture, industry, the environment, consumer markets, and more.

### Core Courses

- ENGS 108: Applied Machine Learning
- ENGS 150: Intermediate Fluid Mechanics
- ENGS 155: Intermediate Thermodynamics
- ENGS 156: Heat, Mass, and Momentum Transfer
- ENGS 157: Chemical Process Design
- ENGS 158: Chemical Kinetics and Reactors
- ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering
- ENGS 160: Biotechnology and Biochemical Engineering
- ENGS 161: Metabolic Engineering
- ENGS 162: Basic Biological Circuit Engineering
- ENGS 163: Advanced Protein Engineering
- ENGS 165: Biomaterials
- ENGG 260: Advances in Biotechnology
- ENGG 261: Biomass Energy Systems
- ENGS 262: Advanced Biological Circuit Engineering
- COSC 175: Introduction to Bioinformatics (Applied Math)
- BIOC 101: Molecular Information in Biological Systems

### Example Non-engineering Courses

- COSC 174: Machine Learning and Statistical Data Analysis1
- COSC 186: Computational Structural Biology
- COSC 189: Topics in Computational Immunology
- MICR 142: Advanced Cellular and Molecular Immunology
- MICR 144: Cellular and Molecular Basis of Immunity
- MICR 149: Microbial Physiology and Metabolism
- QBS 108: Applied Machine Learning1
- QBS 120: Foundations of Biostatistics I: Statistical Theory for the Quantitative Biomedical Sci.
- QBS 121: Foundations of Biostatistics II: Regression
- QBS 149: Mathematics and Probability for Statistics and Data Mining
- QBS 175: Foundations of Bioinformatics II2
- CHEM 101.2: Statistical Thermodynamics
- CHEM 161.2: Biomolecular Simulations
- CHEM 161.4: Structure and Dynamics of Biomolecules

*Notes*

- ENGS 108, COSC 174, and QBS 108 are equivalent, and only one may be taken for credit.
- COSC 175 and QBS 175 are equivalent courses, and only one may be taken for credit.

## Biomedical Engineering

Biomedical engineering is the broad area of study in which engineers use an interdisciplinary approach to solve problems in the medical field, often associated with the interaction between living and non-living systems. The program is intended for engineers who want to add depth to their knowledge or acquire new specialized knowledge in biomedical engineering. The breadth of solution methodologies requires biomedical engineers to take a quantitative approach to system analysis in “traditional” engineering fields, while simultaneously employing a fundamental understanding of the relevant life sciences. Biomedical engineers should be prepared to design, build, test, and/or analyze biological systems, diagnostics, devices, and treatment modalities.

### Core Courses

- ENGS 111: Digital Image Processing
- ENGG 113: Image Visualization and Analysis
- ENGS 129: Biomedical Circuits and Systems
- ENGS 156: Heat, Mass and Momentum Transfer
- ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering
- ENGS 162: Basic Biological Circuit Engineering
- ENGS 165: Biomaterials
- ENGG 166: Quantitative Human Physiology
- ENGS 167: Medical Imaging
- ENGG 168: Biomedical Radiation Transport
- ENGS 169: Intermediate Biomedical Engineering
- ENGG 199: Advanced Imaging
- ENGS 262: Advanced Biological Circuit Engineering
- ENGG 325: Introduction to Surgical Innovation
- ENGG 365: Advanced Biomaterials

### Additional Courses

- ENGS 91: Numerical Methods in Computation
- ENGS 92: Fourier Transforms and Complex Variables
- ENGS 93: Statistical Methods in Engineering
- ENGS 105: Computational Methods for Partial Differential Equations I
- ENGS 108: Applied Machine Learning
- ENGS 110: Signal Processing

## Electrical Engineering

Electrical engineering leverages the fundamental principles surrounding electricity to advance today’s emerging technologies ranging from semiconductor devices to advanced communication networks, from self-powered sensors to electric cars, from wearable devices to cognitive medical imaging, and from autonomous vehicles to smart cities. Numerous subfields are found within this broad discipline, all of which are built on the foundations of mathematics and computer science, physical and life sciences, electromagnetics, electronics, and systems. The program is flexible, allowing the student either to focus on a single specialization, or to build an individualized curriculum from a combination of complementary subfields.

### Core Courses

#### Electronic Systems

- ENGS 125: Power Electronics and Electromechanical Energy Conversion
- ENGS 128: Advanced Digital System Design
- ENGS 129: Biomedical Circuits and Systems

#### Signal Processing

- ENGS 110: Signal Processing
- ENGS 111: Digital Image Processing
- ENGG 113: Image Visualization and Analysis
- ENGG 122: Image Visualization and Analysis
- ENGS 167: Medical Imaging

#### Nano/microelectronics

- ENGS 126: Analog Integrated Circuit Design
- ENGS 129: Biomedical Circuits and Systems
- ENGS 162: Basic Biological Circuit Engineering
- ENGS 262: Advanced Biological Circuit Engineering
- ENGG 324: Microstrip Lines and Circuits

#### Optics/Electromagnetics

- ENGS 120: Electromagnetic Waves: Analytical and Modeling Approaches
- ENGS 123: Optics
- ENGS 220: Electromagnetic Wave Theory

### Additional Courses

#### Electronic Systems

- ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering
- ENGS 169: Intermediate Biomedical Engineering
- ENGS 147: Mechatronics

#### Signal Processing

- ENGS 124: Networked Multi-Agent Systems
- ENGG 149: Introduction to Systems Identification
- ENGS 145: Modern Control Theory

#### Nano/microelectronics

#### Data Science

- ENGS 108: Applied Machine Learning
- COSC 174: Machine Learning and Statistical Data Analysis

*(Credit allowed for only one of COSC 174 or ENGS 108)* - COSC 178: Deep Learning

#### Mathematics

- ENGS 92: Fourier Transforms and Complex Variables
- ENGS 105: Computational Methods for Partial Differential Equations I Alt W
- ENGS 106: Numerical Linear Algebra
- PHYS 100: Mathematical Methods for Physicists Fall
- PHYS 105: Electromagnetic Theory I Winter
- PHYS 106: Electromagnetic Theory II Spring
- PHYS 110: Methods in Applied Mathematics II

## Energy Engineering

Energy is a major determinant of world events and quality of life. Energy engineering brings to bear the spectrum of engineering disciplines on challenges and opportunities involving energy, recognizing social, political, and economic contexts. This area of study aims to increase the efficiency of energy conversion, storage, transmission and utilization, to accelerate the transition to sustainable energy sources, and to improve access to and management of energy systems. Students are encouraged to develop depth in one or more technical areas along with a broad understanding of energy technologies, systems, challenges, and opportunities.

### Core Courses

- ENGS 171: Industrial Ecology
- ENGS 172: Climate Change and Engineering
- ENGG 173: Energy Utilization
- ENGS 174: Energy Conversion
- ENGS 175: Energy Systems

### Additional Courses

- ENGS 91: Numerical Methods in Computation
- ENGG 103: Operations Research
- ENGS 104: Optimization Methods for Engineering Applications
- ENGS 106: Numerical Linear Algebra
- ENGS 108: Applied Machine Learning
- ENGS 110: Signal Processing
- ENGS 114: Networked Multi-Agent Systems
- ENGS 115: Parallel Computing
- ENGS 145: Modern Control Theory
- ENGG 177: Decision-Making under Risk and Uncertainty
- ENGM 182: Data Analytics
- ENGG 199: Model-Based Systems Engineering, Analysis, and Simulation
- ENGS 202: Nonlinear Systems
- COSC 170: Numerical and Computational Tools for Applied Science
- COSC 174: Machine Learning and Statistical Data Analysis
- COSC 184: Mathematical Optimization and Modeling
- COSC 271: Numerical Linear Algebra

## Materials Science and Engineering

The study of materials science and engineering relates the properties of materials—chemical, electrical, magnetic, mechanical, optical—to their internal architecture or microstructure. In turn, structure is related to processing—solidification, thermal/mechanical treatment, vapor deposition etc.—and to the underlying thermodynamic "driving forces" and kinetics that cause changes in structure and hence in properties and behavior. Fundamental to the study are both qualitative and quantitative methods of microstructural analysis.

### Core Courses

- ENGS 130: Mechanical Behavior of Materials
- ENGS 131: Science of Solid State Materials
- ENGS 132: Thermodynamics and Kinetics in Condensed Phases
- ENGS 133: Methods of Materials Characterization
- ENGS 134: Nanotechnology
- ENGS 135: Thin Films and Microfabrication Technology
- ENGG 138: Corrosion and Degradation of Materials
- ENGS 165: Biomaterials
- ENGG 230: Fatigue and Fracture
- ENGG 332: Topics in Plastic Flow and Facture of Solids
- ENGG 339: Advanced Electron Microscopy
- ENGG 365: Advanced Biomaterials

### Additional Courses

- ENGS 91: Numerical Methods in Computation
- ENGS 93: Statistical Methods in Engineering
- ENGS 105: Computational Methods for Partial Differential Equations I
- ENGS 108: Applied Machine Learning
- ENGS 124: Optical Devices and Systems
- CHEM 101.2: Statistical Thermodynamics
- CHEM 101.4: Chemistry of Macromolecules

## Mechanical Engineering

Mechanical engineers apply principles of engineering to the design, analysis, and manufacture of machines ranging from power systems, industrial equipment, and vehicles to athletic equipment and medical devices. Mechanical engineering is one of the broadest engineering disciplines, and as such, mechanical engineering programs should include, but are not limited to, courses in mechanics, materials, dynamics, thermal and fluid systems, robotics, applied mathematics, systems and controls.

### Core Courses

- ENGS 130: Mechanical Behavior of Materials
- ENGS 142: Intermediate Solid Mechanics
- ENGS 145: Modern Control Theory
- ENGS 146: Computer Aided Mechanical Engineering Design
- ENGS 147: Mechatronics
- ENGG 148: Structural Mechanics
- ENGG 149: Introduction to Systems Identification
- ENGS 150: Intermediate Fluid Mechanics
- ENGS 155: Intermediate Thermodynamics
- ENGS 156: Heat, Mass and Momentum Transfer
- ENGG 240: Kinematics and Dynamics of Machinery