Courses
The Master of Advanced Study in Engineering (MAS-E) online program is completed in 22 one-unit courses and a two-unit capstone project. The academically rigorous micro-courses have pre-recorded lectures, and all materials are available online and designed for self-paced study.
Full-time students could complete the degree requirements in as little as nine months, while those enrolling part-time would typically take two- to four-years to complete the program.
Interdisciplinary themes
The MAS-E curriculum is organized into five interdisciplinary themes:
- Infrastructure Systems Engineering
- Biomedical and Biomechanical Engineering
- Engineering Data Analysis
- Advanced Manufacturing and Materials
- Electrical, Power and Autonomous Systems
Students must complete courses in four categories:
- Technical Foundation (9 units): 3 one-unit courses from 3 themes.
- Technical Depth (7 units): 7 units in a single theme
- Technical Breadth (6 units): 6 units outside technical depth theme
- Interdisciplinary Capstone Project (2 units): Integrates knowledge and skills
Altogether, the curriculum provides a comprehensive engineering education designed to enhance a student’s professional portfolio.
Course details
The courses listed are the planned course offerings starting in 2024. Not all classes will be offered each semester, and the list of available courses is subject to change. Please refer to the Berkeley Academic Guide for more information.
ENGIN 200: Ethics, Engineering, and Society
How can we identify and analyze ethical issues in engineering? How do we leave room for rapid and disruptive innovation while responsibly considering the impact of technology on society and identifying the new ethical challenges that arise? This course provides an introduction to how theories, concepts, and methods from the humanities and social science can be applied to ethical problems in engineering.
Instructor: Raluca O. Scarlat
ENGIN 210A: A First Course in Renewable Energy
This is an engineering introduction to renewable energy technologies and potentials. The course aims to introduce a general engineering/science audience to the basic concepts of renewable energy. Topics to be covered include Solar Energy, Ocean Energy, Wind Energy, and Geothermal Energy. Some mathematical criteria will be covered, e.g. Betz limit for wind, limit of WEC point absorber. Each lecture contains several examples from real world applications and in-progress industrial developments.
Instructor: Reza Alam
ENGIN 210B: Energy Systems Engineering
Climate change is arguably the preeminent issue of our time. The transition to a clean energy society can help avoid the worst impacts of climate change. The energy systems engineer’s role is to deeply understand the challenges and develop creative technical solutions. This course provides students with an introduction to the technical fundamentals of clean energy challenges and opportunities. Challenges include urbanization, renewable energy integration, and sectors that are difficult to decarbonize. Opportunities include clean energy generation technologies, energy storage, microgrids, and electrified transportation.
Instructor: Scott Moura
ENGIN 212: The Physics of Water-Enabled Technology
The physics of water flow is an enabling element in technologies both new and old. The physics concepts are familiar laws and straightforward principles, but however simple they are, they require very careful treatment to get meaningful results about water flow. This is because water, like all systems comprised of many small parts, shows patterns that emerge from the sum of many small motions and cannot be predicted easily from the basics. The challenge for a working engineer or manager is knowing when these “emergent” patterns can be reliably extrapolated from one system from another, when they can be controlled, and how they can be connected to the basic laws of physics when a “sanity check” is needed. This course attempts to do that by examining key principles in water physics through the lens of contemporary technology. This technology includes membranes, turbines, flow cytometers, treatment ponds, gas exchangers, and atomizers. This course works well alongside one on waves.
Instructor: Evan Variano
ENGIN 215A: Nuclear Energy and the Environment
Electricity production from nuclear energy is highly concentrated and free of green-house gasses. The pressure to decarbonize electricity generation is leading many to think of nuclear as a near term solution. Nevertheless, public opinion remains in general skeptical of nuclear. This course aims to familiarize students with nuclear energy, the way it is produced, and its overall environmental impact. The course will cover fundamental characteristics of nuclear energy, will provide students with a practical understanding of nuclear reactors, and will review the benefits and the challenges that nuclear energy can provide.
Instructor: Massimiliano Fratoni
ENGIN 216B: Soil Liquefaction 101
One of the leading causes of damage during earthquakes is soil liquefaction, and it can have devastating consequences on critical infrastructure such as dams, ports and other lifelines. This course will serve as a great introduction of the phenomenon of soil liquefaction, as well as go into details on simplified and advanced methods of analyses. Specifically, the phenomenon of soil liquefaction will be presented, as well as empirical and mechanistic methods to determine soil liquefaction triggering and post-liquefaction strength loss and its consequences for a range of materials (gravels, sands and silty soils). Laboratory and field testing to collect data that helps determine liquefaction triggering and post-liquefaction soil behavior (e.g. strength loss, dilation, and hardening) will be discussed. The state of the art with respect to numerical modelling of liquefaction will also be included, as well as relevant constitutive soil models. Finally, possible mitigation measures will be presented.
Instructor: Adda Athanasopoulos-Zekkos
ENGIN 217B: Ocean Engineering, A Crash Course
Ocean Engineering is gaining a renewed flood of attention as energy companies (oil, mining, renewables) eagerly look for extra resources in the oceans, entailing concerns about the environment and the planet. This course intends to introduce the basics of engineering principles for working in the area of ocean engineering. Specifically, topics of wave dynamics, wave, wind and current loads on ocean structures, and cables and mooring are covered. Each lecture is accompanied with examples from real-life problems, and for each subject a review of state of the art applications is provided through videos and presentations.
Instructor: Reza Alam
ENGIN 236A: Applied Data Science for Engineers
This course aims at providing basics of Data Science to students and professionals who need to work with and analyze a large volume of data. The base programming language is Matlab, but techniques taught, and topics covered can be coded in any programming language (examples from Python and Fortran will be discussed). The course is aimed at graduate students in engineering, and therefore examples, assignments and the course project are from real life scenarios and engineering problems.
Instructor: Reza Alam
ENGIN 238C: Applied Optimization
Optimization is a fascinating topic that finds applications across a wide array of disciplines, including finance, energy, data science, physical sciences, public policy, social science, and more. After completing the course, students will have an entirely new perspective on designing systems using mathematical optimization. Specifically, this course provides students with an introduction to mathematical optimization from the point-of-view of data science applications, e.g. mobility, energy, finance. Foundational concepts include optimization formulations, linear programming, quadratic programming, convex optimization, and machine learning.
Instructor: Scott Moura
ENGIN 245A: Resilient Structural Systems to Natural Hazard
This course emphasizes the background, theory, analysis, assessment, and design frameworks and engineering tools to achieve resiliency of smart structural systems. We focus on use of sensors, structural analyses, experimental methods, and probabilistic modeling and structural health monitoring using artificial intelligence tools. The concepts are holistically integrated towards a paradigm of resilient design engineering of sustainable critical infrastructure systems subjected to extreme and service conditions.
Course topics cover a variety of numerical methods, experimental methods, combination of numerical and experimental methods (hybrid simulation), structural health monitoring, structural reliability, decision making under uncertainty and deep learning. The course will empower the participants with the general multipurpose trans-disciplinary knowledge, background and tools needed for successful assessment and design of resilient structural and infrastructural systems in the face of natural hazards and extreme events.
Instructor: Khalid Mosalam
ENGIN 245C: Structural Fire Engineering
Topics are: 1) Model & simulate combustion & heat release for indoor & outdoor fires, 2) Perform heat transfer analysis for conduction, convection & radiation to calculate exposed structural elements temperature, 3) Develop material response for steel & concrete structural elements to fire, 4) Calculate mechanical response of structural elements & assemblies exposed to fire during expansion & weakening due to increasing temperatures, 5) Implement design approaches to mitigate the effects of fire on a structure, and 6) Understand current codes, standards & emerging technologies in structural fire engineering.
Instructors: Khalid Mosalam, Mohammadreza Eslami
ENGIN 247: An Introduction to Aerodynamics
This course aims at providing the basics of Aerodynamics for students and professionals who are considering the Aerospace industry as an academic focus area, a job target, or for those who are aircraft enthusiasts. A basic knowledge of mathematics (undergraduate level) is recommended for students to follow everything discussed in the course, but even without that the audience should be able to follow most of the course. Several experiments will be shown, and concepts are discussed with the help of videos of real-life scenarios, incidents and controlled-experiments.
Instructor: Reza Alam
ENGIN 250A: Analysis and Control of Nonlinear Systems
This course provides a basic introduction to nonlinear dynamical systems and their control. The first module begins with an overview of nonlinear system models, and types of behaviors that can only arise in nonlinear systems. It then introduces phase portraits for systems with two state variables, states basic existence and uniqueness results for solutions of ordinary differential equations, and concludes with sensitivity equations that allow one to evaluate the sensitivity of the solutions with respect to parameters and initial conditions. The second module introduces Lyapunov stability theory and Lyapunov functions. It proceeds to linearization as a method for determining local stability properties around operating points, and defines the notion of a region of attraction. The third module focuses on feedback control design for nonlinear systems, starting with backstepping as an example of Lyapunov-based feedback design to stabilize an operating point. It continues with input/output linearization for trajectory tracking, by first introducing requisite concepts such as relative degree. The fourth module introduces feedback linearization for stabilization, then proceeds to sliding mode control for stabilization in the presence of model uncertainty. The course will illustrate all concepts with physically-motivated examples, and will point to resources for further study.
Instructor: Murat Arcak
ENGIN 251: Model Predictive Control for Autonomous systems
Forecasts are fundamental in the new generation of autonomous and semi-autonomous systems. Predictions of systems dynamics, human behavior and environment conditions can improve safety and performance of the resulting system. Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy automotive, aerospace, process control and manufacturing. This course covers the basic design of SISO and MIMO and predictive feedback controllers for linear and nonlinear systems. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to self-driving cars and robotic manipulators.
Instructor: Francesco Borrelli
ENGIN 252: Legged Robots: How to make Robots Walk and Run
Bipedal robot locomotion is a challenging problem. This course will introduce students to the math behind bipedal legged robots. We will cover modeling and dynamics of legged robots, trajectory planning for designing walking and running gaits, and common control strategies to achieve the planned motions. The course will also include applied techniques of programming up a simulator with a dynamical model of a bipedal robot as well as a controller that stabilizes a walking gait. This short course will take students through every step of the process, including:
- Mathematical modeling of walking gaits in planar robots.
- Analysis of periodic orbits representing walking gaits.
- Algorithms for synthesizing feedback controllers for walking.
- Algorithms for optimizing energy-efficient walking gaits.
- Detailed simulation examples.
Instructor: Koushil Sreenath
ENGIN 254: Model Predictive Control for Energy systems
Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy, automotive, aerospace, process control and manufacturing. Forecasts are fundamental in the new generation of autonomous and semi-autonomous energy systems. This course covers the basic design of applied predictive control. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to renewable energy systems including solar power plants, energy storage systems and Heating, Ventilation and Air Conditioning (HVAC).
Instructor: Francesco Borrelli
ENGIN 282: Techniques for Electronic Devices Fabrication
This course is designed to give an introduction, and overview of, the techniques used in fabrication of electronic devices. Topics such as materials deposition, patterning, laboratory safety and best practices will be covered. The students will learn basic processes used in the fabrication of silicon-based devices and novel semiconducting materials. After covering the fundamental processes and technologies needed to form an electronic device, the fabrication flow of NMOS devices will be studied in detail.
Instructor: Ana Claudia Arias
ENGIN 291A: Introspective and Authentic Leadership
This course provides the framework for personal leadership development. The class comprises three parts: (I) Exploration of your leadership journey; (II) Discovery of your personal leadership style; and (III) Development of a personal leadership plan. Topics include identification of personal crucibles, moral compass, ethical decision-making, conflict resolution, navigation of difficult conversations, positive psychology, growth mind-set, teamwork and development of personal leadership plans. Students engage in weekly reflections and introspective exercises.
Instructor: Lisa Pruitt
ENGIN 200: Ethics, Engineering, and Society
How can we identify and analyze ethical issues in engineering? How do we leave room for rapid and disruptive innovation while responsibly considering the impact of technology on society and identifying the new ethical challenges that arise? This course provides an introduction to how theories, concepts, and methods from the humanities and social science can be applied to ethical problems in engineering.
Instructor: Raluca O. Scarlat
ENGIN 202B: Designing for the Human Body
Students will learn how the body transfers loads during daily activities and how external or internal device design can have a long-term impact on body biomechanical function. Some examples include the impact of phone use and forward flexion of the neck and asymmetrical spinal loading due to shoulder bags (e.g., impact on factory workers or military personnel). The role of human-centered design on internal and external devices will be presented through case studies. Lastly, the impact of data from novel portable measurement tools that can be incorporated into wearable devices will be discussed, with a specific focus on disease monitoring, prevention, and early detection.
Instructor: Grace O’Connell
ENGIN 222: Molecular Imaging Methods for R&D and Clinical Trials
This course is designed as an introduction to the growing world of molecular imaging in medicine and research. The current confluence of increased understanding of how genetic differences mitigate drug response, alongside substantial innovation in targeted molecular therapeutics including gene editing approaches, represents an inflection point for the use of molecular imaging.
This course will provide individuals with fundamental understandings of medical imaging modalities that are used in both R&D and clinical settings. Building upon this framework, corresponding methods for targeted molecular imaging including contrast mechanisms and probe design will provide direct relevance to current needs for high throughput in vivo efficacy measurements. Quantitative methods for image analysis will be taught in the context of real world disease targeted applications using published data from recent clinical trials.
Instructor: Moriel Vandsburger
ENGIN 223: Radiopharmaceuticals: From Radiation Biophysics to Clinic
This is an introductory course to the science behind radiopharmaceutical development and use. It will also cover emerging topics in the field, including new exciting methods for disease treatment and diagnosis. The course is tailored to a broad audience.
Instructor: Rebecca Abergel
ENGIN 224B: Introduction to Neurophysiology
The brain is the most spectacular yet most mysterious organ in our body. It controls every action we make, determines who we are and exceeds in its capacity any existing computer. The course will provide students with a detailed description of the basic principles of brain function, i.e., neurophysiology. The course will start from the cellular resolution and expand into a systems-wide view (such as vision, auditory, motor, memory systems) while underscoring shared neurophysiological principles. Furthermore, the course will provide students with real-life examples of clinical conditions that are associated with malfunctions in those systems as well as examples of solutions that were derived to treat physiological deficits in them.
Instructor: Michael Yartsev
ENGIN 264: An Introduction to Continuum Mechanics and Modern Applications
Continuum mechanics is a powerful method of modeling physical systems of a very large variety. In this course students will learn the basic elements for describing system state and how balance laws are formulated to ensure correct system response. The developed methodology will first be applied to basic problems in elasticity, followed by application to poroelastic systems, batteries, and piezoelectric material systems.
The foundations gained from this course will allow students to understand how continua, both simple and complex, are properly modeled. It will set them up to be able to formulate continuum mechanical problems and it will allow them to more fully understand numerical solutions that are arrived at via modern computational methods, such as the finite element method. This course sets students up for the ability to contribute a sophisticated perspective on modeling questions that arise in a wide variety of engineering problem classes.
Instructor: Sanjay Govindjee
ENGIN 291A: Introspective and Authentic Leadership
This course provides the framework for personal leadership development. The class comprises three parts: (I) Exploration of your leadership journey; (II) Discovery of your personal leadership style; and (III) Development of a personal leadership plan. Topics include identification of personal crucibles, moral compass, ethical decision-making, conflict resolution, navigation of difficult conversations, positive psychology, growth mind-set, teamwork and development of personal leadership plans. Students engage in weekly reflections and introspective exercises.
Instructor: Lisa Pruitt
ENGIN 200: Ethics, Engineering, and Society
How can we identify and analyze ethical issues in engineering? How do we leave room for rapid and disruptive innovation while responsibly considering the impact of technology on society and identifying the new ethical challenges that arise? This course provides an introduction to how theories, concepts, and methods from the humanities and social science can be applied to ethical problems in engineering.
Instructor: Raluca O. Scarlat
ENGIN 210A: A First Course in Renewable Energy
This is an engineering introduction to renewable energy technologies and potentials. The course aims to introduce a general engineering/science audience to the basic concepts of renewable energy. Topics to be covered include Solar Energy, Ocean Energy, Wind Energy, and Geothermal Energy. Some mathematical criteria will be covered, e.g. Betz limit for wind, limit of WEC point absorber. Each lecture contains several examples from real world applications and in-progress industrial developments.
Instructor: Reza Alam
ENGIN 217B: Ocean Engineering, A Crash Course
Ocean Engineering is gaining a renewed flood of attention as energy companies (oil, mining, renewables) eagerly look for extra resources in the oceans, entailing concerns about the environment and the planet. This course intends to introduce the basics of engineering principles for working in the area of ocean engineering. Specifically, topics of wave dynamics, wave, wind and current loads on ocean structures, and cables and mooring are covered. Each lecture is accompanied with examples from real-life problems, and for each subject a review of state of the art applications is provided through videos and presentations.
Instructor: Reza Alam
ENGIN 232: Fundamental Data Structures
In this course, Fundamental Data Structures, students will learn about the foundational data structures used by almost all programming languages. Rather than simply presenting these data structures as fait accompli, we will start from scratch, working together to develop the beautiful and important ideas that result. The course assumes familiarity with the Java Programming language, which is covered in the course ENGIN 234 “Introduction to Java and Software Engineering.”
Instructor: Josh Hug
ENGIN 234: Introduction to Java and Software Engineering
The Introduction to Java and Software Engineering course provides important principles and techniques that you can use to minimize overall development and maintenance time when writing computer programs. To that end, we introduce the Java programming language, a widely used programming language that supports these best practices, though these practices can be applied in other languages as well. The course assumes familiarity with at least one programming language, not necessarily Java.
Instructor: Josh Hug
ENGIN 235A: Python for Engineers
In recent years Python has emerged as an indispensable programming language for engineers, both practicing and academic, as well as data scientists, web developers, and many others. However the language is vast and includes many features that are not immediately relevant to most engineers. The goal of this course is to help students to quickly gain a foothold with the parts of the language that they are most likely to use. We will begin with a high-level description of Python and how it differs (both in syntax and in philosophy) from other popular programming languages. We will learn about Python’s extensive offering of libraries, starting with the standard library, and including Numpy and Pandas. We will set up our programming environment with Anaconda, Jupyter, and Spyder. We will then delve into the basic constructs of the language (data types, program flow, etc). We will also cover code organization and object-oriented programming. As well, we will begin using numerical libraries such as Numpy and Pandas to solve more advanced problems. The course will be suffused with demonstrations of the concepts, and sample visualizations created with Matplotlib.
Instructor: Gabriel Gomes
ENGIN 236A: Applied Data Science for Engineers
This course aims at providing basics of Data Science to students and professionals who need to work with and analyze a large volume of data. The base programming language is Matlab, but techniques taught, and topics covered can be coded in any programming language (examples from Python and Fortran will be discussed). The course is aimed at graduate students in engineering, and therefore examples, assignments and the course project are from real life scenarios and engineering problems.
Instructor: Reza Alam
ENGIN 236B: Data Science and Machine Learning Fundamentals
The Data Science and Machine Learning Fundamentals course provides an introduction to machine learning in the context of data science. By the end of the course, students will know how to clean, visualize, and model real world datasets using basic machine learning techniques. The course assumes a familiarity with the Python programming language.
Instructor: Josh Hug
ENGIN 237A: An Introduction to the Basics of Machine Learning
This course will introduce linear algebra, and cover some fundamental algorithms in machine learning including least squares, orthogonal matching pursuit and ridge regression. We will talk about the concepts of validation and testing. This is not intended to be an advanced machine learning course, but more a mathematical course to build out the basic background.
Instructor: Gireeja Ranade
ENGIN 238B: Optimization Theory and Practice
Optimization theory concerns the selection of a best option from a set of available options. Formulating an optimization problem involves describing the feasible set as well as prescribing a notion of “best”. This setup, although simple, is one of the most important and widespread ideas in engineering and the sciences.
This course will begin by demonstrating the use of optimization theory in many contexts. The student will learn the standard categorization of optimization problems, and the mathematical and numerical tools available in each category. The second module of the course will delve into the class of tractable “convex” problems. We will learn about special cases, applications in the real world, and available solution techniques. In the third module we will review more advanced topics: optimization theory for steering dynamical systems (optimal control), training of data-based models with optimization (machine learning), and solving non-convex problems with genetic algorithms.
Instructor: Gabriel Gomes
ENGIN 245A: Resilient Structural Systems to Natural Hazard
This course emphasizes the background, theory, analysis, assessment, and design frameworks and engineering tools to achieve resiliency of smart structural systems. We focus on use of sensors, structural analyses, experimental methods, and probabilistic modeling and structural health monitoring using artificial intelligence tools. The concepts are holistically integrated towards a paradigm of resilient design engineering of sustainable critical infrastructure systems subjected to extreme and service conditions.
Course topics cover a variety of numerical methods, experimental methods, combination of numerical and experimental methods (hybrid simulation), structural health monitoring, structural reliability, decision making under uncertainty and deep learning. The course will empower the participants with the general multipurpose trans-disciplinary knowledge, background and tools needed for successful assessment and design of resilient structural and infrastructural systems in the face of natural hazards and extreme events.
Instructor: Khalid Mosalam
ENGIN 245C: Structural Fire Engineering
This course is focused on the design and assessment of structures subjected to fire. The course material emphasizes a 3-phase approach to structural-fire engineering: (1) fire modeling, (2) heat transfer modeling, and (3) structural modeling. Students will become familiar with both current prescriptive approaches to structural-fire engineering and emerging performance-based design approaches. Students will be able to appreciate several important topics related to performance of structures under the effect of fires.
Topics are: 1) Model & simulate combustion & heat release for indoor & outdoor fires, 2) Perform heat transfer analysis for conduction, convection & radiation to calculate exposed structural elements temperature, 3) Develop material response for steel & concrete structural elements to fire, 4) Calculate mechanical response of structural elements & assemblies exposed to fire during expansion & weakening due to increasing temperatures, 5) Implement design approaches to mitigate the effects of fire on a structure, and 6) Understand current codes, standards & emerging technologies in structural fire engineering.
Instructors: Khalid Mosalam, Mohammadreza Eslami
ENGIN 247: An Introduction to Aerodynamics
This course aims at providing the basics of Aerodynamics for students and professionals who are considering the Aerospace industry as an academic focus area, a job target, or for those who are aircraft enthusiasts. A basic knowledge of mathematics (undergraduate level) is recommended for students to follow everything discussed in the course, but even without that the audience should be able to follow most of the course. Several experiments will be shown, and concepts are discussed with the help of videos of real-life scenarios, incidents and controlled-experiments.
Instructor: Reza Alam
ENGIN 250: Feedback Control for Linear Systems
This course provides an overview of the basic concepts in linear systems and feedback control. The course begins with an exploration of the feedback control problem and its applications in various fields: robotics, manufacturing, traffic, etc. We will present the unifying mathematical formulation of the problem, as well as its fundamental concepts: equilibrium and stability. We then explore the application of these concepts to linear systems and the role of linear algebra. With a grasp of the range of possible behaviors of linear time-invariant systems, we proceed to the design of feedback controllers.
In the second session of the course we talk about output feedback techniques. We consider the influence of proportional and integral action, and we put these together in a worked example using proportional integral derivative (PID) control. This example illustrates the limits of PID and motivates the third session on state feedback methods.
In the third session we describe the pole placement approach to state feedback, and couple it with the analogous state estimator. We briefly discuss observability and controllability as prerequisites for this design approach. We end the course by solving the example of the previous session with state feedback techniques, and motivating other advanced topics in control theory.
Instructor: Gabriel Gomes
ENGIN 250A: Analysis and Control of Nonlinear Systems
This course provides a basic introduction to nonlinear dynamical systems and their control. The first module begins with an overview of nonlinear system models, and types of behaviors that can only arise in nonlinear systems. It then introduces phase portraits for systems with two state variables, states basic existence and uniqueness results for solutions of ordinary differential equations, and concludes with sensitivity equations that allow one to evaluate the sensitivity of the solutions with respect to parameters and initial conditions. The second module introduces Lyapunov stability theory and Lyapunov functions. It proceeds to linearization as a method for determining local stability properties around operating points, and defines the notion of a region of attraction. The third module focuses on feedback control design for nonlinear systems, starting with backstepping as an example of Lyapunov-based feedback design to stabilize an operating point. It continues with input/output linearization for trajectory tracking, by first introducing requisite concepts such as relative degree. The fourth module introduces feedback linearization for stabilization, then proceeds to sliding mode control for stabilization in the presence of model uncertainty. The course will illustrate all concepts with physically-motivated examples, and will point to resources for further study.
Instructor: Murat Arcak
ENGIN 251: Model Predictive Control for Autonomous systems
Forecasts are fundamental in the new generation of autonomous and semi-autonomous systems. Predictions of systems dynamics, human behavior and environment conditions can improve safety and performance of the resulting system. Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy automotive, aerospace, process control and manufacturing. This course covers the basic design of SISO and MIMO and predictive feedback controllers for linear and nonlinear systems. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to self-driving cars and robotic manipulators.
Instructor: Francesco Borrelli
ENGIN 252: Legged Robots: How to make Robots Walk and Run
Bipedal robot locomotion is a challenging problem. This course will introduce students to the math behind bipedal legged robots. We will cover modeling and dynamics of legged robots, trajectory planning for designing walking and running gaits, and common control strategies to achieve the planned motions. The course will also include applied techniques of programming up a simulator with a dynamical model of a bipedal robot as well as a controller that stabilizes a walking gait. This short course will take students through every step of the process, including:
- Mathematical modeling of walking gaits in planar robots.
- Analysis of periodic orbits representing walking gaits.
- Algorithms for synthesizing feedback controllers for walking.
- Algorithms for optimizing energy-efficient walking gaits.
- Detailed simulation examples.
Instructor: Koushil Sreenath
ENGIN 254: Model Predictive Control for Energy systems
Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy, automotive, aerospace, process control and manufacturing. Forecasts are fundamental in the new generation of autonomous and semi-autonomous energy systems. This course covers the basic design of applied predictive control. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to renewable energy systems including solar power plants, energy storage systems and Heating, Ventilation and Air Conditioning (HVAC).
Instructor: Francesco Borrelli
ENGIN 291A: Introspective and Authentic Leadership
This course provides the framework for personal leadership development. The class comprises three parts: (I) Exploration of your leadership journey; (II) Discovery of your personal leadership style; and (III) Development of a personal leadership plan. Topics include identification of personal crucibles, moral compass, ethical decision-making, conflict resolution, navigation of difficult conversations, positive psychology, growth mind-set, teamwork and development of personal leadership plans. Students engage in weekly reflections and introspective exercises.
Instructor: Lisa Pruitt
ENGIN 200: Ethics, Engineering, and Society
How can we identify and analyze ethical issues in engineering? How do we leave room for rapid and disruptive innovation while responsibly considering the impact of technology on society and identifying the new ethical challenges that arise? This course provides an introduction to how theories, concepts, and methods from the humanities and social science can be applied to ethical problems in engineering.
Instructor: Raluca O. Scarlat
ENGIN 202A: Introduction to Design Methodology
This course provides an introduction to design methods used in the development of innovative and realistic customer-driven engineered products, services, and systems. Design methods and tools are introduced and the student’s design ability is developed via a series of short design process modules: design research, analysis and synthesis, concept generation and creativity. Students will be expected to use tools and methods of professional practice to consider the social, economic and environmental implications of their products, services, or systems. There is an emphasis on hands-on innovative thinking and professional practice.
Instructor: Kosa Goucher-Lambert
ENGIN 202B: Designing for the Human Body
Students will learn how the body transfers loads during daily activities and how external or internal device design can have a long-term impact on body biomechanical function. Some examples include the impact of phone use and forward flexion of the neck and asymmetrical spinal loading due to shoulder bags (e.g., impact on factory workers or military personnel). The role of human-centered design on internal and external devices will be presented through case studies. Lastly, the impact of data from novel portable measurement tools that can be incorporated into wearable devices will be discussed, with a specific focus on disease monitoring, prevention, and early detection.
Instructor: Grace O’Connell
ENGIN 204A: Digital Transformation and Industry 4.0
The purpose of this course is to make the student fluent with the context, concepts and key content of the technologies that are driving what is collectively known as “Digital Transformation” (DT), and more specifically, focus on the industrial impact of DT, as captured under the term “Industry 4.0” (I4.0). This topic is quite important: for millennia we have improved our circumstances by managing our material surroundings: tools, shelter, supplies, land. Access to information is meant to enhance our efficiency in doing so, and dwindling resources, impeding climate change, and geopolitical strife are now stressing our planet. But this will not be a course in sociology, economics or geopolitics. Rather, it will be an engineering course, taught in these contexts.
Instructor: Costas Spanos
ENGIN 211B: Manufacturing in a Climate Emergency
The current rapid evolution of manufacturing technology is reshaping where, when, and by whom objects are produced. In particular, the emergence of increasingly sophisticated additive manufacturing processes, coupled with greater automation, mean that mass customization, decentralized production and more complex geometries and material combinations are now more attainable than ever before. The environmental impacts of these new ways of transforming material are challenging to quantify and are subject to a wide range of differing opinions and assumptions. This course provides participants with a framework for critically analyzing new processing routes, so that decisions can be made with a clearer view of their implications for energy consumption, recyclability, and consumption of finite resources.
Instructor: Hayden Taylor
ENGIN 241A: Introduction to structural materials I
This course takes the students from atomic arrangements, to crystal structure, grain structure, texture, defects in materials, and finally to thermodynamic assessment of materials microstructure. The main focus is on metallic materials with steel metallurgy and steel classification being commonly used to demonstrate course content, while an introduction to ceramics are provided. Basic introduction in materials characterization is provided to give the students the background necessary to distinguish different materials in use.
Instructors: Peter Hosemann, Matthew Sherburne
ENGIN 241B: Introduction to structural materials II
This class builds upon the 241A “Introduction to Structural Materials 1” class and expands towards diffusion, phase diagrams, phase transformation, solidification, and alloy systems. Examples include steels, aluminum and titanium alloys. Furthermore, composite materials and ceramics are featured for high performance applications.
Instructors: Peter Hosemann, Matthew Sherburne
ENGIN 264: An Introduction to Continuum Mechanics and Modern Applications
Continuum mechanics is a powerful method of modeling physical systems of a very large variety. In this course students will learn the basic elements for describing system state and how balance laws are formulated to ensure correct system response. The developed methodology will first be applied to basic problems in elasticity, followed by application to poroelastic systems, batteries, and piezoelectric material systems.
The foundations gained from this course will allow students to understand how continua, both simple and complex, are properly modeled. It will set them up to be able to formulate continuum mechanical problems and it will allow them to more fully understand numerical solutions that are arrived at via modern computational methods, such as the finite element method. This course sets students up for the ability to contribute a sophisticated perspective on modeling questions that arise in a wide variety of engineering problem classes.
Instructor: Sanjay Govindjee
ENGIN 280A: Electronic properties of materials
Introduction to the physical principles underlying the electronic properties of solids from macroscopic to nano dimensions. General solid state physics will be taught in the context of technological applications, including the structure of solids, behavior of electrons and atomic vibration in periodic lattice, and interaction of light with solids. Emphasis will be on semiconductors and the materials physics of electronic and optoelectronic devices.
Instructor: Junqiao Wu
ENGIN 280E: Photovoltaic Materials
This course focuses on the fundamentals of photovoltaic energy conversion with respect to the physical principles of operation and design of efficient semiconductor solar cell devices. This course aims to equip students with the concepts and analytical skills necessary to assess the utility and viability of various modern photovoltaic technologies in the context of a growing global renewable energy market.
Instructors: Zakaria Al Balushi, Matthew Sherburne
ENGIN 281: Thin Film Science for Materials Sci. & Elec. Eng.
This course covers the materials science and processing of thin film coatings that incorporates fundamental knowledge of materials transport, accumulation, defects and epitaxy. Through this course, an understanding of the fundamental physical and chemical processes which are involved in crystal growth and thin film fabrication will be gained. Important synthesis and processing techniques used for the fabrication of electronic and photonic devices will be discussed. Finally, this course will provide an understanding of how material characteristics are influenced by processing and deposition conditions. This course is designed to directly address current challenges and future needs of the semiconductor and coating industries.
Instructors: Zakaria Al Balushi, Matthew Sherburne
ENGIN 291A: Introspective and Authentic Leadership
This course provides the framework for personal leadership development. The class comprises three parts: (I) Exploration of your leadership journey; (II) Discovery of your personal leadership style; and (III) Development of a personal leadership plan. Topics include identification of personal crucibles, moral compass, ethical decision-making, conflict resolution, navigation of difficult conversations, positive psychology, growth mind-set, teamwork and development of personal leadership plans. Students engage in weekly reflections and introspective exercises.
Instructor: Lisa Pruitt
ENGIN 200: Ethics, Engineering, and Society
How can we identify and analyze ethical issues in engineering? How do we leave room for rapid and disruptive innovation while responsibly considering the impact of technology on society and identifying the new ethical challenges that arise? This course provides an introduction to how theories, concepts, and methods from the humanities and social science can be applied to ethical problems in engineering.
Instructor: Raluca O. Scarlat
ENGIN 210B: Energy Systems Engineering
Climate change is arguably the preeminent issue of our time. The transition to a clean energy society can help avoid the worst impacts of climate change. The energy systems engineer’s role is to deeply understand the challenges and develop creative technical solutions. This course provides students with an introduction to the technical fundamentals of clean energy challenges and opportunities. Challenges include urbanization, renewable energy integration, and sectors that are difficult to decarbonize. Opportunities include clean energy generation technologies, energy storage, microgrids, and electrified transportation.
Instructor: Scott Moura
ENGIN 238C: Applied Optimization
Optimization is a fascinating topic that finds applications across a wide array of disciplines, including finance, energy, data science, physical sciences, public policy, social science, and more. After completing the course, students will have an entirely new perspective on designing systems using mathematical optimization. Specifically, this course provides students with an introduction to mathematical optimization from the point-of-view of data science applications, e.g. mobility, energy, finance. Foundational concepts include optimization formulations, linear programming, quadratic programming, convex optimization, and machine learning.
Instructor: Scott Moura
ENGIN 250A: Analysis and Control of Nonlinear Systems
This course provides a basic introduction to nonlinear dynamical systems and their control. The first module begins with an overview of nonlinear system models, and types of behaviors that can only arise in nonlinear systems. It then introduces phase portraits for systems with two state variables, states basic existence and uniqueness results for solutions of ordinary differential equations, and concludes with sensitivity equations that allow one to evaluate the sensitivity of the solutions with respect to parameters and initial conditions. The second module introduces Lyapunov stability theory and Lyapunov functions. It proceeds to linearization as a method for determining local stability properties around operating points, and defines the notion of a region of attraction. The third module focuses on feedback control design for nonlinear systems, starting with backstepping as an example of Lyapunov-based feedback design to stabilize an operating point. It continues with input/output linearization for trajectory tracking, by first introducing requisite concepts such as relative degree. The fourth module introduces feedback linearization for stabilization, then proceeds to sliding mode control for stabilization in the presence of model uncertainty. The course will illustrate all concepts with physically-motivated examples, and will point to resources for further study.
Instructor: Murat Arcak
ENGIN 251: Model Predictive Control for Autonomous systems
Forecasts are fundamental in the new generation of autonomous and semi-autonomous systems. Predictions of systems dynamics, human behavior and environment conditions can improve safety and performance of the resulting system. Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy automotive, aerospace, process control and manufacturing. This course covers the basic design of SISO and MIMO and predictive feedback controllers for linear and nonlinear systems. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to self-driving cars and robotic manipulators.
Instructor: Francesco Borrelli
ENGIN 252: Legged Robots: How to make Robots Walk and Run
Bipedal robot locomotion is a challenging problem. This course will introduce students to the math behind bipedal legged robots. We will cover modeling and dynamics of legged robots, trajectory planning for designing walking and running gaits, and common control strategies to achieve the planned motions. The course will also include applied techniques of programming up a simulator with a dynamical model of a bipedal robot as well as a controller that stabilizes a walking gait. This short course will take students through every step of the process, including:
- Mathematical modeling of walking gaits in planar robots.
- Analysis of periodic orbits representing walking gaits.
- Algorithms for synthesizing feedback controllers for walking.
- Algorithms for optimizing energy-efficient walking gaits.
- Detailed simulation examples.
Instructor: Koushil Sreenath
ENGIN 253: Flying Robots: from Small Drones to Aerial Taxis
Aerial robots are increasingly becoming part of our daily lives. This course is aimed at a broad audience, and intends to give an introduction to the main considerations made when designing aerial robots. We will consider sizes ranging from less than 1 kilogram to vehicles that can carry multiple passengers. Using simple physics, we will derive some fundamental constraints and trade-offs. We will also discuss autonomy of such systems, and specifically different components used in the sense-decide-act feedback control loop.
Instructor: Mark Mueller
ENGIN 254: Model Predictive Control for Energy systems
Predictive control is the discipline of feedback control where forecasts are used to change in real time the behavior of a dynamical system. Optimization-based control design is a highly requested skill from a number of industries, including energy, automotive, aerospace, process control and manufacturing. Forecasts are fundamental in the new generation of autonomous and semi-autonomous energy systems. This course covers the basic design of applied predictive control. The student will be exposed to how to apply predictive control design and analysis tools to classical and modern control problems with application to renewable energy systems including solar power plants, energy storage systems and Heating, Ventilation and Air Conditioning (HVAC).
Instructor: Francesco Borrelli
ENGIN 280A: Electronic properties of materials
Introduction to the physical principles underlying the electronic properties of solids from macroscopic to nano dimensions. General solid state physics will be taught in the context of technological applications, including the structure of solids, behavior of electrons and atomic vibration in periodic lattice, and interaction of light with solids. Emphasis will be on semiconductors and the materials physics of electronic and optoelectronic devices.
Instructor: Junqiao Wu
ENGIN 280E: Photovoltaic Materials
This course focuses on the fundamentals of photovoltaic energy conversion with respect to the physical principles of operation and design of efficient semiconductor solar cell devices. This course aims to equip students with the concepts and analytical skills necessary to assess the utility and viability of various modern photovoltaic technologies in the context of a growing global renewable energy market.
Instructors: Zakaria Al Balushi, Matthew Sherburne
ENGIN 281: Thin Film Science for Materials Sci. & Elec. Eng.
This course covers the materials science and processing of thin film coatings that incorporates fundamental knowledge of materials transport, accumulation, defects and epitaxy. Through this course, an understanding of the fundamental physical and chemical processes which are involved in crystal growth and thin film fabrication will be gained. Important synthesis and processing techniques used for the fabrication of electronic and photonic devices will be discussed. Finally, this course will provide an understanding of how material characteristics are influenced by processing and deposition conditions. This course is designed to directly address current challenges and future needs of the semiconductor and coating industries.
Instructors: Zakaria Al Balushi, Matthew Sherburne
ENGIN 282: Techniques for Electronic Devices Fabrication
This course is designed to give an introduction, and overview of, the techniques used in fabrication of electronic devices. Topics such as materials deposition, patterning, laboratory safety and best practices will be covered. The students will learn basic processes used in the fabrication of silicon-based devices and novel semiconducting materials. After covering the fundamental processes and technologies needed to form an electronic device, the fabrication flow of NMOS devices will be studied in detail.
Instructor: Ana Claudia Arias
ENGIN 291A: Introspective and Authentic Leadership
This course provides the framework for personal leadership development. The class comprises three parts: (I) Exploration of your leadership journey; (II) Discovery of your personal leadership style; and (III) Development of a personal leadership plan. Topics include identification of personal crucibles, moral compass, ethical decision-making, conflict resolution, navigation of difficult conversations, positive psychology, growth mind-set, teamwork and development of personal leadership plans. Students engage in weekly reflections and introspective exercises.
Instructor: Lisa Pruitt