This project-based course will introduce the physical concepts that can be applied to various human athletic endeavors. Students will focus on analyzing the dynamics of a specific sport/ physical activity through a project that they develop. This will allow students to construct physical models with an increasing level of realism that can used to analyze sporting events. Mathematics is the language of physics, and its use will be ever-present throughout the semester. However, we will focus more on the application of the laws of physics to understand the world of athletics. Students will learn the use of motion trackers and sensors to analyze motion in its dynamical and kinematic aspects.

Microorganisms produce a diverse array of specialized small molecules as part of their metabolic processes. In this course we will study the production, properties, and characterization of these molecules through the lens of food fermentation. In particular, we will focus on the small molecules that contribute taste and aroma in fermented foods. Students will experience the scientific inquiry process in a creative way by designing and implementing their own research project based on a fermented food of their choosing. Still a field with much potential for discovery, interested students are invited to continue their research project in the summer.

The main course objectives are to introduce students to the exciting and powerful world of electrical engineering and to explain how gadgets that we use every day actually work. After taking ES 50, you will be able to leverage the power of electricity to build systems that sense, control and program the physical world around you. Examples include intelligent and autonomous systems (robots), audio amplifiers (e.g. guitar amp), interactive art installations, light-shows, mind-controlled machines, and so on.

An introductory course in the design, fabrication, and assembly of mechanical and electromechanical devices. Topics include: Engineering graphics and tolerances; Structural design and material selection; Machine elements and two-dimensional mechanisms; DC motors; Design methodology. Emphasis on hands-on work and team design projects using professional solid modeling CAD software and numerically controlled machine tools.

An introductory course in the design, fabrication, and assembly of mechanical and electromechanical devices. Topics include: Engineering graphics and tolerances; Structural design and material selection; Machine elements and two-dimensional mechanisms; DC motors; Design methodology. Emphasis on hands-on work and team design projects using professional solid modeling CAD software and numerically controlled machine tools.

Guided reading and research.

Guided reading and research.

Entrepreneurship is increasingly transforming our society and economy. This course aims to provide for undergraduates an introduction to entrepreneurship and its implications for innovation. The class will primarily consist of case study discussions, but will include some traditional lecture sessions that build on academic papers to provide more frameworks. As such, it draws primarily on materials from the introductory MBA course at Harvard Business School, “The Entrepreneurial Manager” (TEM). Students will be expected to come to class prepared to discuss the cases.

Entrepreneurship is increasingly transforming our society and economy. This course aims to provide for undergraduates an introduction to entrepreneurship and its implications for innovation. The class will primarily consist of case study discussions, but will include some traditional lecture sessions that build on academic papers to provide more frameworks. As such, it draws primarily on materials from the introductory MBA course at Harvard Business School, “The Entrepreneurial Manager” (TEM). Students will be expected to come to class prepared to discuss the cases.

Entrepreneurship is increasingly transforming our society and economy. This course aims to provide for undergraduates an introduction to entrepreneurship and its implications for innovation. The class will primarily consist of case study discussions, but will include some traditional lecture sessions that build on academic papers to provide more frameworks. As such, it draws primarily on materials from the introductory MBA course at Harvard Business School, “The Entrepreneurial Manager” (TEM). Students will be expected to come to class prepared to discuss the cases.

Students do field-based work in entrepreneurship to develop their existing startup and explore new ideas and opportunities for startup creation. The course is for student-founders seeking to advance their innovation experience in a supportive community of peer founders. Students may work individually; teams with a working history are preferred. Requires self-directed, independent work and active outreach to mentors, customers, and partners for guidance and feedback in addition to that provided by the instructor and teaching staff.  Students share their work regularly and engage in a peer-to-peer feedback forum. Coursework is customized to the needs of each student and their startup role and includes development of product, technology, market, business, organization and leadership. See: https://tech.seas.harvard.edu/rad to apply for instructor permission to enroll.

Students do field-based work in entrepreneurship to develop their existing startup and explore new ideas and opportunities for startup creation. The course is for student-founders seeking to advance their innovation experience in a supportive community of peer founders. Students may work individually; teams with a working history are preferred. Requires self-directed, independent work and active outreach to mentors, customers, and partners for guidance and feedback in addition to that provided by the instructor and teaching staff.  Students share their work regularly and engage in a peer-to-peer feedback forum. Coursework is customized to the needs of each student and their startup role and includes development of product, technology, market, business, organization and leadership. See: https://tech.seas.harvard.edu/rad to apply for instructor permission to enroll.

Semester-long team-based project providing experience working with clients on complex multi-stakeholders real problems. Course provides exposure to problem definition, problem framing, qualitative and quantitative research methods, modeling, generation and co-design of creative solutions, engineering design trade-offs, and documentation/communication skills. Ordinarily taken in the junior year.

Semester-long team-based project providing experience working with clients on complex multi-stakeholders real problems. Course provides exposure to problem definition, problem framing, qualitative and quantitative research methods, modeling, generation and co-design of creative solutions, engineering design trade-offs, and documentation/communication skills. Ordinarily taken in the junior year.

Individual engineering design projects which demonstrate mastery of engineering knowledge and techniques. Each student will pursue an appropriate capstone project which involves both engineering design and quantitative analysis. This culminates in a final oral presentation and final report/thesis. Students must complete both parts of this course, fall and spring, in order to receive credit.

Individual engineering design projects which demonstrate mastery of engineering knowledge and techniques. Each student will pursue an appropriate capstone project which involves both engineering design and quantitative analysis. This culminates in a final oral presentation and final report/thesis. Students must complete both parts of this course, fall and spring, in order to receive credit.

Multi-year long team projects that provide an engineering experience working with partner communities on real-world problems. Projects provide exposure to problem definition, quantitative analysis, modeling, generation of creative solutions utilizing appropriate technology, engineering design trade-offs, and documentation/communication skills. These projects will be implemented with our project partners after the appropriate design and approvals have been obtained.

Many science and engineering problems don’t have simple analytical solutions or even accurate analytical approximations. Scientific computing can address certain of these problems successfully, providing unique insight. This course introduces some of the widely used techniques in scientific computing through examples chosen from physics, chemistry, biology, computer science and other fields. The purpose of the course is to introduce methods that are useful in applications and research and to give the students hands-on experience with these methods. The main programming language will be Python.

Fundamental concepts and formalisms of conservation of energy and increase of entropy as applied to natural and engineered environmental and biological systems. In addition to lectures, pedagogical approach includes real-world observations and applications through student presentations and projects.

Abstracting the essential components and mechanisms from a natural system to produce a mathematical model, which can be analyzed with a variety of formal mathematical methods, is perhaps the most important, but least understood, task in applied mathematics. This course approaches a number of problems without the prejudice of trying to apply a particular method of solution. Topics drawn from biology, economics, engineering, physical and social sciences.

A first course in the mechanical sciences that introduces elements of continuum mechanics and explains how materials and structures stretch, bend, twist, shake, buckle, and break. Definitions of stress and strain. Strain-displacement relations. Stress-strain behavior of materials. Torsion, beam theory with applications to beam deflections, buckling, and energy methods. Statically determinate and indeterminate structures. Three laboratory sessions required. Strong emphasis on analytical skills and mathematics.

Introduction to basic mathematical ideas and computational methods for solving deterministic optimization problems. Topics covered: linear programming, integer programming, branch-and-bound, branch-and-cut. Emphasis on modeling. Examples from business, society, engineering, sports, e-commerce. Exercises in AMPL, complemented by Mathematica or Matlab.

Atomistic-Mesoscale-Continuum Fluids and Flows; Dimensional Analysis; Diffusion and Heat Transfer Processes; Fluid kinematics; Eulerian and Lagrangian descriptions of Flows; Mass conservation and potential flows; Momentum conservation and the Navier-Stokes equations; Vorticity and Vortices; Lift and Drag in Aerodynamics; Flows in Pipes and Channels; Elementary concepts of Turbulent flows.

Modeling and analysis of mechanical systems. Topics include 3D rigid body dynamics, resonance, damping, frequency response, Laplace transform methods, Lagrange's equations, multiple degree-of-freedom systems and an introduction to control and continuous systems. Analytical modeling will be supplemented with numerical simulations and lab experiments. Laboratory exercises will explore vibration, and stabilization using data acquisition systems.

Introduction to finite element methods for analysis of steady-state and transient problems in solid and structural mechanics. Implementation of simple MATLAB codes and use of existing general-purpose software (ABAQUS). Final project offers opportunities to extend focus to fluid mechanics and heat transfer and to explore additional software (e.g. COMSOL, FEniCS), if desired.

This class integrates perspectives from leading innovators with collaborative practice and theory of innovation to teach and inspire you to be more innovative in your life and career. Our approach is to engage with leaders and learn their perspectives and align this with innovation sprints where you learn the best tools, processes, and methods to innovate. You can see a course overview here https://youtu.be/CqfvXf33TCE.  Find out more information on Instagram @engsci139 or https://www.instagram.com/engsci139/

An introduction to the mathematical, optical, and computational foundations of computer vision, with a focus on applications in augmented reality and robotic perception. Topics include: camera optics, digital color photography pipelines, multi-camera geometry, image processing and manipulation, simultaneous localization and mapping, lighting and material estimation, and 3D scanning. Emphasis on combining mathematical modeling with robust algorithms for solving ill-posed problems.

This course introduces the fundamentals of probability theory for parameter estimation and decision making under uncertainty. It considers applications to information systems as well as other physical and biological systems. Topics include: discrete and continuous random variables, conditional expectations, Bayes’ rules, laws of large numbers, central limit theorems, Markov chains, Bayesian statistical inferences, and parameter estimations.

Electromagnetism and its applications in science and technology. Topics: Maxwell's equations; electromagnetic waves (e.g., light, microwaves, etc.); wave propagation through media discontinuity; transmission lines, waveguides, and microwave circuits; radiation and antennae; interactions between electromagnetic fields and matters; optics of solids; optical devices; origin of colors; interference and diffraction; lasers and masers; nuclear magnetic resonance and MRI; radio astronomy; wireless networking; plasmonic wave (charge density wave).

This course introduces the fundamentals of circuit theory for the analysis of electrical circuits and the fundamentals of semiconductor devices for the understanding of transistors circuits and other useful actuators and sensors (i.e., transducers). Building on the principles from these two core fundamental areas of electrical engineering, the analog behavior of electronic circuits and physical devices will be modelled, analyzed, and applied. Lab assignments will focus on the design, implementation, and measurement of analog electronic circuits using real electrical components which interface to the physical world. This course complements and forms the basis for many of the abstractions that are used in digital computing systems such as in COMPSCI 141, COMPSCI 146, and COMPSCI 148.

This course follows the material covered in ES152 and dives deeper into the analysis and design of modern analog mixed-signal circuits using CMOS transistors. The course begins with a broad conceptual survey of important mixed-signal circuits such as CMOS amplifiers of various types and their critical building blocks, digital-to-analog and analog-to-digital converters, oscillators, phase- and delay-locked loops, parallel and serial transceivers, and power supplies of various types. Then, the second phase of the course dives into the details of circuit analysis and design, largely revolving around amplifiers implemented in integrated circuit CMOS, covering concepts such as feedback, open- and short-circuit time constants, noise, etc. The third phase of the course will center on final design projects of mixed-single circuits selected by student groups. In parallel, the final third of lectures will delve into several case studies to reinforce understanding and design of analog mixed-signal circuits. This course will utilize modern circuit simulators to aid in circuit design and analysis.

This course is a follow-on to ENG-SCI 155 and continues to develop the fundamentals of information systems in the real world. It focuses on the analysis and manipulation of signals in the time and frequency domains in the context of authentic applications. Topics include: the sampling theorem, convolution, and linear input-output systems in continuous and discrete time. Further, students are introduced to transforms—including Fourier, discrete cosine, wavelet, and PCA / SVD ‘transforms’—that map between vector spaces via matrix multiplication as a method to ease analysis provided conditionalized knowledge. Randomness, noise, and filtering. Waves and interference in the context of communications; antennae, phasors, modulation, multiplexing. Applications in communications and data science.

This course teaches the fundamentals of optimal control and estimation for dynamical systems. The goal of this course is twofold: to teach how to use optimization to formulate, analyze, and solve control and estimation problems, and to prepare students for control and robotics research by introducing some of the most fundamental topics. Key themes include dynamic programming and its approximation, reinforcement learning, model predictive control, Lyapunov analysis, output feedback (control from cameras), nonlinear filtering, geometric computer vision and estimation, data-driven control and learning, as well as convex optimization and semidefinite programming. This course will cover both the theoretical and practical aspects of the topics with running examples mostly motivated by robotics applications.

Introduction to computer-controlled robotic manipulators. Topics include coordinate frames and transformations, forward and inverse kinematic solutions to open-chain manipulators, the Jacobian, dynamics and control, and motion planning. In addition, special topics will be introduced such as computer vision, soft robotics, surgical robots, MEMS and microrobotics, and biomimetic systems. Laboratory exercises will provide experience with industrial robot programming and robot simulation and control.

This course will focus on physical principles underlying semiconductor devices: electrons and holes in semiconductors , energies and bandgaps, transport properties of electrons and holes, p-n junctions, transistors, light emitting diodes, lasers, solar cells and thermoelectric devices.

The goal of this multidisciplinary course is to enable students to learn how to create miniaturized devices. In addition to the weekly lectures, hand-on activities will lead students to become capable of creating micro-nano devices. Students will understand the physics of sensors and actuators, become familiar with thin-film fabrication technologies, and understanding how these concepts were commercialized. Learning is in small teams – together, students design, simulate, build, edit, discuss, and critique their work. Students will make basic structures using lithography, deposition, and etching. Next, they integrate such structures to create, testable, devices. At the end of the semester, they reverse-engineer some commercial devices and reflect on their fabrication and function.

The course provides introduction to micro- and nano-fabrication processes used to realize photonic, electronic and mechanical devices. Lectures will introduce the state-of-the-art semiconductor fabrication processes, including lithography, deposition of metals and dielectrics, etching, oxidation, implantation, and diffusion of dopants. The fabrication component of the course will be carried out in a state-of-the-art cleanroom in the Center for Nanoscale Systems, where students will fabricate several electronic and photonic devices, including transistors, light-emitting diodes (LEDs), lasers and optical resonators.  Device characterization will be performed in a state-of-the-art teaching labs in SEC in Allston.  

Introduction to classical engineering thermodynamics. Topics: Zeroth Law and temperature. Properties of single-component gases, liquids, and solids. Equations of state for ideal and simple nonideal substances. First Law, heat and heat transfer, work, internal energy, enthalpy. Second Law, Third Law, entropy, free energy, exergy. Heat engines and important engineering applications such as refrigerators, power cycles. Properties and simple models of solutions. Phase and chemical equilibrium in multicomponent systems; chemical potential. Electrochemistry, batteries, fuel cells. Laboratory included.

The macroscopic description of the fundamentals of heat transfer and their application to practical problems in energy conversion, electronics and living systems with an emphasis on developing a physical and analytical understanding of conductive, convective and radiative heat transfer. Emphasis will be given to problem solving skills based on applying governing principles, mathematical models and physical intuition.

Topics include: steady state heat conduction in 1, 2 and 3D; transient heat conduction in 1D and 3D; introduction to convective heat transfer, forced convection as well as free convection; heat exchange analysis and design; elements of radiative heat transfer. There will be an emphasis on physical basis of heat transfer with mathematical description where appropriate, as well as using commercially available computer COMSOL software. Course includes (i) classes and problem sets, (ii) COMSOL simulations and (iii) a semester-long, multi-disciplinary team project.

Introduction to the structure, property, and application of materials. Crystal structure and defects. Structure property relation and crystal symmetry. Phase transformation, phase diagram, diffusion. Principles and examples for a variety of engineering applications of electrical, optical, and especially energy storage and conversion materials.

The repertory of materials available to engineers today and embodied in engineering systems includes tens of thousands of different materials, as well as naturally occurring ones. This course addresses why specific materials are selected for particular applications and the rational basis for their selection. The course is intended to serve as an introduction to the principles and methodology of selecting materials for engineering components based on the functionality and purpose of the component in different system applications and operating environments. The selection specification includes satisfying a variety of objectives, such as minimizing weight, cost (financial as well as environmental), end of life recycling and material scarcity.

This course is an introduction to the foundations of quantum mechanics, with specific focus on the basic principles involved in the control of quantum systems. Experimental foundations of quantum mechanics. Superposition principle, Schrödinger’s equation, eigenvalue and time dependent problems, wave packets, coherent states; uncertainty principle. One dimensional problems: double well potentials, tunneling and resonant tunneling; WKB approximation. Hermitian operators and expectation values; time evolution and Hamiltonian, commutation rules, transfer matrix methods. Crystals, Bloch theorem, superlattices. Angular momentum, spin, Pauli matrices. Coherent interaction of light with two-level systems. Quantization of the EM field, spontaneous and stimulated emission; qubits, entanglement, teleportation.

This course is an introduction to the foundations of quantum mechanics, with specific focus on the basic principles involved in the control of quantum systems. Experimental foundations of quantum mechanics. Superposition principle, Schrödinger’s equation, eigenvalue and time dependent problems, wave packets, coherent states; uncertainty principle. One dimensional problems: double well potentials, tunneling and resonant tunneling; WKB approximation. Hermitian operators and expectation values; time evolution and Hamiltonian, commutation rules, transfer matrix methods. Crystals, Bloch theorem, superlattices. Angular momentum, spin, Pauli matrices. Coherent interaction of light with two-level systems. Quantization of the EM field, spontaneous and stimulated emission; qubits, entanglement, teleportation. Taking this course meets the quantum mechanics core course requirement for the Applied Physics model programs.

ES 201/AM 231 is a course in statistical inference and estimation from a signal processing perspective. The course will emphasize the entire pipeline from writing a model, estimating its parameters and performing inference utilizing real data.  The first part of the course will focus on linear and nonlinear probabilistic generative/regression models (e.g. linear, logistic, Poisson regression), and algorithms for optimization (ML/MAP estimation) in these models. We will play particular attention to sparsity-induced regression models, that arise for instance in compressed sensing, because of their relation to artificial neural networks, the topic of the second part of the course.  The second part of the course will introduce students to the nascent and exciting research area of  generative models of deep networks called model-based deep learning. At present, we lack a principled way to design artificial neural networks, the workhorses of modern AI systems. Moreover, modern AI systems lack the ability to explain how they reach their decisions. In other words, we cannot yet call AI explainable or interpretable which, as a society, poses important questions as to the responsible use of such technology. Model-based deep learning provides a framework to develop and constrain neural-network architectures in a principled fashion. We will see, for instance, how neural-networks with ReLU nonlinearities arise from sparse probabilistic generative models introduced in the first part of the course. This will form the basis for a rigorous recipe we will teach you to build interpretable deep neural networks, from the ground up. We will invite an exciting line up of speakers. Speakers will suggest papers that a group of students will present at the beginning of lecture, which will build up to a final project/paper that utilizes/on model-based deep learning applied to problems of interest to students.

This graduate level course studies dynamic systems in time domain with inputs and outputs. Students will learn how to design estimator and controller for a system to ensure desirable properties (e.g., stability, performance, robustness) of the dynamical system. In particular, the course will focus on systems that can be modeled by linear ordinary differential equations (ODEs) and that satisfy time-invariance conditions. The course will introduces the fundamental mathematics of linear spaces, linear operator theory, and then proceeds with the analysis of the response of linear time-variant systems. Advanced topics such as robust control, model predictive control, linear quadratic games and distributed control will be presented based on allowable time and interest from the class. The material learned in this course will form a valuable foundation for further work in systems, control, estimation, identification, detection, signal processing, and communications.

This course covers fundamental neuroanatomy, physiology, and the principles that guide the development and implementation of peripheral neurotechnology. This course will provide an overview of the state of art in neuroprosthetics, functional electrical stimulation, and other relevant devices. Clinical case studies will be used to frame the lectures.

This course will study the fundamentals of human movement, emphasizing applications in rehabilitation, athletics, and assistive devices. Topics will focus on the biomechanical principles of movement (muscle and tendon properties), experimental data collection techniques (motion capture, wearable sensing, and imaging), simulation with musculoskeletal modeling, and cutting-edge topics in assistive robotics (human-centered design, human-in-the-loop optimization, exoskeletons, etc). A semester-long project will allow students to apply the topics to solve a problem of interest relating to human movement or assisted mobility.

This course provides an introduction to biological neural systems, and current engineering efforts to understand, control, and enhance the function of neural systems. The focus is on the basic knowledge of molecular basis, anatomic structures, and electrical functions of central and peripheral nervous systems, and the most state-of-the-art genetic/genomic, optical, electrical, magnetic, and computational tools for nervous systems. Key themes throughout the course will include structures of central and peripheral nervous systems, genetic engineering, RNA sequencing, optogenetics, microscope, bioelectronics, MRI, and computational neuroscience. This includes both the practical and theoretical aspects of the topic.

Project-based course on the design of medical devices to address needs identified by hospital-based clinicians. Students work in teams with physicians to develop a novel device. The design process includes: needs finding; problem identification; prior art searches; strategy and concept generation; estimation; sketching; sketch modeling; machine elements, ergonomics and prototyping.

Introduction to finite element methods for analysis of steady-state and transient problems in solid and structural mechanics. Implementation of simple MATLAB codes and use of existing general-purpose software (ABAQUS). Final project offers opportunities to extend focus to fluid mechanics and heat transfer and to explore additional software (e.g. COMSOL, FEniCS), if desired.

Fundamental engineering and biological principles underlying field of tissue engineering, along with examples and strategies to engineer specific tissues for clinical use. Student design teams prepare a research proposal and participate in a weekly laboratory.

Using a learning-by-doing approach, student teams will work on their own venture concepts in this intensive immersion course. The course will convey concepts and builds skills required in early stage technology ventures, including problem finding (human-centered design, customer discovery), solution finding (ideation methods, prototyping, user testing), business model validation (hypothesis generation, minimum viable products, lean experimentation), sales and marketing methods, venture financing, and team building and leadership skills. Enrollment limited to first-year MS/MBA: Engineering Sciences students only.

This graduate-level seminar course is part of the MDE program's first-year core curriculum, comprising a two-course sequence spanning one year. The course focuses on building an integrated intellectual framework to explore the complex relationships between science, engineering, manufacturing, design, innovation, environment, sustainability, culture, aesthetics, business, public policy, and government. Through the study of various frameworks and lenses, students will gain insights into real-world problem-solving.  The course fosters critical thinking and intellectual literacy, providing a holistic perspective on the interplay between scientific progress, technological innovations, manufacturing systems, and their broader implications for industry and society. Through readings, discussions, and exercises, students will develop interdisciplinary knowledge and problem-solving skills, empowering them to address multifaceted challenges effectively in their professional endeavors.

This graduate-level seminar course is part of the MDE program's first-year core curriculum, comprising a two-course sequence spanning one year. The course focuses on building an integrated intellectual framework to explore the complex relationships between science, engineering, manufacturing, design, innovation, environment, sustainability, culture, aesthetics, business, public policy, and government. Through the study of various frameworks and lenses, students will gain insights into real-world problem-solving.  The course fosters critical thinking and intellectual literacy, providing a holistic perspective on the interplay between scientific progress, technological innovations, manufacturing systems, and their broader implications for industry and society. Through readings, discussions, and exercises, students will develop interdisciplinary knowledge and problem-solving skills, empowering them to address multifaceted challenges effectively in their professional endeavors.

This class integrates perspectives from leading innovators with collaborative practice and theory of innovation to teach and inspire you to be more innovative in your life and career. Our approach is to engage with leaders and learn their perspectives and align this with innovation sprints where you learn the best tools, processes, and methods to innovate. You can see a course overview here https://youtu.be/CqfvXf33TCE.  Find out more information on Instagram @engsci139 or https://www.instagram.com/engsci139/

Students are expected to meet all the requirements of Engineering Sciences 139 and in addition are required to prepare an individual term project with significant analytic emphasis in an area of scientific or technological innovation.

The course aims to develop understanding of electrochemical processes in energy related materials. The fundamental thermodynamics, kinetics, and the underlying electronic and atomistic structure details related to energy storage and conversion materials will be introduced. Model material systems in Li or Na ion battery, solid state battery, perovskite solar cell, etc. will be discussed.

This course teaches how to create original robotic devices made of light, compliant – informal – materials.

New fabrication techniques are transforming the field of robotics. Rather than rigid parts connected by mechanical connectors, robots can now be made of folded paper, carbon laminates or soft gels. They can be formed fully integrated from a 3D printer rather than assembled from individual components. Informal Robotics draws on cutting-edge research from leading labs, in particular, Harvard’s Micro Robotics Laboratory which has created unique designs for ambulatory and flying robots, end-effectors, medical instruments and other applications.

We will explore informal robotics from multiple perspectives, culminating with the design of original devices displaying animated intelligence in real-time. Going beyond traditional engineering approaches, we will also explore new opportunities for design at the product, architectural, and urban scales.

Techniques:
Hands-on:  Working with the GSD’s Fab Lab we are creating a kit of parts that will be available to all enrolled students. With the kit, you can create a wide range of folding mechanisms controlled by on-board miniature electronics.
Software / Simulation: Software workshops will be offered on Fusion 360 and Grasshopper to simulate robotic performance within a virtual environment.

Topics:
- Kinematics: design techniques for pop-ups, origami, and soft mechanisms.
- Fabrication: methods: for composite materials, laminated assembly, self-folding, and integrated flexures - the kit of parts will allow for hands-on exploration.
- Controls: how to actuate movement and program desired behavior. Topics include servos, linear actuators, and use of Arduino actuator control.
- Applications: takes us beyond purely technological concerns, contextualizing Informal Robotics within larger trends where materials, manufacturing and computation are starting to merge

This course introduces bioelectronics and its applications in neuroscience, neuroengineering, cardiology, wearable technology, and so on. The focus is on the basic principles of bioelectricity, biochemistry, and physiological behaviors of biological systems and how to design electronic tools to precisely measure and control them. Key themes throughout the course will include bioelectricity, biochemistry, cellular and tissue physiological behavior, optogenetics, sensors, stimulators, circuits, signal processing, electronics-biology interface, and applications. This includes both the practical and theoretical aspects of the topic. Three experimental demonstrations will be included as part of the normal class meeting time. Given its broad coverage, students who enroll in this course are expected to have a substantial background in chemistry, biology, and electrical engineering (see recommended prep and course requirements). The contents and course requirements are similar to those of Biomedical Engineering 129 (BE 129), with the exception that students enrolled in Engineering Sciences 258 (ENG-SCI 258) are expected to undertake a substantial course project.

Introduction to computer-controlled robotic manipulators. Topics include coordinate frames and transformations, forward and inverse kinematic solutions to open-chain manipulators, the Jacobian, dynamics and control, and motion planning. In addition, special topics will be introduced such as computer vision, soft robotics, surgical robots, MEMS and microrobotics, and biomimetic systems. Laboratory exercises will provide experience with industrial robot programming and robot simulation and control.

This course will review some introductory geophysical fluid dynamics before focusing primarily on the physics of the stratosphere. Topics covered will include eddy transport of heat and momentum, stratospheric Rossby and gravity waves, wave-mean flow interaction, and tracer transport. The course will alternate lecture with in-class coding activities. Each week will have a preparatory reading and brief assignment.

A seminar course that dives into research and development of various topics in integrated circuits and systems for low-power and/or high-performance computing. The course in Spring 2021 will focus on recent advances in novel devices, circuits, and systems that have been developed for machine learning and AI tasks and applications.

The focus is on the foundations of optics/photonics and on some of its most important modern developments and applications. Powerful and widely used computational tools will be developed in the sections. Topics to be covered: Maxwell's equations, Free space optics. Reflection, refraction, polarization (Jones Calculus and Stokes parameters); interference and diffraction. Light-matter interaction, dispersion and absorption. Guided wave optics (including optical fibers). Perturbation and couple mode theory, transfer matrix methods; numerical methods. Optical resonators.  Photonic crystals. Near-field optics. Metal optics and Plasmonics. Metamaterials and Metasurfaces.

The goal of this multidisciplinary course is to enable students to learn how to create miniaturized devices. In addition to the weekly lectures, hand-on activities will lead students to become capable of creating micro-nano devices. Students will understand the physics of sensors and actuators, become familiar with thin-film fabrication technologies, and understanding how these concepts were commercialized. Learning is in small teams – together, students design, simulate, build, edit, discuss, and critique their work. Students will make basic structures using lithography, deposition, and etching. Next, they integrate such structures to create, testable, devices. At the end of the semester, they reverse-engineer some commercial devices and reflect on their fabrication and function.

The course provides introduction to micro- and nano-fabrication processes used to realize photonic, electronic and mechanical devices. Lectures will introduce the state-of-the-art semiconductor fabrication processes, including lithography, deposition of metals and dielectrics, etching, oxidation, implantation, and diffusion of dopants. The fabrication component of the course will be carried out in a state-of-the-art cleanroom in the Center for Nanoscale Systems, where students will fabricate several electronic and photonic devices, including transistors, light-emitting diodes (LEDs), lasers and optical resonators.  Device characterization will be performed in a state-of-the-art teaching labs in SEC in Allston. 

This is a core course for students in the MS/MBA: Engineering Sciences program. The course will begin with methods for modeling engineering and business systems, including discrete and continuous systems and feedback controls. Students will write simple simulations and then use professional modeling software to simulate complex systems. Students will next learn design methodology, including stakeholder modeling, ideation, and decision making tools. A final team project will involve design of a system, including simulation and prototyping.

Any organization, business or venture grounds its value on how "meaningful" are its products (functionally, symbolically and emotionally). Design Theory and Practice (DTP) empowers students to create products that are meaningful, to people who use them and to society at large. The course has three purposes:

1. To inspire students about the power of design in new business creation. We will address questions such as: Why is design relevant in tech ventures? How does it create value? And, most of all, why is it fundamental for a technology entrepreneur/leader?

2. To enable them to move into action, by learning the theories and practice (mindsets, processes, methods) of design: Where do ideas come from? How to frame (and especially re-frame) a problem? How to understand what is meaningful to users? How to make a product desirable (functionally, emotionally and symbolically)? How to design and build the user interface of a product? How to test it? How to narrate and visualize a novel idea?

3. To co-explore, with the class and the instructor, the use of design as a leadership practice: How does a leader who masters design can better contribute to creation of value? How can we forge a new manifesto for leadership, inspired by design?

The course is intensively project-based. Students will work in teams on a complex innovation challenge proposed by a real corporation. They will suggest a more effective framing of the problem, and create a novel meaningful solution, with a special focus on the user interface.

This course is an interdisciplinary platform for designers, engineers, and scientists to interact and develop innovative new products. The course introduces ideas-to-innovation processes in a hands-on, project/product focused manner that balance design and engineering concepts with promising, real-world opportunities. Switching back and forth between guided discovery and focused development, between bottom-up and top-down thinking, and market analyses, the course helps students establish generalizable frameworks as researchers and innovators with a focus on new and emerging technologies. There are no prerequisites.

The MS/MBA Capstone is an intensive project that requires teams of students to apply and integrate the skills they have learned across core disciplines developed in the program curriculum. Specifically, teams will be expected to design, build and launch a new technology-based product/service venture, and thereby to demonstrate mastery with respect to three areas of knowledge: Design Knowledge: The use of human-centered design methods to understand users, identify solutions to their needs, and gather feedback via rapid, iterative prototyping. Technical Knowledge: The use of rigorous system engineering methods to plan, design, develop, build, and test a complex technology-based product/service, integrating knowledge across multiple engineering disciplines. Business Knowledge: The use of business model analysis and lean experimentation methods to develop and test a set of hypotheses that capture how the new product/service will create value, including business model design, pricing, sales and marketing, operating model and profit formula.

The Capstone is divided into two parts, the first of which is an immersive course completed during the January term of the G2 year (Capstone I). The subsequent spring course (Capstone II) follows on from and builds upon work completed in January. Given students prior coursework, a working knowledge of human-centered design methods, systems engineering techniques, and business modeling and lean experimentation is assumed. Launch Lab therefore focuses on the practical application of these skills to team projects, supplemented by content in three areas: i) seminars on advanced methods and techniques, ii) workshops that demonstrate how to put these skills and tools into practice, and iii) guest speakers who share their experience in the areas of design, technology and business.
 

The MS/MBA Capstone is an intensive project that requires teams of students to apply and integrate the skills they have learned across core disciplines developed in the program curriculum. Specifically, teams will be expected to design, build and launch a new technology-based product/service venture, and thereby to demonstrate mastery with respect to three areas of knowledge: Design Knowledge: The use of human-centered design methods to understand users, identify solutions to their needs, and gather feedback via rapid, iterative prototyping. Technical Knowledge: The use of rigorous system engineering methods to plan, design, develop, build, and test a complex technology-based product/service, integrating knowledge across multiple engineering disciplines. Business Knowledge: The use of business model analysis and lean experimentation methods to develop and test a set of hypotheses that capture how the new product/service will create value, including business model design, pricing, sales and marketing, operating model and profit formula.

The Capstone is divided into two parts, the first of which is an immersive course completed during the January term of the G2 year (Capstone I). The subsequent spring course (Capstone II) follows on from and builds upon work completed in January. Given students prior coursework, a working knowledge of human-centered design methods, systems engineering techniques, and business modeling and lean experimentation is assumed. Launch Lab therefore focuses on the practical application of these skills to team projects, supplemented by content in three areas: i) seminars on advanced methods and techniques, ii) workshops that demonstrate how to put these skills and tools into practice, and iii) guest speakers who share their experience in the areas of design, technology and business.
 

This class leads students to develop their skills in the critical reading and writing of science and engineering. Genres will include research articles, grant proposals, school/fellowship/job applications, or lay abstracts & press releases for the non-scientific public. Crucially, students will be empowered not only to achieve their own writing goals, but also to break down these learned skills and impart them to others, as effective collaborators and mentors of younger students.

This class leads students to develop their skills in the critical reading and writing of science and engineering. Genres will include research articles, grant proposals, school/fellowship/job applications, or lay abstracts & press releases for the non-scientific public. Crucially, students will be empowered not only to achieve their own writing goals, but also to break down these learned skills and impart them to others, as effective collaborators and mentors of younger students.

Supervision of experimental or theoretical research on acceptable problems in engineering and applied science and supervision of reading on topics not covered by regular courses of instruction.

Supervision of experimental or theoretical research on acceptable problems in engineering and applied science and supervision of reading on topics not covered by regular courses of instruction.