Spring 2027 Supplement and Course Offerings

Instructor(s): Tim Ferguson Sauder, Annick Dewald, Rob Martello, Sam Michalks, Elizabeth Sylven; TBD 

Credits: 4 

Curriculum Role: E! Foundation

Course Description: Triple T (aka T3) is half-semester course that focuses on three areas that will be a large part of every student's experience over the course of their time at Olin - Teaming, Talking and Trying. 

This course is meant to help students develop a solid base of experience in each area:

Students will work in groups, study what makes a group work, and use tools to make their own groups more successful. Students will experience talking and engaging with people they don't know and practice seeking out others perspectives in order to inform their designs. Finally, team members will work together to try out designs and then make changes to those designs based on feedback from users.

Instructor: Dyllan Nguyen

Credits: 4 AHS

Recommended Requisite: Design Nature

Course Description: In this studio art course, we'll explore topics in contemporary art and create works using wood as a primary medium. We'll develop a foundational understanding of wood as a material, learn to safely operate a variety of tools, and consider the context of each individual’s work in the field of sculpture and contemporary art more broadly. Lectures and demonstrations will be complimented by readings, screenings, student presentations, and studio practice. Assignments will be structured so students may choose to work on teams or independently.

Assessment of projects will be based on rubrics provided when assignments are set and will seek to balance the conceptual and technical development of each student, with an emphasis on process engagement.

Instructor: Erhardt Graeff

Credits: 4 AHS

Course Description: Tired of doomscrolling the news? Education, environmental action, transportation/infrastructure, jobs—these all happen somewhere—the place you live. From town meetings to school boards, community organizing to participatory planning, learning to navigate local government and politics can build common ground and unlock tremendous impact and resilience. We will visit our democratic institutions in Needham and hear from local politicians, government officials, journalists, and activists in the Greater Boston area; learn the lingo of local politics (zoning, public records, NIMBYism); and make connections between local, national, and global issues through current events discussions and case studies. Expect field trips and regular opportunities for personal and collective reflection.

Instructor: Daniel Sambor

Credits: 4

Curriculum Category: ME Elective; E:Sust Req:Adv

Recommended Requisites: ENGX2000 AND MTH1111

Course Description: This course will take a model-based approach to analyze, size, and predict performance of renewable energy systems, with an emphasis on solar photovoltaic (PV) arrays, at varying scales and contexts. A primary learning goal of the course is to understand how to design a complete renewable energy system: estimating the renewable resource, choosing the appropriate energy technology, and integrating with energy storage systems to satisfy energy demand for a specific context. Activities will highlight practical aspects of real renewable energy projects that can inform models, such as solar PV shading impacts and siting. The course will have two projects: first, an individual project to perform a solar microgrid modeling analysis and proposal using industry-standard tools; and a final group project working hands-on with renewable energy technologies for an application. Topics include the smart grid, wind power systems, and battery energy storage systems.

Instructor: Daniela Faas

Credits: 4 ENGR

Curriculum Role: ME, Design Elective

Requisites: Recommended material science or mech solids 

Course Description: Digital fabrication techniques create unique geometries and forms from standardized, often industrially processed materials. This course explores the materialization of design as both a technical and a creative endeavor, structured around core manufacturing skills. Students engage with the methods and materials that underpin digital fabrication, including ceramics, glass, metal, and potentially composites.

In this course, we will examine the fundamental similarities and differences between ceramics, metals, and glass. We will learn the related material strengths, working properties, and manufacturing techniques, before exploring the diverse ways digital technologies can integrate with these materials. This course is hands-on and project-based with two longer projects and weekly lab sessions. Students document their process and share their creations with the class.

Students will use computational design tools to create functional, aesthetic objects — household items like mugs, plates, and bowls — that integrate digital processes such as 3D printing with traditional and modern fabrication methods to produce personalized, high-quality, innovative products. This spans the full design-to-production workflow, from initial concept and digital modeling to material selection and final output, including how to choose appropriate materials for a given application based on durability, aesthetics, and other factors. Universal Design principles and human-factors considerations further inform these design decisions. 

Instructor: Zachary del Rosario

Credits: 4

Recommended Requisites: ModSim, Prob/Stat

Course Description: Optimization is ubiquitous in engineering practice: Structural engineers optimize structural layouts, control engineers use optimization to do path planning for robots and spacecraft, materials scientists use optimization for materials selection, and machine learning is enabled by a suite of highly efficient optimization algorithms. However, optimization is not a silver bullet: Running a successful optimization requires experience to avoid pitfalls, and optimization that ignores uncertainty can select fragile designs. This course is about the tools and understanding necessary to do optimization under uncertainty.



In Probabilistic Design Optimization (PDO), students will learn mathematical ideas to formulate and solve optimization problems and to model uncertainty with probability. Students will practice modeling engineering problems with objectives, constraints, and densities, and will see examples across many different fields. They will gain an intuitive and practical understanding of relevant practical challenges: necessary conditions for optimality, local minima, approximation challenges, problem rescaling, data sparsity, and modeling uncertainties.



Students will also learn broader ideas to contextualize the math of this class, drawing on concepts from philosophy, history, and social sciences. These ideas will help students develop a more expert-like understanding; in particular, the widespread view of veteran engineers that mathematics is both necessary and *in*sufficient for engineering practice.



This course will reinforce content through problem sets, seminars, and a large project with significant student choice. Students will work on individual projects and will choose a system to model, analyze, and optimize under uncertainty. This class is intended as a design depth; however, students have the option to take this as an ME, ECE, or E:Computing elective. Students taking this course as such an elective must select a simple system from the relevant core topic---e.g. Thermodynamics, MechSolids, Transport, etc. for ME; Circuits, Signals and Systems, etc. for ECE; a CompArch or Machine Learning for E:Computing---and communicate this choice to the PDO instructor. High-level work on the project will begin with the first problem set, and students will iterate on their project throughout the course.

Instructor: Emily Tow

Credits: 4 ENGR

Registration Note: This course is offered at MIT in Cambridge

Course Description: Thermal energy networks (TENs) use ambient-temperature water loops to move thermal energy between buildings with heat pumps, efficiently decarbonizing heating and cooling. Students will learn about heat pumps, shallow geothermal energy, ambient loops, thermal energy storage, waste energy recovery, and techno-economic analysis. Students will hear from industry experts and local community leaders, build shared language and intuition around key thermal-fluids concepts, and conduct a feasibility study of a potential TEN at a local site. In this interdisciplinary, team-project-based course, students will learn about building decarbonization by moving a real geothermal/TEN project forward. The class meets at MIT with an analogous MIT course, enabling knowledge sharing and cross-campus collaboration; transportation (likely carpooling) will be arranged collaboratively among enrolled Olin students.

Instructor: Victoria Preston

Credits: 4 (2 MTH, 2 ENGR)

Curriculum Role: E:Robo advanced elective, E:C / ECE elective, Prob-Stat requirement

Registration Note: Required pre-requisite of Software Design (ENGR2510). Suggested pre-requisite of Discrete (MTH2110) or a Computational Introduction to Robotics (ENGR3590). Limited seats (15).

Course Description: This class extensively discusses the intersection of robotics with probabilistic reasoning. Robots, by virtue of being embodied, interact with the world – and as it turns out, the world is an incredibly complex and uncertain place. For robots to perform what we might consider “intelligent” or complex tasks, such as navigating previously unseen terrain in search of a nebulous goal (e.g., planetary exploration, search and rescue) or collaborating with people in dynamic environments (e.g., factory floors, households), those robots need a way of representing the world, and leveraging that representation to plan out actions and action sequences. The course will deeply inspect modern methods in state estimation and localization, mapping, and planning under uncertainty. The learning objectives of this course include (1) fluency in constructing (mathematical) formalisms for robotics tasks, (2) practice designing and prototyping robotic algorithms computationally, (3) building statistical analysis and uncertainty quantification skills, and (4) ability to identify limitations and assumptions in models and algorithms and assert their implications.

Instructor: Sarah Spence Adams

Credits: 4

Curriculum Role: Advanced Math, ME Math, E:Robo Math

Pre-Requisites: QEA1 and QEA2

Course Description: In this course, students will design their own learning goals, including content goals related to linear algebra, abstract algebra, or other algebraic structures, and then coordinate with a small group to design their own projects/experiences to achieve those goals. This structure will allow students to improve their self-directed learning skills, develop quantitative knowledge related to algebraic structures, and apply their new learnings to applications relevant to their major or personal interests. This course counts as an advanced math elective for ME and E:Robo (and maybe other majors). 

Short introductions to key content or applications in linear/abstract algebra will occur, particularly during the first several weeks of the course as students are deciding what to learn and how to learn it. There may be a small amount of homework on these common lessons, however, most of the work in this course will require students to take initiative to articulate their learning goals and craft projects/experiences to achieve those goals.

This class is a great match for students who have finished QEA 1 and 2 and are motivated to significantly challenge themselves to design experiences to learn advanced technical material. Based on student feedback from the first few iterations of this course, seniors going into graduate school or careers in technical fields are particularly encouraged to use this course as a way to build technical content knowledge and transition to more fully self-directed learning.  

*2-Credit Option*

Instructor: Sarah Spence Adams

Credits: 2

Curriculum Role: Math Elective

Pre-Requisites: QEA1 and QEA2

Course Description: In this course, students will design their own learning goals, including content goals related to linear algebra, abstract algebra, or other algebraic structures, and then coordinate with a small group to design their own projects/experiences to achieve those goals. This structure will allow students to improve their self-directed learning skills, develop quantitative knowledge related to algebraic structures, and apply their new learnings to applications relevant to their major or personal interests. This course counts as an advanced math elective for ME and E:Robo (and maybe other majors). 

Short introductions to key content or applications in linear/abstract algebra will occur, particularly during the first several weeks of the course as students are deciding what to learn and how to learn it. There may be a small amount of homework on these common lessons, however, most of the work in this course will require students to take initiative to articulate their learning goals and craft projects/experiences to achieve those goals.

This class is a great match for students who have finished QEA 1 and 2 and are motivated to significantly challenge themselves to design experiences to learn advanced technical material. Based on student feedback from the first few iterations of this course, seniors going into graduate school or careers in technical fields are particularly encouraged to use this course as a way to build technical content knowledge and transition to more fully self-directed learning.  

Intructor: Jean Huang

Credits: 4

Curriculum Role: Foundation Biology

Course Description: This project-based course invites students to collaborate on real-world sustainability challenges with faculty and industry partners. Working in multidisciplinary teams, students will engage with external liaisons to analyze and develop solutions to current sustainability challenges with external partners.  Students will apply skills in engineering, science, teamwork, sustainability, biology, and systems thinking.  Through this hands-on experience, students will gain insights into real-world sustainability problem-solving and apply systemic thinking for analysis and design. For Spring 2026, SIRC partners are the Wellesley Department of Public Works and Town of Wellesley Sustainability.

Instructor: Stephanie Tenney

Credits: 4

Curriculum Role: Mat Sci / Chemistry Requirement

Course Description:  This laboratory-based course will introduce students to fundamental principles in inorganic chemistry, solid-state chemistry, and materials science. Students will begin with a theoretical framework for bonding at the atomic scale, then take a close look at how electronic and physical structure changes when atoms built up into extended networks such as insulators, semiconductors, and metals. Specific properties that will be examined include electrical and thermal conductivity, magnetism, and optical activity. By the end of the semester students will understand how these materials systems lead to functional or structural technologies and have tools to rationalize how to design materials with economic and sustainable solutions in mind.

The course will meet twice a week and will include classroom discussions and activities and laboratory experiments. In the lab, students will perform team-based experiments in materials synthesis and characterization of properties discussed in the classroom. During some weeks, time will be allotted for open-ended projects related to the completed experiments where students take a deeper dive into an aspect that they find most interesting. At the end of the semester, a research-oriented final project will allow students to examine or develop a materials system of their choosing in order to apply the skills developed throughout the prior experiments.

Instructor: Rachel Yang

Credits: 4

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Instructor: Helen Donis-Keller

Credits: 4 SCI

Curriculum Role: advanced biology elective

Registration Note: Students are expected to have taken a foundation biology course at Olin or have foundational knowledge in biology from a high school course such as AP biology, or permission of the instructor

Course Description: As incredible as it might seem, it is well accepted in the scientific community that birds evolved from dinosaurs. In fact, modern birds are classified as living dinosaurs. Evolution of extinct and living organisms will be understood in the context of the environment so we will take a journey from the formation of planet earth, through the remarkable changes of oceans and land masses (think Pangea) to the still changing configuration of our modern world. The fossil record is even more fascinating given the advent of modern technologies that enable new discoveries every day. Immersion in the Mesozoic Era (Triassic, Jurassic, Cretaceous) will allow us to ponder some deeply interesting questions of life during those 200 million years and how we know what we know. Darwin and Wallace’s Theory of Evolution is the thread that binds all biology. We will delve into why this is so, how evolution works, and look at examples of evolution continuing in modern times. The evolution of birds will be a major focus which naturally includes a solid understanding of how birds work. A few interesting questions we will consider are how was it possible for Tyrannosaurus rex get so big? We now know that T. rex had lungs and air sacs like modern birds… why? What was the basis for the 5 mass extinctions and are we headed for the 6th? What new engineering technologies are leading to remarkable new research findings? What have we learned from sequencing the first 500 bird genomes? Who knew that feather development and evolution could be so complicated? Why are scientists working on cloning extinct species like mastodons? We will have the pleasure of seminars by leaders in the fields of paleontology, molecular genetics, and ornithology as well as at least one field trip to a museum of natural history and other venues. The subject of the final project will be to make artifacts that illustrate our learning in the course.

Instructor: Gillian Epstein

Credits: 4

Registration Note: must have project approval and mentor assignment prior to end of Fall 2025 semester

Curriculum Role: flexible, depending on project 

Course Description: Students will develop habits of mind and skills to support their independent learning; work collectively to share and support ongoing work; develop mentor relationships in order to receive and iterate on feedback; and find creative and engaging ways to share their work with the Olin community. Once you register for CLIP, Gillian will reach out to have you complete the mentor process and fill out ISR paperwork.  CLIP mentor pairings and paperwork need to be completed prior to the start of the Spring semester.  We got this!

Instructor: Sarah Bloomer

Credits: 4

Course Description: Help shape the Olin–Pratt partnership for 2027-28 from the ground up. In this course, students will work as a team with peers and faculty at Pratt Institute in Brooklyn, NY, whose programs include fine arts, architecture, fashion, industrial design, and graphic design. Students will connect Olin’s learning culture with Pratt’s creative disciplines through joint projects and by creating new courses and experiences in which students from both schools can learn and create together.

Students will explore, design, and pilot interdisciplinary learning experiences such as workshops, short courses, collaborative challenges, critiques, campus visits (to Brooklyn), and exhibitions. Examples might connect engineering with kinetic or interactive art, architecture and public space, product design and prototyping, or fashion and wearable technology. Students will test and refine their ideas through feedback and critique from peers and faculty.

Students will practice leadership, facilitation, educational and experience design, and community building by creating real programs for Olin and Pratt students. Deliverables will include pilot activities and recommendations for collaborative programs that could be offered in the 2027-28 academic year.