How I teach
Fundamentals before complexity
Students need a rigorous grasp of the underlying physics and mathematics before they can reason reliably about complex systems.
Learning through authentic problems
Engineering judgment develops when students make real decisions under realistic constraints and have to defend the trade-offs they choose.
Structure first, then independence
Students learn best when expectations are explicit and feedback is frequent, and when responsibility shifts to them as their skills grow.
I approach teaching the way I approach research: as an iterative, evidence-driven process. I set clear objectives, try strategies grounded in educational research, look at what students actually learned, and revise.
What my teaching has taught me
Structured activity builds reasoning
As an Assistant in Instruction for an undergraduate course at Princeton, I advocated for turning chalkboard-only lectures into a studio-style "flipped" classroom. Class time became guided group work that started with structured problem sets and built toward open-ended challenges, such as preparing and defending the physics basis for a congressional geoengineering proposal. I went on to complete Princeton's McGraw Center Teaching Transcript program, where I also learned that technical communication has to be explicitly taught, practiced, and assessed.
Scaffolded design projects build systems-level judgment
I helped organize and teach two multi-university courses on fusion power plant design, held jointly between MIT, Princeton, and Columbia. Student teams learned to integrate plasma physics, magnets, thermal management, materials, and cost into one self-consistent design, and to confront the fact that improving one subsystem often degrades another. With staged milestones and regular expert feedback, the students produced professional-quality work: the first offering yielded three peer-reviewed papers authored by students, and the teams produced the MANTA [PPCF 2024] and CENTAUR [PPCF 2026] pilot plant concepts.
Student ownership sustains learning communities
At Columbia, I founded a student-led graduate plasma seminar course to supplement limited course offerings, then deliberately stepped back so graduate students could run it themselves. Years later it remains a staple of the Columbia plasma curriculum, organized entirely by students.
Courses I would like to teach
I am eager to teach core undergraduate courses across the thermal-fluid sciences, computation, and design sequences of a mechanical engineering curriculum. I would also like to develop two electives built around my expertise:
Fusion Energy Engineering
A project-based course in which teams carry a fusion power plant from requirements to integrated conceptual design, combining thermodynamics, heat transfer, structural and electromagnetic design, materials, energy conversion, and cost. It is fundamentally a course in systems engineering and design trade-offs, with fusion as an exceptionally demanding test case, and it requires no prior plasma coursework.
Teams use open-source design tools such as FUSE and TokaMaker, and the semester ends with a formal design review before a panel of scientists and engineers.
Data-Driven Design of Engineering Systems
Engineers increasingly make decisions when simulations are expensive, data are limited, and system behavior is uncertain. This course teaches surrogate modeling, uncertainty quantification, and Bayesian and multi-objective optimization as tools for making those decisions, using datasets drawn from thermal-fluid, energy, and fusion systems.
It is designed to serve students across mechanical engineering, from thermal-fluid sciences to computational design.
Methods matched to goals
Short in-class problem-solving and peer instruction develop analytical reasoning. Computational notebooks, where students change a parameter and watch a design respond, develop modeling intuition. Team design projects develop systems thinking, and oral design reviews develop technical communication and professional judgment. Frequent low-stakes assessments let both me and my students catch misconceptions early.
Following the model of my Columbia seminar, I also hope to help launch a student-led graduate seminar in fusion science and engineering that is open to students across engineering and physics.
Teaching every student in the room
Leading the APS-DPP CONNECT committee and APS-DPP Student Day taught me that small structural choices help determine who feels they belong in engineering.
- In the classroom: explicit learning objectives and rubrics for every assignment; multiple ways to demonstrate mastery (written analyses, code, and oral design reviews); coursework built on free, open-source software so that no student is limited by access to licenses or computing; and anonymous mid-semester feedback, with a report back to students on what I am changing in response.
- In my research group: written mentoring and individual development plans revisited each semester; structured onboarding with shared code, documentation, and paired projects; and paid undergraduate research positions for students who cannot afford to volunteer their time.
Interactive tools for learning
As an undergraduate at CU Boulder, I benefited directly from research-based teaching, including the PhET interactive simulations. Interactive resources that build physical intuition for fusion systems remain scarce. Building on my work with Princeton's Remote Glow Discharge Experiment and with Next Step Fusion on web-based fusion simulation tools, I am the PI on a proposal under review with the NSF Improving Undergraduate STEM Education program to develop interactive simulations for plasma physics education.
Teaching record
- 2021, 2023Instructor, joint Columbia/Princeton/MIT fusion power plant design courses
- 2023–presentCurriculum development, data science and machine learning for fusion energy (Columbia)
- 2022–presentDeveloper, open-source online tools for fusion energy pedagogy
- 2021Founder, student-led graduate seminar course on plasma physics (Columbia)
- 2021–presentGuest lecturer, Columbia Plasma Physics II; PPPL SULI introductory fusion course (2023 lecture); Princeton seminars
- 2020–2022Teaching fellow, Princeton Writing Center and McGraw Center for Teaching and Learning
- 2019, 2020Teaching assistant, one undergraduate lecture course and one graduate lab course (Princeton)
Research mentoring is described on the Group page.