ESP Biography



YOSHIHIRO SAITO, Harvard Physics PhD Student




Major: Physics

College/Employer: MIT

Year of Graduation: 2022

Picture of Yoshihiro Saito

Brief Biographical Sketch:

I'm a current physics PhD student at Harvard working on something called condensed matter physics. Before Harvard, I was an undergrad at MIT studying physics, math, and computer science.



Past Classes

  (Clicking a class title will bring you to the course's section of the corresponding course catalog)

S16150: What is a Particle? in Splash 2025 (Mar. 15 - 16, 2025)
What is a particle? A wave? A vibration in a mysterious field? Or something stranger? In this fast-paced crash course, we’ll journey from Newton’s laws to Maxwell’s equations, through the mind-bending weirdness of quantum mechanics, and into the deep symmetries of quantum field theory trying to answer the ultimate question: what is a particle? Along the way, we’ll touch on the ideas of calculus and uncover the hidden math of group theory and see how everything—from light to matter—is shaped by fundamental principles. No prior physics experience needed—just curiosity and a willingness to challenge your intuition!


S16151: The History of Physics Through Nobel in Splash 2025 (Mar. 15 - 16, 2025)
Maybe you've heard of Heisenberg, Einstein, and Feynman—but what exactly did they win their Nobel Prizes for? And how do their discoveries connect to the bigger picture of physics? This class explores the history of physics by following the trail of Nobel Prizes, from the earliest awards in the early 20th century to modern breakthroughs. Along the way, we’ll see how revolutionary ideas—like quantum mechanics and relativity—reshaped our understanding of the universe. Expect stories of triumph, controversy, and even the occasional overlooked genius. By the end, you’ll see how physics has evolved, one prize at a time.


M13584: Bayes Theorem and How It Changed Statistics in Splash 2019 (Nov. 23 - 24, 2019)
Thomas Bayes, a British minister and statistician, presented a theorem in the 18th century that came to be named after him. This theorem paved the way for a completely new understanding of statistics. Now, "Bayesian thought" appears nearly everywhere from social science, to physics, to machine learning!