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Ben B

- Research Program Mentor

PhD at Stanford University

Expertise

quantum computing, quantum mechanics, computational physics, electromagnetism, computer science, machine learning, scientific visualization

Bio

Hi, I'm Ben! I'm currently a physicist at a quantum computer startup in the Bay Area, and I have a PhD in applied physics from Stanford University. My research focuses on designing programmable photonic circuits for quantum computing and ultra high-speed machine learning, and has been published in high-impact journals including Science and Optica. I have mentored a few students on Polygence before; I really enjoy teaching students new concepts and I will work with you to develop an idea you are excited about and guide you through the research and (if applicable) publication process. Outside of research, I spend a lot of time playing piano, painting, doing LED art projects, working on programming side projects, and making math and physics visualizations with Blender and Mathematica. I also have a very fluffy cat who may occasionally make an appearance in the background.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Using neural networks to solve physics problems

Neural networks have remarkable predictive power for solving all kinds of dynamical systems, and their applicability to computational physics is only recently being explored. In this project, you would explore using neural networks to solve physics problems. A simple starting example could be writing a recurrent NN to predict the evolution of a double pendulum, but there are a lot of directions we could take this project, such as solving quantum or electromagnetic field equations, N-body simulations, or inverse design of electromagnetic components.

Design a quantum computer simulator

Quantum computers are an exciting emerging technology that promise unprecedented computing power. In this project, you would learn some of the basics of quantum mechanics and quantum information, and you would implement a quantum circuit simulator in Python (or any language of your choice). You could demonstrate a variety of quantum algorithms and protocols on your simulator, such as quantum teleportation or quantum error correction.

Create animations for math or physics concepts

Physics seeks to model the rules by which the state of the universe evolves over time. We describe these dynamics with equations and can draw figures to illustrate concepts, but often times for things to really make sense we need an additional dimension for our visualization: time. In this project you would choose one or more concepts from physics you'd like to simulate, and you'd learn how to use a tool such as Mathematica or Blender to create an animation that visually explains these concepts in an intuitive manner.

Coding skills

Python, Mathematica, TypeScript, NumPy/SciPy, TensorFlow, PyTorch, JavaScript, GLSL, Julia, C, C++, Haskell, LaTeX, QuTiP, MEEP

Teaching experience

I was the top-rated instructor at Stanford Pre-Collegiate Studies in 2019, where I designed and taught an accelerated physics course for gifted high school students. I have TA'd several computer science and physics classes at Stanford and Caltech, and have over 10 years of tutoring experience in various subjects in math and science. Also, I was very involved in science fairs in high school, so if you are interested in using your research for a competition such as ISEF or JSHS, I have a good understanding of what makes a successful project.

Credentials

Work experience

PsiQuantum (2022 - Current)
Quantum computer architect
Google X (2021 - 2022)
AI Resident
Stanford Pre-Collegiate Studies (2019 - 2019)
Physics Instructor
CERN (2015 - 2016)
Researcher

Education

California Institute of Technology
BS Bachelor of Science (2017)
Physics, Computer Science
Stanford University
MS Master of Science (2022)
Electrical Engineering
Stanford University
PhD Doctor of Philosophy (2022)
Applied physics

Completed Projects

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