Courses

I graduated with a B.S. in Mathematics from 2018 – 2021 from the University of Florida. I am now in a PhD program in Electrical Engineering from the University of Florida.

I do love math and I would usually tell people that there was no particular reason why electrical engineering — engineering is just applied math in my mind. If it were not for some professional reasons including an engineering title, direct pathways for application and collaboration, the difference is not of essential importance to me.

Mathematics (Undergraduate)

Fall 2018

• [MAC3474] Calculus 3 Honors (Sergei Shabanov)

• [MAP7436] Seminar In Applied 1 (Yunmei Chen)

• [PHY2049] Physics II with Calculus

• [MAP2302] Elementary Differential Equations (Yu Cheng)

Spring 2019

• [MAP7347] Seminar in Applied Math 2 (Yunmei Chen)

• [EEL311C] Circuits 1

• [EEL3135] Signals and Systems (Joel Harley)

Summer 2019

• [MAS4105] Linear Algebra (Willard Keeran)

Fall 2019

• [MAT4930] Numerical Linear Algebra (Sara Pollock)

• [EEL4930] Fundamentals of Machine Learning (Catia Silva)

• [EEL4930] Statistics for ECE (Catia Silva)

• [EEL3112] Circuits 2

Spring 2020

• [MAP4341] Elements of Partial Differential Equations (Sergei Shabanov)

• [MAP4413] Fourier Series and Transforms (Lei Zhang)

• [MAT4930] Numerical Analysis (Sara Pollock)

• [MAT4930] Numerical PDE (Sara Pollock)

• [MAP 4402] Functions of Complex Variables (Jesse Thorner)

Summer 2020

• [MAS4301] Abstract Algebra (Konstantina Christodoulopoulou)

• [MHF3202] Sets and Logic (Paul Robinson)

Fall 2020

• [MAT4930] Math Methods for Physics and Engineering 1 (Sergei Shabanov)

• [MAA4211] Advanced Calculus 1 (Vince Vatter)

Spring 2021

• [MAT4930] Math Methods for Physics and Engineering 2 (Sergei Shabanov)

• [MAA4212] Advanced Calculus 2 (Vince Vatter)

Electrical and Computer Engineering (PhD)

Fall 2021

• [EEL6532] Information Theory (Tan Wong)

• [EEL6935] Neuro-AI (Shreya Saxena)

• [PSB6115C] Clinical and Cognitive Neuroscience (Adam Woods)

Spring 2022

• (COT5615) Math for Intelligent Systems

• (EEL6825) Pattern Recognition (Dapeng Wu)

Fall 2022

• [BME6938] AI and Neuroscience (Mingzhou Ding)

• [ESI6420] Fundamentals of Mathematical Programming (Jorge Sefair)

Spring 2023

• [EEL6935] Information Theory for Data Science and Machine Learning (Yuheng Bu)

• [CIS6930] CS & AI Education

Fall 2023

• [EEL6935] Physics Informed Machine Learning (Joel Harley)

Spring 2024

• [EEL6940 / EEL3135] Supervised Teaching for Signals and Systems (Joel Harley)