Education

Johns Hopkins, Graduate — Ph.D in Applied Mathematics August 2023 – Present
Johns Hopkins, Graduate — M.S in Applied Mathematics August 2022 – May 2023
Johns Hopkins, Undergraduate — B.S in Applied Mathematics August 2019 – May 2022
Johns Hopkins, Undergraduate — B.A in Mathematics August 2019 – May 2022

Teaching Experience

Johns Hopkins, Baltimore — Course Instructor

Developed a complete syllabus, lecture notes, and assignments to facilitate courses ranging from 15 to 80 students. Presented extensive lectures on linear algebra, probability, statistics, data analysis, and differential equations. Facilitated student engagement and discussion.

Johns Hopkins, Baltimore — Directed Reading Program

Paired with up to three students a semester, mentoring a self-contained course on gradient descent, its convergence theory and guarantees. Wrote a series of lecture notes and exercises for students who were expected to discuss and work independently for a few hours every week. After the semester of preparation, each student presented a structured talk to the group of mentees.

Johns Hopkins, Baltimore — Course Developer

Contributed to the design and development of new mathematics and engineering courses. Authored original lecture material, guided Excel practice problems, engaging problem sets, and instructional resources tailored to enhance pedagogical clarity and student engagement.

Johns Hopkins, Baltimore — Teaching Assistant

Supported instruction in twenty undergraduate and graduate-level courses through grading, writing lecture notes, designing assignments, leading weekly discussion sections, and providing academic support to students. Collaborated with faculty to reinforce core course concepts and foster a strong learning environment.

Johns Hopkins, Baltimore — MSE Orientation Review Session

Designed and led a series of review sessions for the incoming 120 masters students, covering foundational concepts in linear algebra and matrix analysis. Developed comprehensive lecture notes and facilitated interactive discussions to prepare students for rigorous graduate coursework.

Mathnasium, Baltimore — Math Instructor

Tutored dozens of students ages 6 to 18 in fundamental math topics ranging from multiplication tables to AP calculus. Adapted instruction to individual learning styles, promoting confidence and mastery in mathematical skills.

Instructor of Record

Data Analysis Workshop (AS.110.100)

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling.

Linear Algebra and Differential Equations (EN.553.291)

An introduction to the basic concepts of linear algebra, matrix theory, and differential equations that are used widely in modern engineering and science.

Course Development

College Algebra (AS.110.102) — Complete
Course Developer, Johns Hopkins University

Collaborated with the Director of Online Programs to develop a comprehensive College Algebra course aimed at preparing incoming students for success in higher-level mathematics. Designed instructional content to reinforce key algebraic concepts through accessible and engaging materials.

Data Analysis Workshop (AS.110.100) — Complete
Course Developer & Instructor, Johns Hopkins University

Developed and launched a summer course for high school students introducing the fundamentals of data analysis, probability, and statistics. Encouraged students to master affective presentation skills and collaborative work. Produced a full suite of materials, including lecture videos, online quizzes, interactive assignments, and guided Excel tutorials, delivered to over 50 students annually.

Teaching Assistant

Graduate Teaching Assistant
Introduction to Computational Mathematics (EN.553.385) Spring 2025, Spring 2026
Machine Learning 1 (EN.553.740) Fall 2025
Introduction to Convexity (EN.553.665) Fall 2024, Spring 2024
Matrix Analysis and Linear Algebra (EN.553.792) Fall 2023
Mathematical Game Theory (EN.553.653) Spring 2023
Mathematical Modeling and Consulting (EN.553.400) Spring 2023
Optimization in Finance (EN.553.661) Fall 2022
Undergraduate Teaching Assistant
Real Analysis I (EN.553.405) Spring 2022, Summer 2022
Cryptology and Coding (EN.553.371) Spring 2022
Calculus II (For Biological and Social Science) (AS.110.107) Spring 2022
Honors Discrete Mathematics (EN.553.172) Fall 2021
Differential Equations and Applications (AS.110.302) Fall 2021, Spring 2021
Discrete Mathematics (EN.553.171) Spring 2021, Fall 2020
Calculus III (AS.110.202) Fall 2020
Introduction to Computing (AS.205.205) Spring 2020

Research Interests

Optimization
Dissertation research with Dr. Benjamin Grimmer, Johns Hopkins University

Conducting theoretical research on algorithm design and analysis to unify the regimes between smooth and nonsmooth convex problem classes (e.g. function exhibiting Hölder smoothness or uniform convexity). Prior work focused on heterogeneously smooth and convex compositions, calculus results expanding and characterizing dual notations between Hölder smoothness and uniform convexity, interpolation theory for inexactly smooth convex functions, performance estimation over respective problem classes, and universal algorithm design. Future work entails characterizing the class of minimax optimal methods for convex Lipschitz minimization.

AI Pedagogy
Extracurricular research led by Dr. Sergey Kushnarev, Johns Hopkins University

Experimentation and implementation of various AI derived course assistants. Herein, we discuss, analyze, and test different methods for embedding the rising LLM tools into the education system. By supplying agents with structured prompts, focused on providing students with motivation and step-by-step guidance instead of direct answers, we aim to improve comprehension and intellectual capability.

Signal Processing
Planned collaboration with Dr. Mario Michelli & Kaleigh Rudge, Johns Hopkins University

Preparing to investigate spectral properties of the Discrete Fourier Transform and its connections to signal representation and harmonic analysis. Further investigation will include advancing understanding of the Fractional Fourier Transform, smoothly interpolating between the signal and frequency domains.

Publications

Accepted Papers
A Universally Optimal Primal-Dual Method for Minimizing Heterogeneous Compositions
(IMA Journal of Numerical Analysis, 2025)
Preprints
A Complete Characterization of Optimal Subgradient Methods for Lipschitz Minimization
(2026)
Inexactly Smooth Performance Estimation and New Optimized Gradient Methods
(2026)

Talks

On Interpolation Theory
Algebra and Number Theory Guest Lecture, Clayton High School Apr. 2026
On Inexactly Smooth Performance Estimation
INFORMS Annual Meeting, Atlanta, Georgia Oct. 2025
Junior MINDS Seminar, Johns Hopkins Mathematical Institute for Data Science Nov. 2025
Modeling and Optimization: Theory and Applications (MOPTA), Lehigh University (Upcoming) Aug. 2026
On Minimizing Heterogeneous Compositions
Junior MINDS Seminar, Johns Hopkins Mathematical Institute for Data Science Apr. 2025
International Conference on Continuous Optimization (ICCOPT), Los Angeles, California Aug. 2025

Awards

Joel Dean Award for Excellence in Teaching, department of Applied Math and Statistics 2019–2020
Joel Dean Award for Excellence in Teaching, department of Mathematics 2019–2020
Gordon L. and Beatrice C. Bowles Fellowship 2022–2023
Promotion to Teaching Fellow in the Department of Applied Mathematics and Statistics, Johns Hopkins University 2025

Skills

  • Expertise in mathematical problem-solving, analytical reasoning, and quantitative analysis, with the adept ability to tackle complex challenges.
  • Aptitude for delivering clear, engaging presentations and cultivating a dynamic, intellectually stimulating classroom environment.
  • Proficiency in Matlab, Python, and Julia, with extensive experience in optimization algorithms and image analysis techniques.

Software

Matlab · Python · Julia · LaTeX · Desmos · Excel