CV

Education

• Ph.D. in Physics, Massachusetts Institute of Technology, 2022 – 2027 (expected)
• B.A. in Mathematics and Physics, Vanderbilt University, 2016 – 2020
• Study Abroad, Mathematics and Economics, UCL, London, Spring 2019

Work Experience

• Doctoral Candidate – Massachusetts Institute of Technology (Aug 2022 – Present)
  • Theoretical researcher in Liang Fu’s group
  • Build analytical and numerical frameworks to solve longstanding problems in condensed matter physics, particularly in moire materials
  • Building the first AI foundation model to learn the full quantum wavefunction across multiple numbers of particles
• Quantitative Trader – IMC Trading (Aug 2020 – Aug 2022)
  • Maintained and developed algorithms that systematically trade index options across S&P 500, Nasdaq Composite, and Russell 2000 complexes
  • Built position taking strategy that yielded over $1MM in the first month of rolling out on index desk
  • Converted position taking strategy to multi-layered algorithm running entirely autonomously; strategy yielded over $80K per day on average
  • Integrated position taking algorithm into production deployment and extended to other strategies across desks and products
• Research Assistant – Vanderbilt University (Jan 2019 – Jun 2020)
  • Developed code simulating nano and attoscale phenomena using quantum mechanics and computational methods
  • Successfully simulated 3-dimensional helium atom in an electric field (the first such simulation without traditional approximation methods)
  • First co-author of paper published in Physical Review E
• Research Assistant – Tokyo University of Science (Jun 2019 – Aug 2019)
  • Programmed scattering simulations using Time Dependent Density Functional Theory (TDDFT)
  • Developed a novel method for calculating matrix elements used in cold atom systems
  • First author of paper published in Few-Body Systems

Skills

• Programming Languages: Python, Julia, Fortran
• Languages: English (Native), Spanish (Full Professional), French (Limited Working)
• Research: Condensed matter theory, AI/ML for physics, numerical simulations

Honors & Awards

• Highest Honors in Physics
• Underwood Award
• Ernest A. Jones Scholarship
• Dean of Science Fellowship

Publications

Structure factor and topological bound of twisted bilayer semiconductors at fractional fillings

Timothy Zaklama, Di Luo, and Liang Fu, "Structure factor and topological bound of twisted bilayer semiconductors at fractional fillings." Physical Review B, 2025. [https://doi.org/10.1103/wlvf-tdq1](https://doi.org/10.1103/wlvf-tdq1)

Self-attention neural network for solving correlated electron problems in solids

Timothy Zaklama et al., "Self-attention neural network for solving correlated electron problems in solids." Physical Review X, 2024.

Nonmonotonic Band Flattening near the Magic Angle of Twisted Bilayer MoTe2

Timothy Zaklama et al., "Nonmonotonic Band Flattening near the Magic Angle of Twisted Bilayer MoTe2." Physical Review B, 2024.

Energy spectrum and structure of confined one-dimensional few-electron systems with and without coupling to light in a cavity

Timothy Zaklama et al., "Energy spectrum and structure of confined one-dimensional few-electron systems with and without coupling to light in a cavity." Physical Review E, 2020.

Matrix Elements of One Dimensional Explicitly Correlated Gaussian Basis Functions

Timothy Zaklama et al., "Matrix Elements of One Dimensional Explicitly Correlated Gaussian Basis Functions." Few-Body Systems, 2020.

Teaching

Head Teaching Assistant, Statistical Mechanics

Service and Leadership

• Head TA for Statistical Mechanics at MIT
• Lead mentor for the MIT Physics Mentorship Program
• Coached the Ivory Coast’s math olympiad team to a record number of gold medals at the Africa Olympiad Competition