Professional Experience

Lawrence Berkeley National Lab,

Berkeley, CA
Machine Learning Researcher
September 2020 – Present

Conducted research at the intersection of machine learning and high energy physics, developing novel computational methods for analyzing particle physics data.

Responsibilities

  • Developed machine learning algorithms for unfolding and deconvolution in particle physics experiments
  • Collaborated with international teams on ATLAS experiment data analysis
  • Published research in peer-reviewed journals and presented at international conferences
  • Mentored undergraduate researchers on machine learning projects

Technologies & Skills

  • Python, TensorFlow, PyTorch, JAX
  • Statistical inference and Bayesian methods
  • High-performance computing on NERSC systems
  • Particle physics simulation and analysis frameworks

Emissary AI,

San Francisco, CA
Machine Learning Engineer
May 2025 – December 2025

Developed and fine-tuned language and vision-language models for client-specific applications at Emissary AI.

Responsibilities

  • Developed and fine-tuned language and vision-language models for client-specific applications, including code completion and image-based IP violation detection
  • Improved model accuracy from around 30% to over 90% for medical message classification through architecture optimization and training refinements
  • Optimized training pipeline for distributed multi-GPU systems, improving scalability and throughput

Technologies & Skills

  • Large language models and vision-language models
  • Model fine-tuning and architecture optimization
  • Distributed multi-GPU training
  • Python, PyTorch, and deep learning frameworks

University of California,

Berkeley, CA
Associate Instructor
August 2020 – December 2024

Served as Associate Instructor in the UC Berkeley Physics Department, teaching a range of undergraduate courses.

Courses Taught

  • Physics 89: Introduction to Mathematical Physics
  • Physics 88: Data Science Applications in Physics
  • Physics 77: Introduction to Computational Techniques in Physics
  • Physics 8B: Introductory Physics (Head Associate Instructor)
  • Physics 7B: Physics for Scientists and Engineers

Technologies & Skills

  • Curriculum development and course instruction
  • Python, data science, and mathematical and computational physics pedagogy

Bridgewater Associates,

Westport, CT
Investment Analyst Intern
June 2023 – August 2023

Worked on systematic trading research and execution at Bridgewater Associates, developing probabilistic models and strategic frameworks to optimize investment decisions.

Responsibilities

  • Created Bayesian Hierarchical Networks to predict market liquidity for optimal execution of alpha signals
  • Engineered Bayesian networks to model systematic trading strategies for transaction cost minimization, preventing alpha leakage
  • Implemented and optimized trading strategies, translating market analyses into actionable portfolios
  • Provided strategic investment input contributing to high-level decisions for large institutional capital pools

Technologies & Skills

  • Bayesian networks and hierarchical modeling
  • Quantitative trading strategy design and execution
  • Python, R, and statistical computing
  • Financial modeling, liquidity analysis, and portfolio optimization

Microsoft Research,

Cambridge, MA
PhD Research Intern
May 2022 – August 2022

Conducted theoretical and computational research at Microsoft Research, advancing mathematical foundations of non-local field theory and its applications to optimization.

Responsibilities

  • Collaborated with Jaron Lanier (Chief Unifying Scientist) on developing non-local field theory from matrix models
  • Bridged discrete and continuous structures through new techniques applicable to optimization problems
  • Applied stochastic calculus and operator theory to establish quantitative relationships between local and non-local dynamics
  • Designed and executed numerical simulations to validate predictions about high-dimensional operators
  • Provided mathematical formalism and technical implementation acknowledged as significant contributions to the project

Technologies & Skills

  • Stochastic calculus, operator theory, and matrix models
  • Theoretical physics and applied mathematics
  • Numerical simulations and computational modeling
  • Python, MATLAB, and high-dimensional analysis

Purple Gaze Inc.,

Amsterdam, Netherlands
Software Developer Intern
May 2020 – July 2020

Contributed to the development of advanced eye-tracking software at Purple Gaze Inc., building AI-driven algorithms and real-time image processing pipelines for production deployment.

Responsibilities

  • Engineered AI-driven glint detection algorithms for eye-tracking software, significantly improving detection accuracy
  • Wrote production-quality code in Python and C++ for real-time image processing applications
  • Collaborated within an agile startup environment, delivering features under tight deadlines while ensuring high code quality

Technologies & Skills

  • Python, C++, and real-time image processing
  • Computer vision and AI-driven algorithm design
  • Agile software development practices
  • Performance optimization and production deployment