Christopher Francisque

Hi, I'm

Christopher Francisque

CS @ UPenn, ML @ Brandeis

Passionate about computer science, physics, and business. I want to solve the world's hardest problems with technology. I am seeking data science and machine learning internships for Summer 2026 where I can apply my skills to build scalable models, deliver insights, and contribute to software projects with real-world impact.

About Me

I'm a Master student studying Computer Science at the University of Pennsylvania and currently working as a Machine Learning Researcher at Brandeis University under Hongfu Liu. My research focuses on parameter-centric learning, data-centric learning, and LLM knowledge editing.

Previously, I worked as a manufacturing engineer in high-volume production environments, where I gained hands-on experience with data analysis, data pipelines, and data cleaning. I saw firsthand how data-driven decision making could uncover risks, highlight hidden opportunities, and improve manufacturing lines and supply chain operations. I was so inspired I decided to fully pursue a career in data science and machine learning, where I can apply these skills to drive even greater impact.

I am a U.S. citizen with an Active Secret Security Clearance. I am eager to bring my combination of technical expertise and proven impact to my next role, and I am fully open to relocating anywhere in the United States. Outside of work and academics, I like to learn about nutrition and bodybuilding, play basketball, read, and play chess.

Education

University of Pennsylvania

Master of Computer Information and Technology

University of Massachusetts

B.S. Mechanical Engineering

Location

Waltham, MA

Clearance

Active Secret

Experience

June 2025 - Present

Machine Learning Researcher

Brandeis University | Waltham, MA

  • Implemented 3 research papers including LoRA and mask fine-tuning, achieving 82-90% accuracy while training only 0.037% of parameters
  • Built distributed training pipeline across 8 TPU cores handling 110M parameters, solving critical PyTorch XLA synchronization issues
  • Developed gradient tracking system to analyze parameter evolution, identifying critical layers whose removal caused complete model collapse
  • Created pruning pipelines using learned binary masks, improving weak models by 4%
June 2022 - June 2025

Manufacturing Engineer

Raytheon | Andover, MA

  • Developed Python and C++ automation scripts for production data analysis using STL containers and file I/O
  • Led root cause analysis resulting in $60,000 annual cost savings
  • Programmed automated manufacturing systems achieving $100,000+ in cost reductions
  • Designed custom fixtures reducing process times by 10-30%

Featured Projects

Parameter-Efficient Fine-tuning Study

Comparative study of FFT, LoRA, and MFT methods on BERT-base model. Achieved 4.24% accuracy improvement on under-trained models using mask fine-tuning from 2025 ICLR paper while training only 0.037% of parameters.

PyTorch Transformers LoRA BERT Google Cloud Platform

Aircraft 6-DOF Simulation

High-fidelity flight dynamics simulation in C++ using physics-based models and numerical integration. Optimized computational performance through efficient data structures and validated against NASA data.

C++ Physics Simulation Numerical Methods Matplotlib

Portfolio Website

Code for this website to display myself and my work.

Javascript HTML CSS

Technical Skills

Languages

Python C++ Java SQL Bash MATLAB Javascript

ML/AI Frameworks

PyTorch TensorFlow Transformers Hugging Face LoRA

Tools & Platforms

Google Cloud Platform AWS Docker Git Linux Weights & Biases

Data Science

Pandas NumPy Jupyter Data Visualization

Get In Touch

I'm currently seeking data science and machine learning internship opportunities for Summer 2026. Feel free to reach out if you'd like to discuss research, potential collaborations, or opportunities!