Hi, I'm

Matthew Xie.

I'm an undergraduate student at the University of Toronto. I'm specializing in Statistics with focus in Machine Learning and minoring in Computer Science.

About Me

I have an interest in deep learning and AI research and building products that leverage these technologies. I have research experience quantizing Protein Language Models (PLMs) built using Transformer architectures with LoRA and QLoRA. I'm also assisting with exploring novel prompting and agentic techniques that allow LLMs to solve more complex MDP reasoning problems.

Where I've Worked

May 2025 - Present

Machine Learning Team Lead | Themis AI

Leading a team of 8 to develop optimal data labeling algorithms. Using Capsa to make uncertainty-aware improvements to model training speed. Also overseeing extension of existing open-source data labeling platforms.

PyTorchPython
Jan - Apr 2025

Machine Vision Engineer Intern | Zebra Technologies

Developed C++ and C# applications for automated quality inspection, OCR, and object classification. Trained and deployed CNN models on IoT hardware. Applied computer vision, 2D and 3D image processing algorithms.

C++C#CNN
May 2024 - Jan 2025

Machine Learning Research Intern | Pardee Lab

ICLR 2025: Co-author on two accepted workshop papers on quantizing Protein Language Models (PLMs) and novel peptide generation from scarce data. Fine-tuned ProteinBERT, ESM-2, ProstT5, and ProLLaMA to predict protein function, structure, and stability. Researched quantization techniques for LLMs, leveraging LoRA and QLoRA fine-tuning to achieve 7:1 model compression while preserving 90% of validation accuracy. Developed flexible PyTorch pipeline for training HuggingFace models across generative and classification tasks. Built benchmark tool to search hyperparameters and visualize metrics, aiding performance evaluations

PyTorchPythonTransformersLoRAQLoRA
Jan 2023 - Apr 2023

Software Developer Intern | Fundserv

Developed Angular website in TypeScript to facilitate client access to Azure backend through microservice APIs. Created novel accessibility testing tool for Angular and integrated it with existing CI/CD pipeline. Conducted comprehensive unit tests on existing codebase using Jasmine and Karma. Developed Angular website in TypeScript to facilitate client access to Azure backend through microservice APIs. Created novel accessibility testing tool for Angular and integrated it with existing CI/CD pipeline. Conducted comprehensive unit tests on existing codebase using Jasmine and Karma

AngularTypeScriptJava

Research and Startups I'm Involved in

April 2025 - Present

Chief Data Officer | Fintech Startup

Startup that seeks to make stock trading more accessible, interpretable, and transparent through intuitive strategy development UI/UX and automated prototyping.

AWSLLMPythonNextJSC++
June 2024 - Present

Agentic LLM Pipeline to Solve MDPs | UofT Engineering Dept.

Assisting with developing and testing LLM prompting techniques such as chain-of-thoguht, RAG, and self-correction.

LLMLangChainLlamaIndexPython
September 2023 - September 2024

Hyperspectral Satellite Image Denoising | UofT Aerospace Team

Developed novel 3D diffusion model to denoise hyperspectral satellite images.

DiffusionCNNPytorchPython

Publications

April 2025

Assessing Quantization and Efficient Fine-Tuning for Protein Language Models | ICLR 2025 Workshop

OpenReview: https://openreview.net/forum?id=KBMxaCSwpB

April 2025

From Minimal Data To Maximal Insight: A Machine Learning Guided Platform For Peptide Discovery | ICLR 2025 Workshop

OpenReview: https://openreview.net/forum?id=sfTXIiu7Op

August 2024

Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH Spacecraft | 38th Annual Small Satellite Conference

DOI: 10.48550/arXiv.2406.10724

Noteworthy Projects

DQN Tetris Bot

Developed a DQN agent to play tetris on a custom-built classic Tetris environment.

PyTorchPython

Links

GitHub

AI Customer Service Call Center

Used ChatGPT and AWS to automatically handle customer queries. Capable of storing user information and interaction history to provide a smooth conversational experience.

AWSOpenAIPythonTwilio

Links

GitHub