Hi there! I'm Hamza,

A Computer Science and Economics double major from Rice University. I've navigated the crossroads of technology and finance, building a foundation in programming languages and market dynamics. My journey has ranged from enhancing system efficiency as a Design Intern to predicting stock prices using ML techniques. I'm excited to leverage this blend of skills in roles within software engineering and quantitative analysis. Let's connect if you're interested in the intersection of tech and finance!

Notable Work Experience
May 2024 - PRESENT
Software Engineering Intern @ HashiCorp

Integrating Vault with Terraform to enhance secret management and infrastructure as code solutions

Designing secure, scalable infrastructure while collaborating with experienced professionals in the field

Oct 2023 - PRESENT
Research Assistant @ OptimaLab, Rice University

Developing a benchmarking algorithm for ICARUS, a transformative deep learning model, reducing GPU training time and enhancing efficiency in distributed learning scenarios

Curating dataset for testing ICARUS in a federated learning context, focusing on data architecture and evaluating its performance in distributed network environments for improved data engineering practices

Education
May 2026
Masters of Science in Computer Science

Rice University

Awards: Department of Computer Science Full-Ride Graduate Research Fellowship

May 2025
Bachelor of Science in Computer Science

Rice University

Relevant Courses: Machine Learning, Concurrent Programming, Database Systems, Optimization, Probability and Statistics, Linear Algebra, Operating Systems, Market Models, Financial Accounting

Skill Stack

Backend has been my bread and butter for the past 3 years. However, at such an early stage of my career, I'd like to think of myself as an intermediate Swiss Army Knife like developer who dabbled in front-end, cloud computing and infrastructure, database management, theoretical optimization, and ML & data engineering. This is an overview of my current skills:

LANGUAGES

Python (Expert)

Java, C, Go (Proficient)

HTML & CSS

Java/Typescript

SQL

DBs, FRMs, LIBs

PostgreSQL, MongoDB

PyTorch, Scikit-learn

NumPy, Pandas

JUnit, UnitTest, GoTest

Matplotlib

TOOLS

Docker & Kubernetes

Linux/Unix & Shell Scripting

Terraform & Vault

REST APIs

Git

Delivered Projects

Listed below are some of the most representative projects I've worked on. They touch on multiple fields of computer science and range from basic software & hardware integration projects to advanced convex optimization algorithms and their applications in trading strategies

StudyBuddy: A comprehensive personal assistant that streamlines your academic life. From organizing your directories and automating Google searches to setting up keyword alerts, reminders, generating citations, and shortening links, StudyBuddy is your all-in-one study companion. details

Health-Monitor: A heart rate sensor that measures BPM and SPO2 and a temperature and humidity sensor. All data are displayed on the TFT touchscreen. details

Data Driven Emotions Prediction: A machine learning project aimed at classifying emotions in speech using SVM, CNN, and GMM, encompassing extensive processes of feature extraction, preprocessing, and model validation. details

AlphaCraft: An advanced machine learning-driven system designed to transcend traditional value and momentum investing strategies. By leveraging state-of-the-art reinforcement learning techniques, it optimizes portfolio management, delivering predictive insights with unmatched accuracy. details

Algorithmic Variants of Frank-Wolfe for Convolutional Neural Network Pruning: A thesis that explores the effectiveness of various Frank-Wolfe algorithm variants for pruning large convolutional neural networks, inspired by the "Lottery Ticket Hypothesis." The results show that using a momentum-based Frank-Wolfe approach on the MNIST dataset yields a sparser model with improved accuracy compared to the original network and other pruning methods. details

Predictive Modeling of Homelessness Risk Factors in Women and Children: A study that employs logistic regression and random forests to identify and predict key factors contributing to homelessness among women and children. By analyzing these predictors, the model aims to inform targeted interventions and improve support services. details

A few words from people who worked with me in the past

“Hamza's ability to rapidly acquire and apply new skills, combined with his proactive approach and commitment to excelling in his role, consistently exceeded expectations. His dedication, adaptability, and strong communication skills made him a valuable team member, and I highly recommend him for any future opportunities.”

alternative
Angelo Cordon
Senior Software Engineer - HashiCorp

Contact Details

For any type of online project please don't hesitate to get in touch with me.