{
"name": "Daniel Hu",
"occupation": "Data Scientist",
"likes": ["Math", "Coding", "Badminton"],
}
About Me
I’m a data science student at the University of Waterloo, passionate about problem-solving and applying computational concepts to real-world challenges. Having completed the IB Program and driven by self-learning, I’ve expanded my expertise through Stanford University & DeepLearning.AI's Algorithms, Machine Learning, and Deep Learning Specializations. I'm passionate and versatile, leveraging technologies like Java, Python, C, C++, SQL, React, JavaScript, and TypeScript to build impactful and efficient solutions.
Currently, I’m a Data Science Intern at ESDC, conducting multivariate regression to improve EI approval rates. Previously, as a Software Engineering Intern at Tramona, I developed web scrapers and designed full-stack platform features. On campus, I lead and contribute to the CS Club and Data Science Club, working on AI-powered apps and judging hackathons, while honing my technical and leadership skills.
Outside of work, I’m a national badminton player, with an all-time highest junior ranking of fourth in Canada. The sport has instilled in me resilience, discipline, and teamwork. I also promote inclusivity through Bridge to Badminton. Balancing my passions for math, data science, software engineering, and sports, I’m dedicated to making a positive impact in the world and exploring new ways to innovate.
Experience
Software Engineering Intern
Contributed to full-stack development using Next.js, tRPC, Drizzle ORM, and Tailwind CSS, focusing on scalability while maintaining a large codebase with over 1000 files.
Implemented a dynamic scraper to automate data retrieval for client listings and automated email systems to enable real-time reminders for thousands of users.
October 2024 - April 2025
AI Engineering Intern
Seattle, Washington, United States · Remote
San Francisco, California, United States · Remote
Data Science Intern
CodeyBot Developer
Tramona
Hangzhou, Zhejiang, China · On-site
October 2024 - Present
July 2024 - August 2024
August 2024 - October 2024
Outlier
GE Vernova
UW Computer Science Club
Utilized Java, Python, C, JavaScript, and TypeScript to develop, test, and fine-tune scalable AI model training pipelines, focusing on efficient and robust architecture.
Conducted performance evaluations, troubleshooting issues for deployment, and maintaining documentation to ensure model reproducibility across 10+ models.
Automated data managing for Bills of Materials using VBA, reducing execution time from 5 hours to 5 minutes and eliminating previous manual approach errors.
Developed Smartsheet automation scripts for factory-wide data management and proposed optimization ideas for machine operations based on data analysis.
Built features for and maintained a Discord bot to improve communication and automation in the CS Club server.
Lead a team in the CSC Projects Program to develop Study Buddy, an AI-powered platform that matches University of Waterloo students with study partners based on academic goals and course enrollment.
Waterloo, Ontario, Canada · On-site
Data Science Intern
ESDC
April 2025 - Present
Ottawa, Ontario, Canada · Hybrid
Performed multivariate regression in Python and R to identify bottlenecks in EI approvals, improving outcomes for over 5000 daily applicants and informing corrective action.
Built 25+ Power BI features processing more than 40 million data points, and collaborated with 20+ stakeholders to reduce Azure data validation time by 77% in Agile sprints.
Data Science Mentor
UW Data Science Club
September 2024 - April 2025
Waterloo, Ontario, Canada · On-site
Mentored participants and judged CxC 2025, Canada’s largest datathon, while also leading technical workshops and facilitating AI paper discussions.
Developed educational content, including visualizations and technical reels, on data science, AI, and machine learning to engage members and enhance learning.
Education
University of Waterloo
St. Robert Catholic High School
Stanford University, DeepLearning.AI
Bachelor of Mathematics, Data Science
Ontario Secondary School Diploma, International Baccalaureate Diploma
Expected April 2028
Completed December 2024
Graduated June 2024
Projects
Lights Out Puzzle Game
I created a web-based version of the classic Lights Out puzzle game using HTML, CSS, and JavaScript. The objective is to turn off all the lights on a grid, where clicking a light toggles its state (on/off) and that of adjacent lights. This version includes multiple grid sizes, adjustable difficulty levels, and a timed mode for an extra challenge. The game offers a sleek, responsive design and can be played online at lightspuzzlegame.ca.
I collaborated with peers and industry mentors at Inspirit AI to develop a high-performance object detection algorithm for autonomous vehicles, achieving a 0.99 confidence score. The project focused on harnessing the YOLO (You Only Look Once) architecture using the Darknet framework. By leveraging advanced machine learning techniques with TensorFlow, Keras, and PyTorch libraries, the algorithm identifies and classifies various objects on the road, ensuring safe and efficient navigation.
Object Detection Algorithm
Formula 1 Strategy Master
Bill of Materials Tools
Formula 1 Physics Paper
Multiplayer Tank Maze Battle
I built F1 Strategy Master, a dynamic web app that allows users to explore historical Formula 1 race data and simulate race strategies. Users can customize tire choices, stint lengths, weather conditions, and tracks to generate optimal strategies. The app adapts to the number of pit stops, providing tailored options for each stint. Built using Python, Node.js, JavaScript, EJS, CSS, and PostgreSQL, the app leverages the random forest classifier machine learning model to predict finishing positions, bringing the thrill of real-time strategy decision-making to life.
I spent 1.5 years analyzing how the angle of attack of an F1 race car front wing affects aerodynamic efficiency and successfully determined the most optimal angle. Driven by my engineering aspirations, I self-taught myself to conduct (CFD) Computational Fluid Dynamics simulations on SolidWorks Flow Simulation, and modelled a multi-element front wing to analyze the effects of varying angles from 0° to 18°. The research explores the interplay between lift, drag, and the lift-to-drag ratio, identifying 11° as the most efficient angle, providing the highest downforce with minimal drag.
I created a powerful and intuitive toolkit using VBA designed to streamline the management of Bills of Materials (BOM) across manufacturing and engineering workflows. The toolkit automates the generation and modification of Manufacturing and Engineering BOM data, allowing users to easily update descriptions and clear sheet contents when necessary. This solution reduced the operational execution time from 5 hours to 5 minutes while achieving 100% accuracy in data management for all BOMs, significantly minimizing manual errors.
I developed a 2-player tank maze battle game using Python's Pygame where two players control a blue and red tank respectively, navigating through a maze while attempting to eliminate each other. Players can fire bullets that bounce off walls and disappear after a few seconds. The game ends when a bullet successfully hits and destroys the opposing tank. The project emphasizes real-time player interactions and strategic gameplay. Click the learn more button to discover a few other games I have developed using Python and Java, including Snake, Tic Tac Toe, and an Adventure Story Game!
Market Wire
I developed Market Wire, an all-in-one platform built at HackPrinceton '24 to simplify smart investing. Market Wire analyzes news-driven sentiment in real time to send instant alerts, advising users when to buy or sell for maximum profit. With user consent, transactions can even be automated for optimal results. Combining personalized real-time trends, stock insights, and company research, Market Wire keeps users ahead of market dynamics. Built with Python's FastAPI, Beautiful Soup for web scraping, a machine learning model, Supabase, and frontend with Next.js, React, TypeScript, and Tailwind CSS. Try Market Wire today at marketwire.vercel.app.
Study Buddy
I spearheaded the development of Study Buddy as project team lead in the CSC Projects Program, creating an AI-powered platform that connects University of Waterloo students with ideal study partners. Using a custom K-means clustering algorithm, it matches students based on academic goals, courses, learning styles, and availability. The platform enables profile updates, allows for ratings, schedules sessions, and gamifies progress with a leaderboard. Built with a Django backend, SQLite database, and HTML/CSS frontend, Study Buddy enhances collaboration and academic success.
Technical Proficiencies
Jupyter
C/C++
JavaScript/Node.js
HTML/CSS
Tensorflow/Keras
TypeScript
Racket
Python
PostgreSQL
Java
VBA
React/Next.js
Git/GitHub
Azure
Power BI
Achievements
Certifications
Throughout my academic and professional journey, I have earned many notable achievements that highlight my dedication, hard work, and passion for excellence. They span from excelling in math and computer science contests, earning school highest achievement awards, winning medals at Canadian National Badminton Tournaments, receiving accolades in piano, and being selected for prestigious fellowships.
Milestones
I have earned a variety of certifications that reflect my commitment to continuous learning and skill development. My certifications span from completing the Machine Learning Specialization and Deep Learning Specialization, being recognized as an AI Scholar by Inspirit AI, and mastering full-stack technologies through the Complete Web Development Bootcamp, and earning a Remote Pilot Certification.
I had the pleasure of overlooking Daniel's work at GE Vernova, where he consistently delivered strong results as our data science intern. He took on complex projects and exceeded expectations, resulting in notable cost savings with an effective optimization of our data management system and his custom-built BOM online toolkit. He embraced feedback for continuous improvement, and clearly articulated his ideas, one of which is now being implemented on a larger scale. Daniel was a key contributor to our team, and any organization would benefit from his skills and dedication.
Sandy Yang, GE Vernova General Manager
During his summer internship at GE Vernova, Daniel always brought a positive and enthusiastic attitude to every task, significantly boosting our team's morale. He automated our bonus reports, BOM conversion and weekly machining plans, all of which greatly improved efficiency across the factory. Daniel was eager to learn and quickly mastered new tools, such as VBA, which he had no prior experience with. He kept challenging himself for more tasks and asked always for reflections not only on what he did but also on how he did the job. Daniel's adaptability, seamlessly integrating himself into any situation, coupled with his initiative on projects, were particularly impressive. His ability to deliver high-impact solutions makes him an asset to any team, and I would highly recommend working with him!
Wang Weikai, GE Vernova Materials and Planning Manager
