ABOUT
I'm Daisy, a practical builder with a background in Computer Science and Mathematics from CUNY Queens College.
I'm interested in the places where software, data, logic, and real-world workflows meet. In college, I explored different technical areas through coursework and research-related projects, including cryptography, software engineering, systems, machine learning, and mathematical research. While I did not continue deeply into academic research, these experiences helped me see how mathematics, data, and computing can work together to understand problems, find patterns, and build useful solutions.
Over time, I found myself more drawn to practical software work — especially tools that make messy or repetitive work feel lighter. My current work often involves spreadsheets, manual steps, unclear workflows, and data that needs to be cleaned, checked, matched, or reorganized. I enjoy breaking these processes down, finding patterns, and turning them into cleaner systems using tools like Python, SQL, FastAPI, React, PostgreSQL, pandas, and Excel-based automation.
Outside of work, I also teach beginner Python to younger students using Turtle and Pygame. Teaching helps me think more clearly about structure, usability, and how to explain technical ideas in a way that feels approachable.
I'm currently open to different paths where I can keep building useful things and growing as a developer. I'm especially interested in full-stack development, backend engineering, data engineering, workflow automation, and other software roles that connect technical problem-solving with real-world needs.
This website is where I document my projects, learning notes, teaching materials, and creative explorations along the way.
ACADEMIC EXPLORATION
Alongside my Computer Science and Mathematics coursework, I participated in several research-oriented academic programs that helped me explore mathematical modeling, machine learning, and technical communication.
Spring 2023
CUNY Directed Reading Program
Created a poster exploring the role of mathematics in collective behaviors. The project introduced me to how mathematical ideas can explain synchronization in nature and helped me practice presenting technical concepts in an accessible way.
Summer 2023
RAMMP Summer Research Program
Contributed to an early-stage research project and was later acknowledged in a published paper. Although I was unable to continue long-term because of a heavy academic schedule, the program gave me exposure to collaborative research, presentation preparation, and mathematical problem-solving.
Summer 2024
Summer Research Opportunity in Machine Learning
Explored neural networks, document vectorization, and automated classification of arXiv papers. Through the program, I gained hands-on exposure to machine learning concepts, text representation, and research questions in document classification.
TECHNICAL TOOLKIT
CONTACT