I didn’t set out to become a researcher, much less an applied one. My journey began at Cornell University, where I studied organizational behavior (OB) with the goal of becoming an industrial-organizational (IO) psychologist. Yet, my drive to achieve sustainability goals and my belief in the power of data and statistics to drive meaningful action ultimately reshaped my path.
A service trip to Haiti in 2013 was a turning point. I witnessed firsthand how inadequate waste management infrastructure—no dumpsters, garbage trucks, or recycling bins—creates a vicious cycle: littering, illegal dumping, and open burning lead to crime, environmental degradation, and air, soil, and water pollution. The data was clear: island nations face losses of nearly $2.5 billion annually if we fail to overhaul the outdated make-take-waste model. Garbage, the most visible and visceral element of sustainability challenges, became my unlikely passion. This experience ignited my interest in data science and inspired me to earn a master’s degree in sustainability management from Stevens Institute of Technology.
I shied away from programming initially. However, that changed when, six years ago, in graduate school, I started using R and SQL for statistical analysis and data management. Tools like R Studio transformed how I approached data, showing me the limitations of Excel for handling multidimensional datasets. Around the same time, I embraced the command line and Git to manage and share projects. A year later, while taking 100 Days of Code, I transitioned to Python—a shift that expanded my skills and sparked my love for programming. Since then, I’ve deepened my expertise, diving into languages like JavaScript and Go and discovering the endless possibilities software development offers.
Published a 7-page report on sustainability aptitude at Stevens Institute of Technology by designing, distributing, and analyzing a campus-wide survey in 2020, then recommending best practices for improving student education on environmental sustainability (Excel).
Visualized how well students incorporated sustainability into engineering capstone design projects by comparing sustainability assessment grades against final project grades, then presented the results at a peer conference in 2021 (R and Markdown).
Analyzed PetMind sales data to identify product repurchase patterns, evaluate whether repeatedly purchased products performed better in sales, and recommend product opportunities for a monthly pet box subscription.
Evaluated sales tactics for Pens and Partners by analyzing customer engagement, revenue distribution, and revenue trends over time to recommend which sales methods the company should prioritize.
Built an interactive dashboard providing a global snapshot of LGBTQ+ rights by visualizing publicly available legal and social indicators in Streamlit (Python).
Applied Research Methods: Survey design, questionnaire development, descriptive analysis, cross-tabulation, statistical modeling, machine learning (regression, classification)
Data Analysis: Excel (advanced), Python, Pandas, NumPy, SciPy, Statsmodels, Jupyter
Data Visualization & Dashboards: Tableau, Streamlit, Matplotlib, Seaborn
Research Communication: Markdown, Word, PowerPoint, executive summaries, technical reports, data storytelling
Web Development & Data Applications: HTML/CSS, Flask, SQLAlchemy, REST API development and integration
Automation & Developer Tools: Beautiful Soup, Selenium, Postman, Command Line (Bash/Zsh), Git
I love to bike, learn, volunteer, swim, spend time with friends...all of the nerdy stuff you'd expect from someone who likes to play on his computer.
I also blog regularly: on civic issues, reducing food waste, recycling, startups, and so much more. Whatever crosses my mind and I have an insight, I write about it.
I make software and data projects for fun, too. Check a few samples out by checking out my GitHub!
