Exploring rigorous methods in statistics and machine learning.
Hi, I'm Justin Philip Tuazon! You can call me Justin. I'm a data science professional and researcher experienced in leveraging mathematical and computational methods to solve problems, with proficiency in developing and applying quantitative methods, programming, and automation.
Recent Highlights
Presentation at the 2026 International Meeting of the Psychometric Society
I recently presented our research, Pairwise Target Rotation for Factor Models, in an oral session at the 2026 International Meeting of the Psychometric Society (IMPS) held at Yonsei University in Seoul, South Korea back in July 2026. This work focuses on developing an intuitive yet flexible method for incorporating a priori information, such as item semantics, into factor rotations. The approach can be used to produce interpretable factor solutions and effectively characterize latent variables.
Poster at the 2026 American Educational Research Association Annual Meeting
Our work, Design and Implementation of Reduced Longitudinal Experiments, was selected from over 13,000 submissions for poster presentation at the 2026 American Educational Research Association (AERA) Annual Meeting. It focuses on characterizing hierarchical linear models to produce practical recommendations for designing and implementing longitudinal experiments. My co-author, Le Dolino, presented our paper at the conference back in April 2026 in Los Angeles, California.
About Me
I am an early-career Data Scientist and Researcher passionate about statistics and machine learning. My work centers on developing novel quantitative methods, as well as intelligent systems, and creatively applying such, ultimately combining rigorous modeling with clever approaches to uncover complex patterns in data. Currently, my research and professional practice focus on latent variable models, mixed-effects models, and causal machine learning.
Moreover, I am currently pursuing an M.S. in Computer Science at the University of the Philippines Diliman (UPD), where I am affiliated with the Computer Vision and Machine Intelligence Group of the Department of Computer Science. I previously earned my B.S. in Statistics degree from UPD, graduating summa cum laude back in 2023.
Outside of academics and work, I enjoy playing video games and playing the guitar. 🙂
- Affiliated with the Computer Vision and Machine Intelligence Group
- Won the 1st Place Best Graduate Student Paper Award at the 25th Student-Faculty Conference on Statistical Sciences
- Co-authored a research paper on factor analysis and presented it in an oral session at the 2026 International Meeting of the Psychometric Society (IMPS) following peer-reviewed acceptance
- Co-authored a research paper on longitudinal experiments that was selected from over 13,000 submissions for poster presentation at the 2026 American Educational Research Association (AERA) Annual Meeting following peer-reviewed acceptance
- Graduated summa cum laude
- Represented the university at the 25th Philippine Statistics Quiz, and won as NCR Regional Champion and National Finalist
- DOST Merit Scholar
- Consistent University Scholar
- Pi Gamma Mu Honor Society Nominee
- Phi Kappa Phi Honor Society Nominee
- Vice President for Academic Affairs at UP Investment Club (A.Y. 2022 — 2023)
- Graduated with high honors
- Represented the school and won in various Mathematics, Statistics, and Economics competitions
- Part of the Data Science and AI Solutions team
- Develops and implements machine learning models and AI solutions (e.g., recommender engines, causal models) to solve business challenges, drive revenue and profit growth, and improve operational efficiency
- Leverages Python, SQL, AWS SageMaker, and Snowflake for model building and evaluation
- Infrastructure Intermediate Technology Analyst
- Developed an interactive dashboard (using PHP, SQL, and JS) that provided real-time figures and trends on service delivery quality
- Created scorecards on performance and productivity, covering 10+ sources and metrics, using Power Query and Power Pivot
- Completed the bank’s global 2-year Management Development Program, an exclusive accelerated track for high-potential talent to build leadership skills and cross-functional expertise
- Built data systems and tools using PHP, SQL, JavaScript, VBA, HTML, and CSS
- Developed a QA platform with analytics, role-based authentication, data validation, notifications, and admin tools, automating workflows and delivering real-time insights from 2,000+ audits monthly
- Launched a site for streamlined communication and knowledge sharing, driving 38,000 visits from 200+ users in 2.5 months
- Created Tableau and Power BI dashboards analyzing 100,000s of data points across key performance metrics
- Performed statistical analyses (e.g., mixed-effects models, generalized linear models, and exploratory analyses) for academic studies across various disciplines (e.g., health sciences, social sciences, and architecture).
- Collaborated with clients to assess statistical needs and explain complex concepts.
- Advised on research design, data collection, and analysis methods to improve study rigor.
- Facilitated workshops on research and statistical analysis for teachers and students.
- Data Freelancer
- Built analytical models (e.g., credit risk), and supported performance evaluation and model deployment.
- Conducted statistical analyses (e.g., unsupervised and supervised learning, statistical modeling, and hypothesis testing) to address operational gaps, and improve products and processes.
- Developed data tools and dashboards with SQL, Databox, Excel, Google Sheets, Data Studio, JavaScript, HTML, CSS, and VBA.
- Delivered insights through clear reports and presentations to both technical and non-technical stakeholders.
- Provided analytical support for operational projects (e.g., KPI design and survey development).
- Utilized R, Python, and SQL for advanced analysis and model development.
- Worked on workforce analytics and automated reporting, with various data sources and options, using VBA and Power Query
- Co-developed the syllabus, and wrote materials and exercises about several Python packages, web scraping, and basic statistics
- Served as one of the panelists during the interns’ capstone project presentations
- Worked in teams to formulate data-driven solutions to fields such as consumer profiling, market research, and credit risk analysis
- Created a comprehensive web-based dashboard with built-in machine learning implementation (text clustering) to automate data transformation, calculations, and visualizations for consumer behavior insights using Python
- Was given special recognition for outstanding performance
Research & Projects
Click on the icon(s) at the top right of each card for more details.Pairwise Target Rotation for Factor Models
We developed a new factor rotation method (an unsupervised learning technique) and its Python implementation, that can incorporate arbitrary prior information (e.g., semantics) for exploration and model building.
Presented at the 2026 International Meeting of the Psychometric Society (IMPS) in an oral session.
Won 1st Place Best Graduate Student Paper Award at 25th Student-Faculty Conference on Statistical Sciences.
Design and Implementation of Reduced Longitudinal Experiments
We characterized hierarchical linear models through the design and analysis of a Monte Carlo experiment (including the simulation of nested data, attrition, and more), implemented in R, to produce recommendations for longitudinal experiments.
Presented at the 2026 American Educational Research Association (AERA) Annual Meeting in a poster session.
FactorFlow: A Visual Analytics Workspace with Large Language Model-Assisted Interpretation for Factor Analysis
I developed an LLM-enhanced visual workbench for exploratory factor analysis with interactive model building and automated interpretation.
Match App
I implemented Gower’s Distance and Binary Integer Linear Programming using R and created a web app for a student council initiative that involved optimally grouping students for theses.
Simulated Normality Test
For a course project in an undergraduate class, we explored an alternative test for normality. I also made an R package implementing the test. We leveraged Monte Carlo simulations to characterize the null distribution of the test statistic after establishing its ancillarity.
TREE$
I made a game for one of my courses during my first semester in college. The game was made using Unity, with C# as the programming language. The simple design assets were made using Microsoft PowerPoint while the background music was created using Chrome Music Lab - Song Maker.
Skills
Experienced with core machine learning (e.g., supervised and unsupervised learning, classification and regression, recommender systems), statistical modeling (e.g., mixed-effects models, generalized linear models, factor models, uplift models), experimental design, hypothesis testing, computational statistics, and applied domains (e.g., computer vision, natural language processing).Core Skills
Technical Languages
Data Tools and Software
Selected Awards
• Event organized by Philippine Statistics Authority.
• Individual Elimination Round: 1st Honors
• Individual Elimination Round: 2nd Honors
• Individual Elimination Round: 2nd Honors
Other activities
Resource Speaker
During the Data Science and Analytics Group Q2 Townhall at UnionBank of the Philippines, I gave a Knowledge Sharing session (i.e., lecture) on latent variable modeling (particularly, factor models). During the talk, I provided an introduction to factor analysis, including its mathematical background, its applications, and some recent developments in the field.
Chief Research Officer
I volunteer as the Chief Research Officer at Beyond the Charts, a team of passionate individuals who believe that numbers should speak to everyone. Our shared purpose is integrating statistics and medicine to advance health.
We aim to empower leaders, communities, and everyone by:
• Democratizing data
• Bridging knowledge gaps
• Advocating for accessibility of information to all
Learn more about us at https://www.facebook.com/beyondthecharts.
Keynote Speaker
I gave a talk to over 30 young students and aspiring Pisay scholars, sharing my journey from school to a career in STEM. I provided advice, answered questions, and hopefully inspired the next generation of Filipino innovators to embrace the challenges ahead.
Resource Speaker
I co-facilitated a research workshop for students and educators, collaborating with colleagues to instruct participants on the end-to-end research process, technical concepts, and quantitative methodologies.
Guest Speaker
In my freshman year, as the representative of students who participated and/or won in local/international competitions and/or conferences, I gave a short speech sharing my experience and encouraging my fellow students to strive for excellence during the University's recognition day.
Let's Collaborate
Interested in statistics, machine learning, and data science? Feel free to connect!