Warm architectural photography

Pat Leetongin

A passionate individual dedicated to learning, growing, and making a meaningful impact through education, work, and community.

01 — About

Warm workspace with books and coffee

About Me

I am a driven and curious individual with a strong foundation in academics and a genuine passion for making a difference in the world around me. My journey has been shaped by diverse experiences in education, part-time work, volunteering, and research.

I believe in the power of continuous learning and community engagement. Whether in the classroom, the workplace, or the community, I approach every opportunity with dedication, empathy, and a desire to grow.

Outside of my professional and academic pursuits, I enjoy watching good movies, reading, exploring new ideas, and connecting with people from all walks of life.

02 — Education

Academic Background

Master of Data Science

Monash University

2023 - 2025

Developed strong expertise in statistical modelling, data wrangling, visualisation, big data processing, and semi-structured data analysis. My thesis strengthened my research and problem-solving skills by applying data-driven methods to real-world challenges. Graduated with High Distinction.

Data Analysis for Semi-Structured DataData Exploration and VisualisationData WranglingData Processing for Big Data

Bachelor of Engineering in Computer Engineering

King Mongkut's University of Technology Thonburi

2018 - 2022

Built a strong foundation in software engineering, data structures, algorithms, and machine learning, with a focus on problem-solving and system design.

Data Structures & AlgorithmsMachine LearningSoftware EngineeringDatabase SystemsData MiningText AnalysisCoding in AIComputer ArchitectureOperating Systems

High School Diploma

Amatyakul School

2003 - 2018

Excelled in STEM subjects with a strong focus on mathematics, physics, and chemistry.

Advanced MathematicsPhysicsEnglish

03 — Experience

Work

Front of House / Host

Mango Tree Thai

2024 - Present

Alongside my postgraduate studies, I have worked part-time at Mango Tree Thai, managing front-of-house operations in a high-volume restaurant serving over 150 guests per night on weekends. I oversee bookings, table allocation, and guest flow to maximise capacity during peak periods while maintaining a positive dining experience. This role has strengthened my communication, problem-solving, and time-management skills, as I regularly coordinate with kitchen and service teams to ensure smooth operations under pressure.

Decision MakingTeamworkTime ManagementCommunicationMultitasking

Data Engineer Intern

Kiatnakin Phatra Financial Group

June - July 2020

During my internship at Kiatnakin Phatra Financial Group, I supported enterprise data pipeline development using IBM DataStage and assisted with cloud-based implementations through Microsoft Azure. This experience introduced me to large-scale data management practices within a financial services environment and strengthened my understanding of data architecture. I also earned the Microsoft Certified: Azure AI Fundamentals certification, building a strong foundation in AI and cloud technologies.

Time ManagementCommunicationAzure

04 — Giving Back

Volunteer Work

Englsih Tutor

Local Youth Center

I have volunteered as an English tutor across both private education and university settings, supporting students in developing their language and communication skills through online Platform, Hint Co. In addition, I volunteered as an English teacher in rural Thailand, where I adapted lessons to different learning levels and classroom environments. These experiences strengthened my ability to communicate clearly, remain patient, and tailor explanations to individual needs. Teaching has reinforced my belief in accessibility and inclusive learning — values that continue to influence my academic and professional work.

2021 - 2023

Event Staff

Monash University

I volunteered during Orientation Week with the Monash Student Association (MSA), supporting event coordination and assisting new students as they transitioned into university life. I helped provide directions, answered enquiries, and ensured activities ran smoothly in a busy, fast-paced environment. This experience strengthened my teamwork, communication, and adaptability skills while allowing me to contribute to creating a welcoming and inclusive campus community.

2023 - 2024

Aged Care Resident Visitor / Ward Ambassador –

Monash Health

As a volunteer at Monash Health, I support elderly patients and residents by providing companionship and assisting with non-clinical needs to help create a positive ward environment. I spend time engaging residents in conversation and activities, ensuring they feel heard, valued, and comfortable. This experience has strengthened my empathy, active listening, and communication skills, particularly in adapting my approach to suit different emotional states and cognitive conditions. It has also deepened my appreciation for patient-centred care and the importance of human connection in healthcare settings.

2023 - Present

05 — Research

Papers

Intake24: SWIPE

TBC · TBC

Pichapat Leetongin

Read Paper

Dietary assessment is essential for understanding nutrition and shaping public health policy. Traditional methods such as 24-hour recalls are accurate but resource-intensive, while food frequency questionnaires are cheaper but less precise. Technology-based tools aim to bridge this gap, yet their reliance on detailed self-reporting can limit accessibility for people with low literacy or digital skills. This study developed and evaluated a machine learning–driven dietary assessment method that classifies individuals into nutrient profiles using simplified binary and portion-based questions derived from historical intake data. Using anonymised Australian Intake24 records (834,242 food entries from 49,954 participants), foods were clustered by macronutrient ratios and meal timing. The top 50 features were converted into yes/no questions with small, medium, and large portion options. XGBoost classifiers for protein, fat, and carbohydrate were trained and tested. The models achieved accuracies of 74.3% (protein), 71.2% (fat), and 73.8% (carbohydrate), with macro-averaged F1-scores around 0.70. This approach provides a low-burden alternative to conventional methods, with potential for adaptive questioning and cross-cultural use.

Machine LearningDietary AssessmentNutritionPublic Health

06 — Contact

Let's Connect

If you would like to discuss a project, collaboration, or just say hello, feel free to reach out. I am always open to new opportunities and conversations.