Economics
Rural
Dedication
Sustainable Development
Economic Solutions
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01.
Co-Author
The Research
“The Impact of Investment Capital on Clean Water Supply in Vietnam's Northern Midland and Mountainous Region”
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Mentored by MSc. Nguyen Van Quan - Academy of Policy and Development (APD), Ministry of Planning and Investment
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Published @ International Journal of Academic Management Science Research
I used to think that more investment naturally meant better living conditions. But researching clean water access in Northern Vietnam made me question that assumption. Working with data from 14 provinces and interviewing local officials and families, I explored why some communities still struggled despite public investment
Surprisingly, our regression analysis found a negative association between public investment and clean water access. It left me wondering whether funding was being used effectively or simply directed toward the areas facing the greatest difficulties.
This research experience taught me that behind every economic statistic lies a much more complicated human story.
02.
Qualitative
Researcher
The Research
“Applying the Circular Economy Model to Enhance Soil Sustainability and Reduce Chemical Dependence: A Case Study of Nga My Commune, Thai Nguyen Province"
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Mentored by Assoc. Prof. Dr. Nguyen Phuc Hien Director of the Center for Testing and Quality Assurance, Foreign Trade University
What happens when farm waste becomes part of the solution instead of the problem? I explored this question at Nga My Agricultural Cooperative in Thai Nguyên, where I observed how livestock waste was transformed into organic fertilizer and returned to the fields. Through fieldwork, interviews with farmers and local officials, and thematic analysis, I examined the economic benefits and practical challenges of circular farming.
Cooperative managers reported 25–30% lower input costs and 15–20% higher incomes, yet limited financing and technical expertise remained major barriers. I proposed green credit and training programs to help farmers adopt these practices. Seeing this cycle firsthand made me curious about how economic incentives could make sustainable agriculture more accessible.
03.
Founder & President
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We began by selling lì xì envelopes I designed to raise funds for water filters in mountainous schools. I thought providing clean water was a straightforward way to help, until I met a woman in Lao Cai whose water sometimes ran green, yet who was afraid to report it because someone might get punished. Her problem wasn't simply a lack of clean water; it was a system she couldn't easily challenge.
Claro Project
In September 2024, just weeks into tenth grade, Typhoon Yagi struck Northern Vietnam. Heavy rains flooded roads in Lang Son, bringing my dad's quarry to a complete standstill. I watched him quietly assess the damage and rebuild what years of hard work had created. For the first time, I realized how quickly a disaster could disrupt someone's livelihood, even when nobody had done anything wrong. Three months later, I founded Claro, not because I knew how to solve environmental problems, but because I wanted to stop watching them from a distance.
Determined to look beyond short-term solutions, I led our 30+ members into the rice fields of Hai Hau, where we helped over 30 farmers adopt Alternate Wetting and Drying (AWD) irrigation. We installed water-level monitoring tubes, developed a Farmers' Handbook, and explored how water conservation could make economic sense for farming households. We also partnered with 20+ families to transform 1.5 tons of rice straw into mushrooms and organic fertilizer, generating $965 in revenue and returning 40% of profits to the farmers and their cooperative.
As a child, I spent my snack money buying cotton swabs from elderly street vendors, thinking that was my way of helping. Claro brought me back to that same instinct, but with a harder question: How do we build solutions that people can afford, benefit from, and sustain long after we've left? I'm still figuring it out, one conversation and one rice field at a time.
Climate Risk
Technological Innovation
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01.
Co-Author
The Research
“Event Aware Flood Mapping for Agricultural Landscapes:
A Robustness Oriented Comparison of Deep Learning and Machine Learning in the Arkansas 2025 Flood Event"
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Mentored by Eng. PhD Student. Vu Manh Dung & Prof. Ming-Che Hu - Department of Bioenvironmental Systems Engineering, National Taiwan University
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Accpeted for publication @ Indonesian Journal of Geography
Claro showed me how difficult it can be to address environmental problems already affecting people's lives. But Typhoon Yagi left me with another question: What if we could anticipate the economic costs of disasters before they happen?
That curiosity led me to research the 2025 Arkansas floods. I integrated satellite, terrain, and rainfall data, developed and compared U-Net (Deep Learning) and Random Forest (Machine Learning) models, and mapped agricultural flood exposure. Surprisingly, Random Forest outperformed U-Net by 33% in IoU and 24.5% in F1.
What fascinated me most was where the models disagreed, especially along flood boundaries where uncertainty matters most. By identifying vulnerable farmland, I began seeing flood prediction not just as a technical challenge, but as a way to make hidden economic risks visible before communities bear their costs.
02.
Researcher & Inventor
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FloodSight AI
A flood doesn't wait for farmers to finish harvesting. By the time the water arrives, crops, investments, and months of hard work may already be lost. After researching flood mapping, I became interested in a different challenge: making disaster risk information useful before those losses occur.
I developed FloodSight AI, a web-based platform that combines real-time weather data, GIS, and Machine Learning to assess flash flood risks in agricultural areas. I experimented with Random Forest, Decision Tree, and Ensemble Learning models, refining their performance through Grid Search and Random Search. I then translated weather and terrain data into GIS heatmaps, built an interactive dashboard, and integrated live weather APIs to display risk levels and warnings.
What excites me most isn't the complexity of the algorithms, but the possibility of turning them into something a farmer can actually understand and use. A prediction alone cannot stop a flood, but accessible information could help someone make a better decision before it arrives.
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