Sungchul Seo

College of Engineering

South Korea

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Articles (15)

Year:

2025

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2025

Year:

2024

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2024

We characterized radon exposure levels at the workplaces and underground public-use facilities using short/long-term, and real-time detectors. The mean radon level in the underground facilities was observed 1.8-fold higher than that at workplaces.

Year:

2023

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

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2020

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2020

Collaborators (3)

Jinhyeon Park

Daegu University

SOUTH KOREA

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Woo Kyung Kim

Professor

Inje University Ilsan Paik Hospital

SOUTH KOREA

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Lakshman Tamil

Professor

University of Texas at Dallas

UNITED STATES

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Sungchul Seo

Research Interests

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Articles (15)

Revisiting the joint effect of temperature and relative humidity on airborne mold and bacteria concentration in indoor environment: A machine learning approach

Area‐Specific Assessment of Stratum Corneum Hydration and Transepidermal Water Loss in Pediatric Patients With Atopic Dermatitis

Enhancing Particulate Matter Estimation in Livestock-Farming Areas with a Spatiotemporal Deep Learning Model

Digital environmental health: a digital platform for preliminary prevention and intervention

Occupational exposure monitoring for radon in various manufacturing workplaces and underground public-use facilities in Korea

Performance evaluation of an electrostatic precipitator with a copper plate using an aerosolized SARS-CoV-2 surrogate (bacteriophage phi 6)

Occupational exposure monitoring for radon in various manufacturing workplaces and underground public-use facilities in Korea

Optimizing Reinforcement Learning Control Model in Furuta Pendulum and Transferring it to Real-World

Identification of Bacteria and Fungi in Various Types of Multi-Use Facilities in Bucheon, South Korea

Ambient PM Concentrations as a Precursor of Emergency Visits for Respiratory Complaints: Roles of Deep Learning and Multi-Point Real-Time Monitoring

Spatial modeling for radon concentrations in subway stations in Seoul, Korea

Real-Time Low-Cost Personal Monitoring for Exposure to PM<sub>2.5</sub> among Asthmatic Children: Opportunities and Challenges

Machine Learning-Based Asthma Risk Prediction Using IoT and Smartphone Applications

Spatial and Temporal Exposure Assessment to PM2.5 in a Community Using Sensor-Based Air Monitoring Instruments and Dynamic Population Distributions

Five Year Trends of Particulate Matter Concentrations in Korean Regions (2015–2019): When to Ventilate?

Collaborators (3)

Jinhyeon Park

Woo Kyung Kim

Lakshman Tamil

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