Assist. Prof. Dr. Pin-Chun Huang | Environmental Science | Best Researcher Award
Assist. Prof. Dr. Pin-Chun Huang, National Taiwan Ocean University, Taiwan
Dr. Huang is an expert in hydrology and river engineering with extensive experience in rainfall-runoff modeling and flood prediction. He holds a Ph.D. from NTOU and has received numerous awards, including the 2022 Excellent Young Scholars Award from Taiwan’s National Science and Technology Council. He has published widely in high-impact journals, focusing on hydrological and geomorphological systems for flood and coastal inundation forecasting. 🌊💧🌐📚
Publication Profile
Professional Experience
Assist. Prof. Dr. Pin-Chun Huang has a diverse academic and research background. Since February 2022, he has been serving as an Assistant Professor in the Department of Harbor and River Engineering at National Taiwan Ocean University (NTOU). He also has experience as a Visiting Scholar at several prestigious institutions, including the University of California, Irvine (2019) and Moscow State University (2017). Dr. Huang worked as an Assistant Research Fellow at NTOU’s Center of Excellence for Ocean Engineering from 2018 to 2022. Additionally, he held a postdoctoral position at NTOU from 2016 to 2018. 🌍🔬📚
Education
Assist. Prof. Dr. Pin-Chun Huang has an extensive academic foundation in Harbor and River Engineering from National Taiwan Ocean University (NTOU). He earned his Ph.D. in 2016, following a Master’s degree in 2013, both from NTOU’s Department of Harbor and River Engineering. Dr. Huang’s academic journey began at NTOU in 2007, where he completed his Bachelor’s degree in 2011. His solid educational background equips him with deep expertise in hydrology, hydraulics, and engineering research. 📘🎓🌊
Awards and Honors
Assist. Prof. Dr. Pin-Chun Huang has received numerous prestigious awards throughout his career. In 2022, he was honored with the Excellent Young Scholars Award by Taiwan’s National Science and Technology Council. Dr. Huang also received the Academic Research Advancement Award from National Taiwan Ocean University in 2021. His academic excellence has been recognized with an Honorary Membership in the Phi Tau Phi Scholastic Honor Society (2016), and the Best Paper Award at the Disaster Management Conference (2013). Additionally, he was awarded the Engineering, Science, and Technology Scholarship by China Engineering Consultants in 2011 and 2012. 🏅🎖️📜
Research Interests
Assist. Prof. Dr. Pin-Chun Huang’s research interests are focused on surface hydrology and channel hydraulics, aiming to better understand water flow and flood behavior in various environments. His expertise includes rainfall-runoff modeling, which helps predict stormwater runoff, and flood forecasting for urban and rural areas. He also specializes in coastal inundation simulation to evaluate flood risks in coastal regions, integrating storm surge and topographic characteristics. Additionally, Dr. Huang works on geomorphologic analysis, studying the impact of landscape features on hydrological processes. 🌊💧🌍🏞️🌧️
Publication Top Notes
- “Distinctions of geomorphological properties caused by different flow-direction predictions from digital elevation models” – Cited by: 21, Year: 2016 🌍📊
- “An efficient method for DEM-based overland flow routing” – Cited by: 21, Year: 2013 🚶♂️🌧️
- “Evaluating the adequateness of kinematic-wave routing for flood forecasting in midstream channel reaches of Taiwan” – Cited by: 21, Year: 2012 🌊🔮
- “Influence of topographic features and stream network structure on the spatial distribution of hydrological response” – Cited by: 16, Year: 2021 🏞️📈
- “An effective alternative for predicting coastal floodplain inundation by considering rainfall, storm surge, and downstream topographic characteristics” – Cited by: 11, Year: 2022 🌧️🌊
- “Improvement of two-dimensional flow-depth prediction based on neural network models by preprocessing hydrological and geomorphological data” – Cited by: 11, Year: 2021 🤖🌐
- “Efficient DEM‐based overland flow routing using integrated recursive algorithms” – Cited by: 11, Year: 2017 🌍🔄
- “A simple depression-filling method for raster and irregular elevation datasets” – Cited by: 11, Year: 2015 🏔️🧑💻
- “Assessment of flood mitigation through riparian detention in response to a changing climate–a case study” – Cited by: 9, Year: 2018 🌎🌧️
- “An alternative for predicting real-time water levels of urban drainage systems” – Cited by: 8, Year: 2023 🌆💧
- “Analysis of hydrograph shape affected by flow-direction assumptions in rainfall-runoff models” – Cited by: 7, Year: 2020 🌧️🔍
- “Channel hydrological response function considering inflow conditions and hydraulic characteristics” – Cited by: 5, Year: 2020 🌊⚙️
- “Channel-flow response function considering the downstream tidal effect and hydraulic characteristics” – Cited by: 3, Year: 2021 🌊🔄
- “Refinement of the channel response system by considering time‐varying parameters for flood prediction” – Cited by: 3, Year: 2020 🌧️📈
- “Establishing a shallow-landslide prediction method by using machine-learning techniques based on the physics-based calculation of soil slope stability” – Cited by: 2, Year: 2023 🌍🔮
- “A novel method of estimating dynamic partial contributing area for integrating subsurface flow layer into GIUH model” – Cited by: 2, Year: 2023 🌍🧠