Zheng Li | Environmental Science | Best Researcher Award

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Dr. Zheng Li | Environmental Science | Best Researcher Award

Dr. Zheng Li, College of environmental sciences and engineering, China

Dr. Zheng Li is a Research Associate at the School of Environmental Sciences and Engineering, Peking University. His expertise lies in environmental planning and management, with a strong research focus on water pollution control, environmental risk assessment, and pollutant migration. He has authored 10 SCI-indexed papers in leading journals such as Journal of Hydrology, Ecotoxicology and Environmental Safety. His research integrates machine learning, neural networks, and isotope tracing to advance environmental sustainability. Dr. Li’s contributions in watershed hydrology and water quality simulation have significantly impacted pollution control strategies. 🌍🔬

Publication Profile

Orcid

Education 🎓

Dr. Zheng Li earned his PhD in Environmental Science from Peking University, specializing in environmental planning, pollution control, and hydrological modeling. His doctoral research focused on heavy metal migration and transformation in sediment-water interfaces. He completed his Master’s in Environmental Engineering with an emphasis on ecological risk assessment and water quality management. His undergraduate studies in Environmental Science and Engineering provided a strong foundation in sustainable development, pollution modeling, and environmental impact assessment. Throughout his academic journey, he has combined theoretical knowledge with practical applications, producing research that influences policy and environmental conservation efforts. 📚🌱

Experience 🏢

Dr. Zheng Li has extensive research experience in environmental risk assessment, hydrological modeling, and heavy metal pollution control. As a Research Associate at Peking University, he has led studies on pollutant behavior, ecological risk assessment, and machine learning applications in water management. He has collaborated on government and industry-funded projects focusing on climate change impact on water ecosystems. His work integrates neural network models and deep learning techniques for predicting pollution trends and mitigation strategies. His experience spans laboratory research, field studies, and policy advising, contributing to sustainable environmental management practices. 🌊🔍

Research Focus 🔬

Dr. Zheng Li specializes in environmental planning, pollution control, and risk assessment. His research explores the migration and transformation of pollutants, with a particular emphasis on heavy metals and their ecological impacts. He employs machine learning, neural networks, and isotope tracing to model pollution trends and hydrological changes. His work contributes to climate change adaptation strategies, watershed management, and sustainable environmental policies. Dr. Li is committed to developing AI-driven predictive models for pollution risk assessment and mitigation planning, ensuring a cleaner and healthier environment. 🌏♻️

Publication Top Notes

  • “Nutrient Release to Qinghai Lake from Buffer Zone Evolution Driven by Climate Change” – Journal of Hydrology, June 2025.​

  • “Climate Change Driven Land Use Evolution and Soil Heavy Metal Release Effects in Lakes on the Qinghai-Tibet Plateau” – Science of The Total Environment, January 2025.​

  • “Principles of Terrestrial Water Distribution Patterns and the Role of Soil Hydraulic Properties” – CATENA, April 2024.​

  • “The Interaction Between Nutrients and Heavy Metals in Lakes and Rivers Entering Lakes” – Ecological Indicators, April 2024.​

  • “Adsorption and Desorption of Heavy Metals at Water-Sediment Interface Based on Bayesian Model” – Journal of Environmental Management, March 2023.​

  • “Spatial Distribution, Ecological Risk, and Human Health Assessment of Heavy Metals in Lake Surface Sections — A Case Study of Qinghai Lake, China” – Environmental Science and Pollution Research, January 2023.​

  • “Temporal and Spatial Distribution and Fluorescence Spectra of Dissolved Organic Matter in Plateau Lakes: A Case Study of Qinghai Lake” – Water, December 2021.​

  • “Plateau River Research: Spatial-Temporal Variations of δ18O and δD in the Water of the Yarlung Tsangpo River and Their Controlling Factors” – Ecotoxicology and Environmental Safety, January 2021.​

  • “Water Environment in the Tibetan Plateau: Heavy Metal Distribution Analysis of Surface Sediments in the Yarlung Tsangpo River Basin” – Environmental Geochemistry and Health, August 2020.​

  • “Plateau River Research: Ecological Risk Assessment of Surface Sediments in the Yarlung Tsangpo River” – Environmental Science and Pollution Research, February 2020.

Pin-Chun Huang | Environmental Science | Best Researcher Award

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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

Google Scholar

 

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 🌍🧠