Lanfeng Li | Industrial Wastewater Treatment | Best Researcher Award

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Dr. lanfeng Li | Industrial Wastewater Treatment | Best Researcher Award

PhD student, School of Environment Studies, China University of Geosciences (Wuhan), China

Li Lanfeng, born in October 1994, is a doctoral candidate specializing in industrial wastewater treatment and resource recovery technologies. His research focuses on the degradation of dissolved organic matter, recovery of valuable components in industrial wastewater, and the resource utilization of municipal sludge. Li has been involved in significant research projects, such as the recovery and purification of hazardous waste liquids in the integrated circuit industry and the sustainable use of lithium-rich ores. He has published over 20 papers, including 16 SCI papers, and holds more than 10 patents. His work has contributed to the application of critical technologies in industries like photovoltaic and agriculture. Li’s academic background includes a PhD in Environmental Science and Engineering from China University of Geosciences (Wuhan). He has received numerous awards and honors, further solidifying his impact in the environmental engineering field.

Profile

Scopus

Education

Li Lanfeng completed his undergraduate studies in Hydrology and Water Resources Engineering at Changjiang University in 2017. He pursued a Master’s degree in Environmental Engineering at China University of Geosciences (Wuhan) from 2017 to 2020. During his master’s, Li focused on water pollution control and resource recovery. He is currently a PhD candidate in Environmental Science and Engineering at the same university, where his research primarily concentrates on industrial wastewater treatment, organic matter degradation mechanisms, and resource recovery technologies. His academic journey reflects his deep commitment to advancing environmental sustainability, with a particular focus on addressing complex industrial wastewater challenges. His education, combined with practical experience in large-scale engineering projects, has equipped him with the skills necessary to drive innovation and contribute significantly to global environmental solutions.

Experience

Li Lanfeng has gained extensive research experience through his involvement in numerous significant projects. He actively contributes to the National Key R&D Program focusing on hazardous waste liquid recovery and purification technologies in the integrated circuit industry. Additionally, he participates in the Chinese Academy of Sciences’ strategic technology initiatives, such as the resource utilization of lithium ores. His expertise extends to key areas, including the recovery of fluoride from industrial wastewater and sludge dewatering for municipal waste management. Notably, Li’s contributions to the development and application of fluoride wastewater recovery technologies have successfully been implemented in Zhejiang’s photovoltaic industry, leading to the completion of two 10,000-ton projects. He is also part of collaborative efforts to improve agricultural sustainability through low-carbon livestock farming and integrated agricultural ecosystems in the middle Yangtze River region. His contributions to both research and practical application continue to shape the future of environmental engineering.

Awards and Honors

Li Lanfeng’s academic excellence and innovation have been recognized with numerous prestigious awards. In 2023, he was awarded the Hubei Provincial Science and Technology Progress Award (Second Prize) as a key contributor to his research. He was also honored with the China Education Ministry’s National Graduate Scholarship in 2019, recognizing his outstanding achievements during his graduate studies. In addition, he received the “Outstanding Master’s Thesis” award from the China University of Geosciences (Wuhan) in 2020. Li’s dedication to his academic work is further demonstrated by his receipt of the university’s prestigious Doctoral Academic First-Class Scholarship for the 2022-2024 period. These awards highlight Li’s commitment to advancing environmental science and engineering, particularly in the areas of wastewater treatment, resource recovery, and sustainability.

Research Focus

Li Lanfeng’s research primarily focuses on industrial wastewater treatment, resource recovery, and sludge utilization. His work delves into the mechanisms of organic matter degradation during wastewater treatment processes, with an emphasis on industrial wastewater containing valuable components. One of his key areas of research is the recovery of fluoride from wastewater in industries such as photovoltaic manufacturing, where he has successfully developed and applied resource recovery technologies. Li is also dedicated to the utilization of municipal sludge, focusing on its dewatering, conditioning, and conversion into valuable by-products. His research extends to sustainable agricultural development, particularly in low-carbon farming practices in the middle Yangtze River region. Through his multidisciplinary approach, Li seeks to advance environmental sustainability while developing practical solutions to the pressing challenges of industrial pollution and resource management.

Publication Top Notes

  1. Lanfeng Li, Niannian Sun, Siwei Peng, et al. (2024). Molecular insights into the degradation of organic matter from secondary swine wastewater effluent: A comparative study of advanced oxidation processes. Chemical Engineering Journal, 500: 156761.
  2. Lanfeng Li, Jing Ai, Hang He, et al. (2024). Molecular-level insights into the transformation and degradation pathways of dissolved organic matter during full-scale swine wastewater treatment. Science of the Total Environment, 909, 168604.
  3. Lanfeng Li, Jing Ai, Weijun Zhang, et al. (2020). Relationship between the physicochemical properties of sludge-based carbons and the adsorption capacity of dissolved organic matter in advanced wastewater treatment: effects of chemical conditioning. Chemosphere, 243, 125333.
  4. Lanfeng Li, XingminFu, Jing Ai, et al. (2019). Process parameters study and organic evolution of old landfill leachate treatment using photo-Fenton-like systems: Cu2+ vs Fe2+ as catalysts. Separation and Purification Technology, 211, 972-982.
  5. Peng Su, Lanfeng Li*, Hao Zhou, et al. (2024). Environmental and economic sustainability of the novel photovoltaic industrial wastewater treatment systems from life cycle perspective. Environmental Research, in revision.

 

 

 

Zizun Wei | Water and Wastewater Treatment | Best Researcher Award

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Mr. Zizun Wei | Water and Wastewater Treatment | Best Researcher Award

College of Computer Science and Software Engineering, Hohai University, China

Zizun Wei is a Master’s student at the College of Computer Science and Software Engineering, Hohai University, Nanjing, China. At 24 years old, he is highly passionate about the intersection of artificial intelligence, computer vision, and water resources. Zizun has demonstrated a strong academic foundation, having completed his Bachelor’s degree in Network Engineering at Heilongjiang University, Harbin. His research interests include object detection, few-shot learning, and applying AI technologies to real-world challenges, particularly in environmental monitoring. Zizun has contributed significantly to scientific literature, with multiple published papers in respected journals and conferences. Additionally, his innovative work in the field has led to a patent in semantic segmentation for water body extraction. His work is at the forefront of AI’s application to environmental science, particularly focusing on river debris detection and crack segmentation in earth dams. Zizun’s drive to combine AI with practical solutions positions him as a promising researcher in his field.

Profile

Google Scholar

Education

Zizun Wei is currently pursuing a Master’s degree in Computer Science and Technology at Hohai University, Nanjing, from September 2022 to June 2025. His academic journey began with a Bachelor’s degree in Network Engineering from Heilongjiang University, Harbin, where he studied from September 2018 to June 2022. During his Bachelor’s, Zizun laid the groundwork for his research interests in artificial intelligence, network systems, and computer vision. At Hohai University, he is expanding his knowledge in computer science, with a focus on object detection, machine learning, and their application to environmental challenges, such as water resource management. Zizun has excelled in both practical and theoretical aspects of his education, participating in multiple research projects while refining his skills in data analysis and AI modeling. His academic path reflects a dedication to advancing technology in ways that contribute to society, particularly in the areas of environmental protection and resource management.

Experience

Zizun Wei has gained diverse research experience throughout his academic career, starting with his involvement in salient object detection during his Bachelor’s degree, where he worked on feature fusion and pixel loss weighting methods. His Master’s research has broadened to focus on few-shot object detection and river floating debris detection. He proposed a meta-feature extraction approach for few-shot object detection and worked on enhancing algorithms using generative fitting for real-world data. Zizun is also exploring text knowledge embedding techniques to enhance the performance of object detection models. His work on river floating debris detection aimed at improving feature enhancement methods, with a view to addressing environmental challenges in water bodies. Additionally, Zizun co-authored papers in top-tier journals and conferences, as well as a patent on semantic segmentation methods for water body extraction. His research not only advances the field of computer vision but also addresses practical environmental concerns, reflecting his interdisciplinary approach.

Research Focus

Zizun Wei’s research primarily revolves around computer vision and artificial intelligence, with a particular focus on object detection and few-shot learning. His work in object detection has been aimed at improving algorithms for complex, real-world applications such as detecting debris in rivers and cracks in earth dams. He is developing few-shot learning techniques that mimic human cognition and leverage transfer learning for more efficient detection in environments with limited labeled data. Zizun’s innovations include the use of meta-feature extraction and generative fitting methods to enhance detection performance, particularly in the context of environmental and water resources. He is also exploring the integration of text knowledge embeddings to further advance the performance of detection models. With an overarching goal of contributing to sustainable water resource management, his work combines cutting-edge AI techniques with real-world applications that can make significant environmental impacts.

Publication Top Notes

  1. L. Zhang, Z. Wei, Y. Shao, Z. Chen, Z. Luo, and Y. Dou, “A context feature enhancement and adaptive weighted fusion network for river floating debris detection,” Engineering Applications of Artificial Intelligence, Mar. 2025.
  2. L. Zhang, Z. Wei, and P. Jin, “DAMFE-Net: A Few-shot Crack Segmentation Model Based on Transfer Learning for Earth Dams,” IEEE 15th International Conference on Software Engineering and Service Science (ICSESS), 2024.
  3. Z. Wei and G. Zhu, “A Salient Object Detection Method Combining Multi-Scale Feature Fusion and Pixel Loss Weighting,” Journal of Natural Science of Heilongjiang University, 2022.
  4. G. Zhu, Z. Wei, and F. Lin, “An Object Detection Method Combining Multi-Level Feature Fusion and Region Channel Attention,” IEEE Access, 2021.
  5. Patent: “A Lightweight Dual-Prediction Branch Semantic Segmentation Deep Learning Method and System for Water Body Extraction.” CN117911701A. Co-inventors: Zhang Lili, Wei Zizun, Lu Yushi, Wang Huibin, Chen Jun, Chen Zhe. Publication Date: April 19, 2024.