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.

 

Yeit Haan Teow | Chemical And Environmental | Best Researcher Award Universiti Kebangsaan Malaysia

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Assoc. Prof. Dr Yeit Haan Teow | Chemical And Environmental | Best Researcher Award

Associate Professor, University Kebangsaan Malaysia, Malaysia

Teow Yeit Haan is an Associate Professor of Chemical Engineering at the Faculty of Chemical and Process Engineering, University Kebangsaan Malaysia. With a strong academic foundation and over a decade of expertise in water and wastewater treatment, membrane separation technology, and nanotechnology applications, Dr. Teow has made significant contributions to sustainable water solutions. He has authored numerous impactful publications and continues to lead innovative research in developing advanced materials and technologies for environmental challenges.

PROFESSIONAL PROFILE

Google scholar

STRENGTHS FOR THE AWARD

Teow Yeit Haan is an outstanding researcher in the field of Chemical Engineering, specializing in water and wastewater treatment. His expertise in integrating membrane technology and nanotechnology for water treatment, as demonstrated by his research on nanofiltration membranes and novel membrane materials, positions him as a leading figure in this field. His substantial publication record, with works frequently cited in journals such as Desalination, Journal of Water Process Engineering, and Journal of Membrane Science, further attests to the impact and relevance of his contributions. He has shown great innovation in developing advanced materials such as nanocomposite membranes for water desalination and wastewater treatment.

AREAS FOR IMPROVEMENTS

While Teow’s research has advanced significantly in membrane technology and water treatment, there is potential for further interdisciplinary collaborations. Expanding his research to integrate more diverse environmental technologies and sustainability models could broaden the scope and applicability of his work. Additionally, focusing on practical, real-world implementation of his findings in collaboration with industries could increase the practical impact of his research.

EDUCATION

Dr. Teow earned his Doctorate of Philosophy in Chemical Engineering from Universiti Sains Malaysia (USM) in 2014, specializing in the integration of membrane technology and nanotechnology for water and wastewater treatment. He graduated with First-Class Honors in his Bachelor of Engineering (Chemical Engineering) from Universiti Tunku Abdul Rahman (UTAR) in 2010. His educational journey reflects his dedication to advancing the field of environmental and chemical engineering.

EXPERIENCE

Dr. Teow has over 10 years of research experience in water and wastewater treatment, reclamation, and reuse. His expertise spans membrane separation technology, adsorption processes, and sustainable water solutions. As an academic leader, he has mentored numerous students, collaborated on international projects, and contributed extensively to the scientific community with his innovative approaches to environmental challenges.

AWARDS AND HONORS

Dr. Teow has received multiple awards for his research excellence, including recognition for his contributions to membrane and nanotechnology. His work has been widely cited, underscoring its global impact. He continues to earn accolades for his advancements in chemical engineering and environmental sustainability.

RESEARCH FOCUS

Dr. Teow’s research focuses on water and wastewater treatment, membrane separation technology, adsorption processes, and the development of nanomaterials for sustainable water solutions. His groundbreaking work aims to address global water challenges through innovative technologies and environmental stewardship.

PUBLICATION TOP NOTES

  • Nanofiltration membranes review: Recent advances and future prospects 🌊📚
  • New generation nanomaterials for water desalination: A review 💧🌐
  • Preparation and characterization of PVDF/TiO2 mixed matrix membrane via in situ colloidal precipitation method 🧪🎯
  • Synthesis of cellulose hydrogel for copper (II) ions adsorption 🌿⚗️
  • Nanofiltration membrane processes for water recycling, reuse and product recovery 🚰♻️
  • A review of moving-bed biofilm reactor technology for palm oil mill effluent treatment 🏭🌏
  • Novel GO/OMWCNTs mixed-matrix membrane with enhanced antifouling property 🧑‍🔬💡
  • Development of graphene oxide/multi-walled carbon nanotubes conductive membranes 🌐💧
  • Preparation of novel polysulfone-Fe3O4/GO mixed-matrix membrane for humic acid rejection 🏗️🌿
  • Hybrid chitosan/FeCl3 coagulation–membrane processes: Performance evaluation ⚛️🌟
  • Current approaches for the exploration of antimicrobial activities of nanoparticles 🦠🔬
  • An overview of modification strategies in developing antifouling nanofiltration membranes 🛠️🚿
  • Studies on the surface properties of mixed-matrix membranes for humic acid removal 🧫🌀
  • Treatment of semiconductor-industry wastewater with ceramic and polymeric membranes ⚡💡
  • Water pathways through the ages: Integrated laundry wastewater treatment 💦📖
  • Fouling behaviors of PVDF-TiO2 mixed-matrix membranes in humic acid treatment 🌾🚰
  • Fouling assessment of tertiary palm oil mill effluent membrane treatment ♻️🌴
  • Improving membrane bioreactor performance with silver-decorated graphene oxide 🌟⚙️
  • Environmental impact of nanomaterials in composite membranes 🌍🧪
  • Investigation of anti-fouling and UV-cleaning properties of PVDF/TiO2 membranes 🌞🔬

CONCLUSION

Teow Yeit Haan is highly deserving of the Best Researcher Award due to his groundbreaking work in water and wastewater treatment, specifically in membrane separation and nanotechnology. His extensive research portfolio, innovative approach, and contributions to improving water solutions make him an exceptional candidate for this recognition. With continued focus on industry collaborations and sustainable technologies, his work will undoubtedly have lasting global impact.

Farzaneh Shayeganfar – Nanofiltration – Best Researcher Award

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Farzaneh Shayeganfar - Nanofiltration - Best Researcher Award

University of Michigan - United States

AUTHOR PROFILE

GOOGLE SCHOLAR

FARZANEH SHAYEGANFAR, Ph.D.

Farzaneh Shayeganfar is a distinguished researcher and postdoctoral fellow specializing in the fields of optoelectronic devices, nanotechnology, and computational nanoscale systems. She is currently a Postdoctoral Fellow and Visitor Scientist at Rice University, Texas, where she conducts cutting-edge research on nanopillar BN/graphene for energy storage under the supervision of Prof. Rouzbeh Shahsavari. Her work at Rice University has been supported by a research scholarship, highlighting her exceptional contributions to the field.

EDUCATION AND ACADEMIC BACKGROUND

Farzaneh completed her Ph.D. in Physics at Sharif University of Technology, focusing on Condensed Matter Theory. Her doctoral research, supervised by Prof. MohammadReza RahimiTabar and Prof. Nima Taghavinia, centered on the controlled nucleation and growth of nanoparticles through turbulent dispersion and the study of sol-gel transition by light scattering. This solid foundation in theoretical physics has propelled her into advanced research roles.

RESEARCH AND PROFESSIONAL EXPERIENCE

Before joining Rice University, Farzaneh was a Postdoctoral Fellow and Visitor Scientist at École Polytechnique de Montréal, where she worked in the Department of Engineering Physics under the guidance of Prof. Alain Rochefort. Her research there delved into the electronic properties of organic molecules and self-assembled layers on graphene and SiB, contributing significantly to the understanding of these materials' electronic behaviors.

RESEARCH INTERESTS

Farzaneh's research interests include the simulation of electronic and optoelectronic properties of nanostructures, computational nanoscale systems, and the integration of machine learning in these domains. Her innovative approach combines theoretical and computational methods to address complex challenges in nanotechnology and material science.

AWARDS AND HONORS

Farzaneh's excellence in research has been recognized through numerous awards and honors. She received the prestigious Berkeley scholarship for the BGW workshop in 2015, the best poster prize at École Polytechnique Fédérale de Lausanne, Switzerland, and a scholarship from Santa Barbara University, California, in 2014. Additionally, she was awarded a post-doctoral fellowship at École Polytechnique Montréal and received a prize for her Ph.D. thesis in nanotechnology from Iran in 2011.

SCIENTIFIC CONTRIBUTIONS AND RECOGNITIONS

Farzaneh has made significant contributions to the understanding of nanostructures and their electronic properties. Her research at Rice University and École Polytechnique de Montréal has been pivotal in advancing the field of optoelectronic devices and energy storage solutions. Her work is well-regarded in the scientific community, as evidenced by her numerous scholarships and awards.

Through her extensive research and dedication to advancing scientific knowledge, Farzaneh Shayeganfar continues to make impactful contributions to the fields of physics, nanotechnology, and optoelectronic devices. Her innovative approaches and groundbreaking research hold promise for future developments in energy storage and electronic materials.

NOTABLE PUBLICATION

A comprehensive review on planar boron nitride nanomaterials: From 2D nanosheets towards 0D quantum dots 2022 (71)

Deep learning method to accelerate discovery of hybrid polymer-graphene composites 2021 (17)

Surface/edge functionalized boron nitride quantum dots: Spectroscopic fingerprint bandgap modification by chemical functionalization 2020 (42)

Phase transition and mechanical properties cesium bismuth silver halide double perovskites (Cs 2 AgBiX 6, X= Cl, Br, I): a DFT approach 2020 (35)