Dr. Sue Han Lee - Computational Botany - Women Researcher Award

Swinburne University of Technology Sarawak Campus - Malaysia

Author Profile

Early academic pursuits 🎓

Lee Sue Han's academic journey began with a Bachelor of Engineering (Honours) in Electronics Engineering from Multimedia University, Malaysia. Her passion for technology and innovation propelled her to pursue a Master of Engineering in Electrical and Electronics at Shinshu University, Japan. Under the guidance of Professor Kiyoshi Tanaka, she focused on computer vision and machine learning, laying a solid foundation for her future research. Her quest for knowledge culminated in a Doctor of Philosophy in Computer Science & IT at University Malaya, where she further specialized in computer vision and deep learning under the mentorship of Professor Ir. Dr. Chan Chee Seng.

Professional endeavors 🏢

Since February 2020, Lee has served as a Lecturer at Swinburne University of Technology, Sarawak Campus, where she has taken on significant responsibilities, including Head of the Department of Information and Communication Technologies. Her role as an Interdisciplinary AI Research Driver emphasizes her commitment to advancing AI applications across various fields. Prior to this, she gained valuable experience as a Postdoctoral Fellow at INRAE in Montpellier, France, specializing in computational botany, which showcases her diverse expertise and adaptability in research.

Contributions and research focus 🔍

Lee's research is primarily centered on computer vision and deep learning, with a strong emphasis on machine learning applications. She has made significant strides in developing algorithms and techniques that enhance the understanding and analysis of visual data. Her contributions to computational botany highlight the Computational Botany intersection of technology and environmental science, where she explores innovative solutions for plant research through advanced computational methods. Her interdisciplinary approach not only enriches her field but also opens new avenues for research and application.

Accolades and recognition 🏅

Lee Sue Han's contributions to the field have been recognized through her active involvement in professional organizations. As a member of IEEE Young Professionals since 2019, she has engaged with a global community of engineers and technologists. Recently, she was designated a Graduate Technologist by the Malaysian Board Computational Botany of Technologists (MBOT) in 2023, acknowledging her expertise and commitment to the engineering profession. Her achievements reflect her dedication to excellence and her impactful role in the academic and professional landscape.

Impact and influence 🌍

Lee's work significantly influences the fields of computer vision, machine learning, and computational botany. Her research not only advances theoretical knowledge but also has practical implications for various industries, including agriculture and environmental science. By bridging the gap between technology and real-world Computational Botany applications, she contributes to solving pressing global challenges. Her mentorship and leadership at Swinburne University inspire the next generation of engineers and researchers to explore innovative solutions.

Legacy and future contributions 🔮

As Lee Sue Han continues her academic and research endeavors, her legacy is defined by her commitment to interdisciplinary collaboration and technological advancement. Her future contributions are expected to push the boundaries of knowledge in computer vision and AI, particularly in addressing environmental issues and enhancing agricultural practices. Lee's vision for the future is one where technology plays a pivotal role in creating sustainable solutions, and her ongoing work promises to have a lasting impact on both academia and industry.

Notable Publications

How deep learning extracts and learns leaf features for plant classification 2017

Deep-plant: Plant identification with convolutional neural networks 2015

New perspectives on plant disease characterization based on deep learning 2020

Multi-organ plant classification based on convolutional and recurrent neural networks 2018

Attention-based recurrent neural network for plant disease classification 2020

Early Academic Pursuits

Dr. Muhammad Tayyab's academic journey is marked by his extensive focus on agricultural sciences. He completed his Bachelor's degree in Agriculture from Gomal University in Pakistan in 2014, specializing in agronomy. He further pursued his passion for agricultural sciences at Fujian Agriculture and Forestry University (FAFU) in China, where he earned both his Master of Philosophy and Doctor of Philosophy degrees. His master's thesis explored the influence of sugarcane straw and goat manure on soil nutrient transformation and bacterial communities. For his Ph.D., he delved into how different cultivars and organic fertilization practices improve sugarcane rhizosphere soil properties and microbiomes in a monoculture system.

Professional Endeavors

Dr. Tayyab has amassed a wealth of experience in both academic and practical fields. Currently, he is a postdoctoral fellow at Shantou University in China, where he conducts comprehensive research on shrimp microbiomes and genome-wide analysis of the hsp90 gene family. His role also involves mentoring master's and Ph.D. students, contributing to multiple publications, and securing significant research funding.

Contributions and Research Focus

Dr. Tayyab's research interests are centered on soil microbial communities and their role in carbon sequestration, nutrient cycling, and soil structure development. He is particularly focused on the effects of conventional versus conservation agriculture methods on microbial Crop Cultivation and Farming Systems communities and their ecological services, such as till/no-till practices, cover cropping, and the use of composts and manures.

Impact and Influence

Dr. Tayyab's research has significantly contributed to the understanding of soil microbial dynamics and their interaction with agricultural Crop Cultivation and Farming Systems practices. His work has implications for improving soil health, enhancing crop yields, and promoting sustainable agricultural practices. His mentorship of students and collaboration with peers further amplify his influence in the field.

Legacy and Future Contributions

Dr. Tayyab is poised to continue making substantial contributions to agricultural sciences and soil microbiology. His future research aims to further explore microbial ecology in agricultural systems, focusing on sustainable practices that enhance soil health and productivity. His expertise in microbiome analysis and integration with soil-plant systems positions him to lead innovative research that addresses critical challenges in agriculture.