Mr Zhidong CAO | Artificial Intelligence Award | Best Researcher Award

Mr Zhidong CAO, Institute of Automation, Chinese Academy of Sciences, China

Zhidong Cao 🎓 is a prominent Professor and Principal Investigator at the National Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. He holds a Doctor of Science degree from the Institute of Geographic Sciences and Natural Resources Research, CAS. With over a decade of experience at CAS, Cao has contributed significantly to AI and automation research, leading over 20 national-level projects. His scholarly impact includes 120+ papers in prestigious journals and international conferences, along with authoring 3 books. Cao has been honored with multiple awards, highlighting his substantial contributions to Chinese scientific advancement.

Publication profile

Scopus

Education

Zhidong Cao 📚 pursued a rigorous academic journey that culminated in a Ph.D. from the Institute of Geographic Sciences and Natural Resources Research at the Chinese Academy of Sciences, completed from September 2005 to July 2008. Prior to his doctoral studies, he earned a Master’s degree from Changsha University of Science and Technology, spanning from September 2002 to July 2005. Cao’s educational foundation began with a Bachelor’s degree, also from Changsha University of Science and Technology, covering the period from September 1997 to July 2001. These academic milestones provided him with a comprehensive background for his subsequent influential research career in artificial intelligence and automation.

Experience

Zhidong Cao 🌐 has amassed a rich and diverse professional journey at the Institute of Automation, Chinese Academy of Sciences. Beginning as a Postdoctoral Fellow from July 2008 to April 2010, he transitioned to an Assistant Researcher role from May 2010 to October 2011. His expertise and dedication led to his appointment as an Associate Researcher from November 2011 to October 2020. Currently serving as a Researcher since November 2020, Cao continues to excel in advancing artificial intelligence and automation technologies. His progressive roles reflect a steadfast commitment to pioneering research and development in his field, shaping cutting-edge advancements in technology and scientific innovation.

Awards and Honors

Zhidong Cao 🏆 has garnered significant recognition throughout his career, exemplified by numerous prestigious awards. Notably, he received the Second Prize in the Beijing Science and Technology Progress Award at the Provincial Level in 2022, underscoring his contributions to technological advancement. His achievements include the Grand Prize from the China Surveying and Mapping Society in 2021, highlighting his impact at the Ministry Level. Cao’s accolades also extend to the Chinese Society of Simulation Natural Science First Prize in 2018 and the Chinese Association of Automation Science and Technology Award in 2013, showcasing his leadership in national-level scientific endeavors. Additionally, he has been honored with several provincial and national awards, reflecting his outstanding contributions across diverse domains of research and innovation.

Research Achievements

Zhidong Cao 🌐 has made profound contributions to scientific research, spanning multiple disciplines and domains. He has played a pivotal role in over 20 national-level projects and research initiatives, showcasing his leadership and expertise in advancing technology and innovation. Cao has been integral to major national scientific and technological projects, including those under the National Natural Science Foundation of China and the strategic plans for AI development. His scholarly impact extends to over 120 published papers in esteemed domestic and international journals and conferences. Additionally, Cao has authored 3 influential books and has been honored with 6 prestigious scientific and technological awards, solidifying his reputation as a trailblazer in the field.

Research Focus

Zhidong Cao 🧬 focuses his research on the intersection of artificial intelligence (AI) and public health, particularly in predicting and mitigating the impact of infectious diseases. His work spans various domains such as computational epidemiology, social computing for energy safety, and evolutionary economic-epidemiological modeling related to COVID-19. Cao’s contributions include developing AI-driven models and frameworks to optimize non-pharmaceutical interventions during pandemics and managing the water-energy-carbon nexus in urban environments. Through over 120 research papers and collaborations on national and international platforms, he continues to advance the application of AI in tackling complex societal challenges, emphasizing proactive approaches to health and environmental resilience.

Publication Top Notes

Supply chain loss from easing COVID-19 restrictions 📉 Ye, Y., Cao, Z., Zeng, D.D., Zhang, Q. Proceedings of the Royal Society A, 2024, 1 citation.

Energy-Social Manufacturing for Social Computing 🔋 Zhao, A.P., Li, S., Wang, Y., Cao, Z., et al. IEEE Transactions on Computational Social Systems, 2024, 0 citations.

Cross-lingual transfer learning for COVID-19-related hate speech detection 📝 Liu, L., Xu, D., Zhao, P., Cao, Z., et al. Expert Systems with Applications, 2023, 4 citations.

Managing Water-Energy-Carbon Nexus for Urban Areas 🌍 Zhao, P., Li, S., Hu, P.J.-H., Cao, Z., Xiang, Y. IEEE Transactions on Power Systems, 2023, 4 citations.

Two-Stage Co-Optimization for Utility-Social Systems 🔄 Zhao, P., Li, S., Hu, P.J.-H., Cao, Z., et al. IEEE Transactions on Computational Social Systems, 2023, 3 citations.

Blockchain-Based Water-Energy Transactive Management 🌐 Zhao, P., Li, S., Hu, P.J.-H., Cao, Z., Xie, D., Xiang, Y. IEEE Transactions on Smart Grid, 2023, 1 citation.

Deep Learning Approach for Semantic Analysis of COVID-19-Related Stigma on Social Media 📊 Liu, L., Cao, Z., Zhao, P., et al. IEEE Transactions on Computational Social Systems, 2023, 4 citations.

Dr. Fangxin Fang | Machine learning | Best Researcher Award

Dr. Fangxin Fang, Imperial College London, United Kingdom

Dr. Fangxin Fang 🌐 is a pioneering researcher in numerical simulations of nonlinear fluid flows 🌊. With a PhD from James Cook University 🎓, Australia, and extensive experience at Imperial College London 🏛️, he integrates advanced techniques like Machine Learning and Data Assimilation for accurate predictions. Dr. Fang’s innovative work has led to software development 🖥️, numerous publications 📚, and successful grant applications totaling over £10M 💰. A leader in project management and collaboration, he fosters interdisciplinary research 🤝. His contributions extend to teaching 🎓, mentoring, and impactful engagement with industry and academia worldwide 🌍.

Publication Profile:

Scopus

Google scholar

Education:

🎓 Dr. Fangxin Fang’s educational journey reflects a commitment to academic excellence across diverse continents. Beginning with a Bachelor’s in Engineering from Hehai University, China, they laid the groundwork for their scholarly pursuits. This was followed by a Master of Science degree from the North China Institute of Water Conservancy and Hydropower, China, where they deepened their expertise in a specialized field. Undeterred by geographical boundaries, they pursued doctoral studies at James Cook University, Australia, earning a PhD. Each academic milestone represents their dedication to learning and growth, culminating in a comprehensive understanding of their field. 🌐

Employment:

🌟 Dr. Fangxin Fang’s professional journey spans continents, showcasing their invaluable contributions to the global scientific community. They commenced as an Engineering Assistant at the China Institute of Water Resources and Hydropower Research, Beijing, China, before transitioning to academia as a Lecturer at the North China Institute of Water Conservancy and Hydropower, Beijing. Following their passion, they pursued doctoral studies at James Cook University, Australia, setting the stage for a distinguished career. Over the years, they’ve held pivotal roles, from Research Assistant at the University of Auckland, New Zealand, to Postdoctoral Researcher in Toulouse, France. Currently, they serve as a Senior Research Fellow at Imperial College, London, UK, solidifying their legacy in Earth Science and Engineering. 🌍

Research Focus:

Dr. Fangxin Fang’s 🌊 research focus lies at the intersection of computational fluid dynamics and advanced data-driven methods. With a keen emphasis on numerical simulations, his work delves into understanding complex fluid dynamics in various domains such as oceanography, atmospheric science, and urban environments. Utilizing techniques like reduced order modeling, machine learning, and deep convolutional networks, Dr. Fang explores nonlinear spatio-temporal fluid flows. His contributions pave the way for enhanced predictions of phenomena like ocean currents, air pollution dispersion, and flood dynamics. Dr. Fang’s innovative research transcends traditional boundaries, offering insights crucial for environmental sustainability and disaster management 🌍.