Olimjon Saidmamatov | Cross-disciplinary Synthesis | Emerging Research Star Award

Olimjon Saidmamatov | Cross-disciplinary Synthesis | Emerging Research Star Award

Dr Olimjon Saidmamatov, Urgench State University, Uzbekistan

Dr. Olimjon Saidmamatov appears to be a strong candidate for the Emerging Research Star Award, given his extensive work in renewable energy, the green economy, and sustainable development. His research covers vital areas such as the bio-economy, ecotourism, and the water-energy-food nexus, all of which address critical global sustainability challenges. His focus on rural development, infrastructure investment, and climate change further highlights his interdisciplinary approach to tackling regional and global issues.

Publication profile

google scholar

PhD and Education

Dr. Saidmamatov completed his PhD in Economics from Urgench State University, Uzbekistan (2020-2023). He also holds an MS in Economics (2014-2016) from the same institution and a BSc (Hons) in Accounting and Finance from the University of Bradford, UK (2009-2013).

Projects and Consulting Experience

Dr. Saidmamatov has held several key roles in high-profile projects, including as a Regional Executive for International Development Ireland and a Project Coordinator for UNESCO’s ecotourism initiatives in the Aral Sea region. He has also consulted on water projects for the Asian Development Bank and World Bank, showcasing his practical impact on sustainable development projects.

International Experience and Collaborations

His international collaborations are extensive, including visiting researcher positions at ETH Zurich and the University of Geneva, where he contributed to research on ecological systems and regional development.

Publications

Dr. Saidmamatov has co-authored several highly cited publications, including works on the water-energy-food nexus and sustainable tourism in the Aral Sea region. His work on biogas technology, renewable energy, and green economy initiatives has received recognition and contributes significantly to advancing sustainability in Central Asia.

Awards and Recognition

His achievements include the prestigious Stipendium of the President of Uzbekistan for PhD researchers (2022) and the title of Best Young Energy Specialist (2018). He was also recognized for the best master’s dissertation by the Ministry of Higher Education of Uzbekistan in 2016.

Publication top notes

Employing Ecotourism Opportunities for Sustainability in the Aral Sea Region: Prospects and Challenges

Water–energy–food nexus framework for promoting regional integration in Central Asia

The Nexus between Agriculture, Water, Energy and Environmental Degradation in Central Asia—Empirical Evidence Using Panel Data Models

Challenges and solutions for biogas production from agriculture waste in the Aral Sea Basin

Mountain Resilience: A Systematic Literature Review and Paths to the Future

Renewable energy potential of developing countries: The drivers towards a green economy (a case study from Uzbekistan)

The volatility of global energy uncertainty: Renewable alternatives

Evaluating Culturalization Strategies for Sustainable Tourism Development in Uzbekistan

TOWS analysis for sustainable ecotourism development and state support during the pandemic: The Aral Sea region of Uzbekistan

Laparoscopy in Gynecologic and Abdominal Surgery in Regional (Spinal, Peridural) Anesthesia, the Utility of the Technique during COVID-19 Pandemic

Conclusion

Dr. Saidmamatov’s diverse expertise and impactful contributions make him a fitting candidate for the Emerging Research Star Award.

Chuanxi Liu | Cross-disciplinary Synthesis | Cross-disciplinary Excellence Award

Chuanxi Liu | Cross-disciplinary Synthesis | Cross-disciplinary Excellence Award

Mr Chuanxi Liu, State Nuclear Power Information Technology Company.LTD, China

Chuanxi Liu is a prolific researcher with a strong background in astrophysics and artificial intelligence. He has co-authored pivotal papers on Gamma-Ray Burst (GRB) X-Ray flare properties and statistical studies of Swift X-Ray Flash and X-Ray Rich GRBs. Liu’s contributions to electric power technology include developing neural network algorithms for waveform data processing and using image processing techniques for fault detection. He has also innovated in wind power inspection with advancements in oil leakage detection and crack recognition. His notable achievements include a patent on traveling wave ranging and success in the Shandong Provincial AI Competition. 📡🛰️💡💻🔍

Publication profile

scopus

Education

I earned my BSc in Applied Physics from Shandong Jianzhu University, studying from September 2011 to June 2015. During my time there, I took a variety of courses including Thermodynamics, Mechanics, Optics, Electromagnetism, and Quantum Mechanics 📚. My coursework also covered Higher Mathematics, Linear Algebra, Statistics and Probability Theory, Theoretical Mechanics, Machining Drawing, and Fundamentals of Digital and Analog Circuit Technology 📐. Following this, I pursued an MSc in Astrophysics at the University of Chinese Academy of Sciences from September 2015 to June 2019. My graduate studies included courses such as Image Processing, Semiconductor Device Physics, and Astronomical Data Processing 🌌. I also gained expertise in Numerical Simulation Methods for Magnetohydrodynamics and used Linux systems and the Astronomy Software Package IDL for my research 🖥️.

Experience

From September 2015 to June 2019, I pursued a Master of Science at Yunnan Observatory, where I conducted extensive research on gamma-ray bursts. My work involved analyzing their spectra and light to validate astrophysical models. During this period, I co-authored several papers, including “GRB X-Ray Flare Properties among Different GRB Subclasses” published in the Astrophysical Journal in 2019 📚, and “Statistical Study of the Swift X-Ray Flash and X-Ray Rich Gamma-Ray Bursts” in 2018 🌟. Additionally, I contributed to the “Research Progress of GRB X-Ray Flare” in Progress in Astronomy in 2020 🌌.

Research focus

Liu, C., involved in multiple research areas, appears to have a diverse focus. In the field of object detection, Liu contributes to enhancing detection techniques through the development of the TBFF-DAC model, which leverages deformable attention and convolution for improved feature fusion 🤖. Additionally, Liu is engaged in electrical engineering, specifically in fault location methods for railway systems, utilizing non-contact measurements 🚄. In the realm of astrophysics, Liu explores the properties of gamma-ray bursts and X-ray flares, analyzing their characteristics across different subclasses 🌌. This multidisciplinary approach underscores Liu’s expertise in both technological advancements and astrophysical phenomena.

Publication top notes

TBFF-DAC: Two-branch feature fusion based on deformable attention and convolution for object detection

Research on Traveling Wave Fault Location Method of Railway Automatic Blocking/Power Continuous Line Based on Noncontact Measurement

GRB X-Ray Flare Properties among Different GRB Subclasses

Statistical Study of the Swift X-Ray Flash and X-Ray Rich Gamma-Ray Bursts