Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award-3904

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Prof. Dr. Dongxing Song | Machine Learning | Best Researcher Award

Prof. Dr. Dongxing Song, Zhengzhou University, China

Prof. Dr. Dongxing Song is an innovative researcher in power engineering and thermophysics, currently serving as a Research Fellow at Zhengzhou University’s School of Mechanics and Safety Engineering. He earned his doctoral degree from Tsinghua University and previously studied at Xi’an Jiaotong University and Central South University. His expertise lies in nanofluid dynamics, ionic thermoelectric conversion, and energy system optimization. Dr. Song’s research integrates machine learning with thermodynamics, pushing boundaries in sustainable energy technologies. His work has been published in top-tier journals such as Joule and Cell Reports Physical Science, gaining recognition for both originality and technical depth. Driven by scientific rigor and curiosity, Dr. Song continues to shape future solutions for clean energy and advanced material systems. ⚛️🔬🌱

🌍 Professional Profile 

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

Prof. Dr. Dongxing Song is a standout candidate for the Best Researcher Award due to his cutting-edge work in ionic thermoelectric energy conversion and nanoscale heat transfer. His publications in high-impact journals, including Joule and Cell Reports Physical Science, demonstrate his role in shaping the future of clean and efficient energy generation. Dr. Song has independently led national-level research projects supported by the NSFC and China Postdoctoral Science Foundation, focusing on ion-electron coupling mechanisms and dynamic heat-mass transport. His interdisciplinary approach—blending thermophysics, machine learning, and materials science—makes him a trailblazer in green energy innovation. His research not only advances scientific understanding but also offers scalable solutions for low-grade waste heat recovery. 🔋🏅🌍

🎓 Education

Prof. Dr. Dongxing Song holds a robust academic background in power engineering and thermophysics. He completed his Ph.D. at Tsinghua University (2018–2022) under Prof. Weigang Ma, following his Master’s studies at Xi’an Jiaotong University (2015–2018) under Prof. Dengwei Jing. His foundational education in Thermal Energy and Power Engineering was completed at Central South University (2011–2015), where he was mentored by Dengwei Jing and Jianzhi Zhang. Throughout his academic journey, Dr. Song developed deep expertise in energy conversion, ionic transport, and thermodynamic modeling. His cross-institutional training at China’s most prestigious engineering schools laid the groundwork for his innovative and interdisciplinary research in the clean energy domain. 🎓📘⚙️

💼 Experience

Since February 2022, Dr. Dongxing Song has served as a Research Fellow at the School of Mechanics and Safety Engineering, Zhengzhou University, contributing significantly to ionic thermoelectric research. He previously pursued advanced research at Tsinghua University, one of China’s top engineering institutions, from 2018 to 2022. His earlier academic appointments include graduate research at Xi’an Jiaotong University and Central South University, where he gained hands-on experience in power engineering, energy optimization, and thermophysical modeling. In every role, Dr. Song has demonstrated scientific leadership, managing national-level projects and publishing influential research. His experience reflects a well-rounded career rooted in high-impact research and technological innovation in sustainable energy. 🧑‍🔬🔋📈

🏅 Awards and Honors

Prof. Dr. Dongxing Song has received prestigious grants and recognition from leading national institutions. He is the Principal Investigator of a National Natural Science Foundation of China (NSFC) Original Exploration Program Project, as well as multiple China Postdoctoral Science Foundation awards, including the Innovative Talents Grant (BX20220275). His work on ion thermoelectric conversion received a high recommendation from Joule Preview, marking him as a rising star in energy systems innovation. Dr. Song’s publications in top-impact journals and his ability to secure competitive funding reflect his academic excellence and research potential. These accolades highlight his position as a thought leader in the next generation of thermophysical science and energy innovation. 🥇🏛️📚

🔬 Research Focus

Dr. Dongxing Song’s research centers on the optimization of power generation systems for low-grade waste heat recovery, specifically using ion thermoelectric conversion and salt gradient power. He investigates the fundamental coupling between heat and ion transport and has derived a new expression for the ionic Seebeck coefficient, setting the stage for thermoelectric optimization. His studies also integrate nanofluidic heat transfer, solid-state ion battery transport, and machine learning to enhance the performance of sustainable energy devices. His broader focus includes nanoscale heat and mass transfer, where he explores transport mechanisms across interfaces using simulation and experimental validation. Dr. Song’s pioneering models are helping redefine energy recovery systems with enhanced efficiency and low environmental impact. 🔬♻️🧪

📊 Publication Top Notes

  • Design of Microchannel Heat Sink with Wavy Channel and Its Time-Efficient Optimization with Combined RSM and FVM Methods

    • Citations: 209

    • Year: 2016

  • Optimization of a Circular-Wavy Cavity Filled by Nanofluid under Natural Convection Heat Transfer

    • Citations: 194

    • Year: 2016

  • Optimization of a Lid-Driven T-Shaped Porous Cavity to Improve the Nanofluids Mixed Convection Heat Transfer

    • Citations: 138

    • Year: 2017

  • Prediction of Hydrodynamic and Optical Properties of TiO₂/Water Suspension Considering Particle Size Distribution

    • Citations: 87

    • Year: 2016

  • A Nitrogenous Pre-Intercalation Strategy for the Synthesis of Nitrogen-Doped Ti₃C₂Tₓ MXene with Enhanced Electrochemical Capacitance

    • Citations: 71

    • Year: 2021

 

Mr. Anthony Kyung Guzman Leguel | V2X Communication | Best Researcher Award

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Mr. Anthony Kyung Guzman Leguel | V2X Communication | Best Researcher Award

Mr. Anthony Kyung Guzman Leguel, PNU, Mexico

Anthony Kyung Guzmán Leguel, originally from Busan, Korea, is a passionate electrical engineer dedicated to advancing technology for sustainable solutions. With a stellar academic background, he earned his Bachelor’s degree from ITESO (2014-2019) and is currently a GKS Scholar pursuing a Master’s in Electrical Engineering at PNU (2021-2024). Throughout his journey, Anthony has balanced academics with extracurricular activities, including teaching high school students about electrical systems and practicing Soo Bahk Do for 25 years. He has been recognized for his contributions to the field, showcasing an impressive blend of technical expertise and commitment to community engagement.

Professional Profile

Orcid

Recommendation for Anthony Kyung Guzmán Leguel for the Best Researcher Award

Anthony Kyung Guzmán Leguel is an exceptional candidate for the Best Researcher Award due to his extensive academic achievements, innovative research contributions, and significant industry experience in electrical engineering. His current pursuit of a Master’s degree at Pusan National University (PNU) as a GKS Scholar underscores his commitment to academic excellence, evidenced by a remarkable GPA of 9.6/10 during his Bachelor’s studies at ITESO.

🎓  Education 

Anthony began his educational journey at ITESO, where he earned a Bachelor’s degree in Electrical Engineering, graduating with a commendable GPA of 9.6/10 (2014-2019). He then became a GKS Scholar, pursuing a Master’s in Electrical Engineering at PNU from 2021 to 2024. During his Master’s program, he has engaged in cutting-edge research, particularly in areas related to reinforcement learning and V2X communications. This academic path reflects his commitment to both theoretical understanding and practical application, positioning him as a forward-thinking engineer poised to contribute to renewable energy integration. Anthony’s bilingual skills in Spanish and English, along with his intermediate proficiency in Korean and French, further enhance his capacity for collaboration in diverse environments, emphasizing the global nature of modern engineering challenges.

💼  Experience 

Anthony’s professional experience includes significant roles at PNU’s Vialab, where he has worked on developing a V2X beaconing scheme using reinforcement learning. His contributions led to a notable reduction in computation time for CenterPoint 3D Object Detection, showcasing his ability to enhance technological efficiency. Before this, he interned and later became an engineer at Intel, contributing to the development of algorithms for multi-agent autonomous systems, thus significantly impacting the creation of intellectual property. His early career included a role at ITESO, where he reviewed embedded systems master thesis projects and taught high school students about electrical engineering applications. This blend of internships, academic projects, and teaching experiences has equipped Anthony with a robust skill set, allowing him to effectively navigate the challenges of modern electrical engineering and technology development.

🏅Awards and Honors 

Anthony’s dedication and achievements have garnered numerous accolades throughout his academic and extracurricular pursuits. Notably, he was inducted into the Tae Kwon Do Hall of Fame in 2013, reflecting his excellence in martial arts. As a member of the Mexican Technical Advisory Committee for Soo Bahk Do Moo Duk Kwan, he has demonstrated leadership and commitment to martial arts. His participation as a captain of ITESO University’s Tae Kwon Do team from 2017-2019 further showcases his ability to inspire and lead others. Additionally, Anthony’s work in electrical engineering has led to patents that contribute to advancements in autonomous systems and V2X communications. These accomplishments, alongside his role as a GKS Scholar, position him as a prominent figure in both sports and engineering, embodying a well-rounded individual dedicated to excellence in multiple arenas.

🌍 Research Focus 

Anthony’s research focus lies at the intersection of electrical engineering and innovative technology, particularly in the realm of renewable energy integration and autonomous systems. His current work at PNU’s Vialab involves utilizing reinforcement learning to enhance V2X communications, aiming to improve efficiency and reliability in connected vehicle networks. This work not only addresses the growing need for intelligent transportation systems but also aligns with global sustainability goals. Additionally, his research extends to 3D object detection, where he explores methods to reduce computational demands while maintaining accuracy, crucial for autonomous driving applications. By investigating decentralized trajectory planning and human-robot collaboration, Anthony aims to contribute to the development of smarter, more efficient systems that facilitate renewable energy solutions. His interdisciplinary approach, combining advanced algorithms with practical applications, positions him as a forward-thinking researcher poised to make significant impacts in the field of electrical engineering.

📖 Publication Top Notes

Enhancing the Minimum Awareness Failure Distance in V2X Communications: A Deep Reinforcement Learning Approach

Mr. Adrian Ly | Reinforcement learning | Best Researcher Award

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Mr. Adrian Ly | Reinforcement learning | Best Researcher Award

Mr. Adrian Ly, Deakin University, Australia

🌐 Mr. Adrian Ly, a distinguished alumnus of Deakin University in Australia, stands as a beacon of the transformative power of education. His academic journey at Deakin not only equipped him with knowledge and skills but also ignited a passion for lifelong learning. As a Principal Data Scientist at National Australia Bank, Adrian spearheads innovation, combating scams and enhancing customer experiences globally. Leading a dynamic team, he achieved a remarkable 32% revenue boost in unsecured lending and transaction portfolios through cutting-edge machine learning models. His tenure as a Data Science Manager at Commonwealth Bank showcased his prowess in developing impactful credit risk models and managing large-scale projects. As a Consultant at NAB, Adrian applied unsupervised learning to create personalized communication strategies, contributing significantly to revenue growth. With a background in Marketing and Sales Operations, Adrian’s diverse expertise has left an indelible mark in the realms of data science and artificial intelligence. 🚀💻

🎓 Education :

Adrian Ly, a proud alumnus of Deakin University in Australia 🎓, is a shining example of the transformative power of education. Armed with knowledge and skills acquired during his time at Deakin, Adrian has become a trailblazer in his field. 🚀 His educational journey has not only shaped his professional success but has also instilled in him a passion for lifelong learning. 📚 Adrian’s connection to Deakin is not just academic; it’s a symbol of growth, resilience, and the pursuit of excellence. 🌟 As he continues to make waves in his career, Adrian carries the spirit of his alma mater with him, a testament to the impact of quality education on shaping individuals into leaders of tomorrow. 🌏

🌐 Professional Profiles :

Google Scholar

🌐 Principal Data Scientist at National Australia Bank (May 2022 – Present) 📊

  • Spearheaded innovative functions in NAB’s web and mobile apps to combat scams, enhance customer experience, and drive retail bank growth.
  • Led a global team of 6 data scientists and engineers, fostering cross-functional collaboration across different time zones.
  • Developed machine learning models resulting in a 32% revenue boost in unsecured lending and transaction portfolios.
  • Deployed cutting-edge neural networks, improving incremental revenue across 15 models by 9%.

📈 Data Science Manager at Commonwealth Bank of Australia (June 2021 – May 2022) 🏦

  • Produced impactful credit risk models for unsecured lending, automating quality assurance and visualization processes.
  • Led development and delivery of default models using novel algorithms.
  • Managed large-scale model development and deployment projects on greenfield systems.
  • Mentored and trained junior analysts in model development and monitoring.

📊 Consultant, Data Scientist at National Australia Bank (April 2019 – June 2021) 💻

  • Applied unsupervised learning to create personalized communication strategies.
  • Delivered business lending acquisition models, driving substantial incremental revenue growth.
  • Implemented real-time and batch decisioning solutions for marketing models.
  • Rebuilt home lending machine learning models in the cloud using Pyspark and EMR.

📊 Marketing Analyst at Liberty Financial (April 2018 – March 2019) 📈

  • Developed predictive models to improve lead pipeline conversion.
  • Identified opportunities for new data streams.
  • Collaborated with stakeholders to understand problems and recommend analytical models.
  • Analyzed data to identify process bottlenecks and suggest improvements.

🔍 Graduate Marketing Analyst at Aesop (Nov 2015 – Jan 2017) 🌐

  • Conducted research to outline global strategic implications of discontinuing products.
  • Provided insights into the impact of product launches and marketing campaigns on sales.
  • Assisted in developing business cases for entry into new markets.
  • Established global marketing success metrics and facilitated the implementation of a marketing dashboard.

🚗 Graduate Sales Operations Analyst at Honda Australia (Jan 2015 – June 2015) 📈

  • Increased productivity by 150% through automation of data entry, weekly reports, and monthly reviews in sales operations and product teams.

🧠 Research Interests 🔬🌐 :

🌐 Adrian Ly, a trailblazer in the realm of artificial intelligence, is fueled by a profound passion for cutting-edge technologies. His research interests encompass the dynamic trio of reinforcement learning, machine learning, and deep learning, symbolizing a commitment to unraveling the intricacies of intelligent systems. With a mind attuned to innovation, Adrian’s journey reflects a fusion of curiosity, expertise, and a relentless pursuit of excellence in the ever-evolving landscape of AI.

Publications Top Notes  :

1.  Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks (2023)

Published in Neurocomputing, Cited by 1

2.  Elastic Step DDPG: Multi-step reinforcement learning for improved sample efficiency (2023)

Published in 2023 International Joint Conference on Neural Networks (IJCNN), Cited by 1