Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

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Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

lecturer, Siran university of science and technology, Iran

Seyed Abolfazl Aghili is a civil engineer and researcher with expertise in construction engineering and management. He holds a Ph.D. in Civil Engineering from Iran University of Science and Technology (IUST). His research focuses on machine learning, resiliency, and building information modeling (BIM). Dr. Aghili has published several papers in reputable journals and has presented his work at international conferences. He is fluent in Persian and English and has skills in various software, including Python, MS Project, and Autodesk AutoCAD.

Profile

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Education 🎓

Ph.D. in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2019-2024 (link unavailable) in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2013-2015 (link unavailable) in Civil Engineering, Isfahan University of Technology (IUT), 2009-2013

Experience 💼 

Researcher, Iran University of Science and Technology (IUST), 2019-2024  Graduate Research Assistant, Iran University of Science and Technology (IUST), 2013-2015  Undergraduate Research Assistant, Isfahan University of Technology (IUT), 2009-2013

Awards and Honors🏆

Ranked 5th among 2200 participants in Nationwide University Entrance Exam for Ph.D. program in Iran, 2019 Ranked 2nd among all construction management students in Iran University Science and Technology, 2013-2015 Ranked 220th among 32,663 participants (Top 1%) in Nationwide University Entrance Exam for (link unavailable) program in Iran, 2013

Research Focus

Machine learning and deep learning methods  Resiliency  Building Information Modeling (BIM)  Human Resource Management (HRM)  Decision Making Systems for Project Managers

Publications 📚

1. Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review 🤖
2. Data-driven approach to fault detection for hospital HVAC system 📊
3. Feasibility Study of Using BIM in Construction Site Decision Making in Iran 🏗️
4. Review of digital imaging technology in safety management in the construction industry 📸
5. The role of insurance companies in managing the crisis after earthquake 🌪️
6. The need for a new approach to pre-crisis and post-crisis management of earthquake 🌊

Conclusion

Seyed Abolfazl Aghili is an exceptional researcher with a strong academic background, interdisciplinary research experience, and a notable publication record. His teaching and mentoring experience, as well as his technical skills, demonstrate his commitment to education and research. While there are areas for improvement, Dr. Aghili’s strengths make him a strong candidate for the Best Researcher Award.

Zicheng Xin | intelligentialization | Best Researcher Award

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Dr. Zicheng Xin | intelligentialization | Best Researcher Award

postdoctor, University of Science and Technology Beijing, China

Zicheng Xin is a renowned researcher and visiting professor at the Korea Invention Academy. He is affiliated with the University of Science and Technology Beijing (USTB) and has made significant contributions to the field of metallurgical engineering. His research focuses on metallurgical process engineering, intelligence, and simulation.

Profile

scopus

Education 🎓

Ph.D. in Metallurgical Engineering, State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing (USTB) (2018-2022)

Experience 🧪

Visiting Professor, Korea Invention Academy (current)  Researcher, State Key Laboratory of Advanced Metallurgy, USTB (current)

Awards & Honors🏆

“Multiscale modeling and collaborative manufacturing for steelmaking plants”, the 10th World Scientist Grand Award — Golden Scientist Grand Award (Second Place, International Federation of Inventors’ Associations, 2023) “Multiscale modeling and collaborative manufacturing for steelmaking plants”, the 10th World Scientist Grand Award— Science & Technology Grand

Research Focus 🔍

Metallurgical process engineering and intelligence  Simulation and optimization of metallurgical process

Publications📚

1. Analysis of multi-zone reaction mechanisms in BOF steelmaking and comprehensive simulation [J]. Materials, 2025, 18(5): 1038. – Zicheng Xin, Qing Liu, Jiangshan Zhang, et al.
2. Modeling of LF refining process: a review [J]. Journal of Iron and Steel Research International, 2024, 31(2): 289-317. – Zicheng Xin, Jiangshan Zhang, Kaixiang Peng, et al.
3. Explainable machine learning model for predicting molten steel temperature in LF refining process [J]. International Journal of Minerals, Metallurgy and Materials, 2024, 31(12): 2657-2669. – Zicheng Xin, Jiangshan Zhang, Kaixiang Peng, et al.
4. Predicting temperature of molten steel in LF refining process using IF-ZCA-DNN model [J]. Metallurgical and Materials Transactions B, 2023, 54(3): 1181-1194. – Zicheng Xin, Jiangshan Zhang, Junguo Zhang, et al.
5. Predicting the alloying element yield in a ladle furnace using principal component analysis [J]. … – Zicheng Xin, Jiangshan Zhang, Yu Jin, et al.

Conclusion

Zicheng Xin’s academic excellence, research focus, and international recognition make him a strong candidate for the Best Researcher Award. While there are areas for improvement, his strengths and achievements demonstrate his potential to make significant contributions to the field of metallurgy.

Nahid Entezarian | Machine Interaction | Best Researcher Award

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Ms. Nahid Entezarian | Machine Interaction | Best Researcher Award

Author, University of Mashhad, Mashhad, Iran

Nahid Entezarian is a Ph.D. candidate in Information Technology Management at Ferdowsi University of Mashhad. Her research interests include text mining, data mining, NeuroIS, artificial intelligence, machine learning, and research methodology in information systems.

Profile

scholar

Education 🎓

Nahid Entezarian is currently pursuing her Ph.D. in Information Technology Management at Ferdowsi University of Mashhad, specializing in Smart Business. Her academic background has provided a solid foundation for her research and professional endeavors.

Experience 🧪

Unfortunately, the provided text does not mention specific work experience or professional roles held by Nahid Entezarian.

Awards & Honors �

Unfortunately, the provided text does not mention specific awards or honors received by Nahid Entezarian.

Research Focus 🔍

1. Text Mining: Investigating the application of text mining techniques in various domains.
2. Data Mining: Exploring the use of data mining methods for knowledge discovery.
3. NeuroIS: Examining the intersection of neuroscience and information systems.
4. Artificial Intelligence: Investigating the application of AI in various domains.
5. Machine Learning: Developing and applying machine learning algorithms for data analysis.

Publications📚

1. An investigation extent and factors influencing the users’ perception of database interface based on Nielsen model 📊
2. GUIDELINES FOR USER INTERFACE DESIGN BASED ON USERS’BEHAVIORS, EXPECTATIONS AND PERCEPTIONS 📈
3. Topic Modeling on System Thinking Themes Using Latent Dirichlet Allocation, Non-Negative Matrix Factorization and BER Topic 🤖
4. NeuroIS: A Systematic Review of NeuroIS Through Bibliometric Analysis 🧠
5. The Application of Artificial Intelligence in Smart Cities: A Systematic Review with Methodi Ordinatio 🌆
6. Systems Thinking in the Circular Economy: An Integrative Literature Review ♻️
7. The impact of knowledge management and Industry 4.0 technologies in organizations: a meta-synthesis approach 📈
8. Topic Modeling Emerging Trends for Business Intelligence in Marketing: With Text Mining and Latent Dirichlet Allocation 📊
9. Topic Modeling Emerging Trends for Business Intelligence in Marketing: With Text Mining and Latent Dirichlet Allocation 📊
10. Introducing and Evaluation of Rogers’s Diffusion Innovation Theory 📈

Conclusion 🏆

Nahid Entezarian’s impressive academic and research experience, research output, interdisciplinary research approach, and collaborations make her an outstanding candidate for the Best Researcher Award. While there are areas for improvement, her strengths and achievements demonstrate her potential to make a significant impact in her field.

Zhangcun Yan | automatic vehicle system | Best Researcher Award

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Dr. Zhangcun Yan | automatic vehicle system | Best Researcher Award

Research fellow,Tongji University, China

Zhangcun Yan is a Research Assistant at Tongji University, specializing in intelligent transportation systems. He earned his Ph.D. in Transportation from Tongji University (2024), an M.Sc. in Transportation Engineering from Southwest Jiaotong University (2018), and a B.Sc. in Transportation from Ningbo University of Technology (2015). As a visiting scholar at the University of Montreal (2023–2024), he expanded his expertise in AI-driven traffic safety solutions. His research focuses on applying computer vision and artificial intelligence to enhance urban mobility, traffic safety, and autonomous systems. Zhangcun has developed novel trajectory reconstruction methods, real-time road friction detection models, and risk assessment frameworks for mixed-traffic environments. His work has been published in top-tier journals such as Expert Systems with Applications and Traffic Injury Prevention. With a citation index of 44, he continues to push the boundaries of intelligent transportation, making significant contributions to reducing accidents and improving urban traffic management.

Profile.

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🎓 Education 

Throughout his academic journey, Zhangcun has been dedicated to integrating artificial intelligence with transportation engineering to enhance road safety and efficiency. His doctoral research led to the development of an innovative NONM trajectory reconstruction method, significantly improving vehicle movement analysis in complex traffic environments. His studies also focused on real-time detection of road surface friction coefficients, a crucial factor in preventing weather-related traffic accidents. Zhangcun’s multidisciplinary education bridges the gap between traditional traffic engineering and cutting-edge AI applications.

💼 Experience

Zhangcun Yan has extensive experience in transportation research, focusing on AI applications in intelligent mobility and road safety. At Tongji University, he spearheaded multiple projects, including real-time road friction detection and automated trajectory reconstruction for urban intersections. During his tenure as a visiting scholar in Canada, he collaborated with global experts to enhance traffic risk modeling. His expertise in integrating deep learning with computer vision has led to groundbreaking solutions for vehicle tracking and collision prediction. Zhangcun’s experience spans interdisciplinary research, algorithm development, and data-driven transportation analytics, contributing to next-generation urban mobility solutions.

🏆 Awards and Honors

Zhangcun Yan has received multiple accolades for his pioneering work in AI-driven transportation research. His paper on NONM trajectory reconstruction was recognized as the Best Research Paper at an international conference, reflecting his innovative approach to solving urban mobility challenges. He was also honored for his contributions to intelligent transportation solutions at Tongji University. His ability to bridge AI with real-world traffic safety applications has earned him recognition as one of China’s top emerging transportation researchers. These awards highlight his dedication to making roads safer and more efficient through AI-powered solutions.

🔬 Research Focus 

🚗 Trajectory Reconstruction & Analysis – Developed a high-precision NONM method to enhance vehicle trajectory accuracy using social force models and particle filtering.

 Road Surface Friction Detection – Created a real-time RSFC detection system using CNN-based vision models, improving road safety in adverse weather.

⚠️ Driving Risk Assessment – Designed an AI-based risk prediction framework for mixed-traffic environments, aiding in proactive accident prevention.

📹 Computer Vision for Traffic Monitoring – Implemented YOLOv7 and DeepSort algorithms for automated vehicle tracking and intersection analysis.

His interdisciplinary work integrates AI, deep learning, and transportation engineering, leading to more efficient urban traffic management and reduced road accidents. Zhangcun’s research continues to drive innovations in autonomous driving, intelligent traffic systems, and urban mobility safety.

Publications

🏎️ “Trajectory Reconstruction Using NONM and Social Force Models” – Expert Systems with Applications

🚦 “AI-Driven Road Surface Friction Estimation in Adverse Weather” – Alexandria Engineering Journal

🚘 “Collision Risk Prediction at Urban Intersections” – Traffic Injury Prevention

🚲 “Analyzing Mixed-Traffic Interactions Using Deep Learning” – Journal of Transportation Engineering

Conclusion

Zhangcun Yan is a strong contender for the Best Researcher Award in mechanics and transportation engineering. His work in computer vision, AI-driven risk modeling, and autonomous safety systems makes a significant contribution to the field. However, improving industry collaborations, patent filings, and professional memberships would further establish his standing as a leading researcher in intelligent transportation systems. If he continues expanding his research outreach and practical applications, he will be an even more influential figure in the domain.

 

 

Manar Hamza | Computer Science Data mining | Best Researcher Award

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Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor at  Prince Sattam bin Abd El Aziz University, China

👩‍🏫 Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. 💻 Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education 🎓

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). 🎓 Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). 🎓 B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). 📚 Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience 🖥️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). 👩‍💼 Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). 🇸🇩 Lecturer at Omdurman Islamic University, Sudan (2005–2012). 👩‍🔬 E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors 🏆

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. 🙌 Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. 📜 Active contributor to enhancing the learning environment with innovative solutions.

Research Focus 🔍

Data mining, text mining, and information security are core research areas. 📊 Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. 🛡️ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Zhiyi Liu | Embodied Intelligence | Best Researcher Award

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Dr. Zhiyi Liu | Embodied Intelligence | Best Researcher Award

Chief Scientist at Eastmoney AI Research Institute, China

The individual is a distinguished AI scientist with a vast background in multimodal AI, data integration, and financial technology. 📊 They have contributed significantly to AI applications across various industries, including search engines, digital healthcare, and financial markets. 🌐 Holding senior positions at prominent companies such as Baidu, SenseTime, and East Money Group, they have driven innovation in AI algorithms and system architecture. 💻 Their leadership in AI governance and multimodal model development has solidified their role as a key player in the AI landscape. 🤖 Additionally, their collaboration with academic and industry leaders, including Professor Andrew Ng, has furthered the integration of cutting-edge AI into real-world applications.

Publication Profile

scholar

Education 🎓

They are pursuing an IMBA at the University of Hong Kong Business School (2024-2026).  They completed their Doctorate in Intelligent Manufacturing at ISTEC Paris (2021-2024).  Their undergraduate education is in Computer Science and Technology from Beijing University of Posts and Telecommunications (2007-2011).  Throughout their academic career, they have focused on merging technical expertise with strategic innovation, especially in fields related to AI, intelligent manufacturing, and business. Their education has laid a solid foundation for their work, combining both advanced technical skills and a keen understanding of the business implications of AI technologies.

Experience 🔧

Currently, they are the Principal Scientist & Executive Dean at East Money Group, leading intelligent financial risk assessment models.  Prior to this, they co-founded and served as an AI scientist at SenseTime (2019-2022), where they led multimodal data fusion projects.  At Baidu (2011-2018), they spearheaded the integration of AI into search technologies and collaborated with top AI experts, including Andrew Ng. 🤝 They have also contributed to the development of multimodal AI models at the Chinese Academy of Sciences (2018-2019). Their diverse experience encompasses AI applications in finance, healthcare, and autonomous systems.

Awards and Honors 🏆 

At the international level, they are a member of the technical committee for the IEEE CCAI 2024 conference and a technical expert for the IEC/SMB/SEG12 Bio-digital Convergence System Evaluation Team.  Nationally, they are a member of the AI Ethics Working Committee of the Chinese Association for Artificial Intelligence and an expert on Chinese AI standards. 🇨🇳 They are a distinguished fellow at Shanghai Jiaotong University’s AI and Marketing Research Center and serve as the Executive Director of the Research Center for Computational Law and AI Ethics. 🏅 Their accolades reflect their contributions to AI ethics, governance, and research.

Research Focus  🔬

Their research centers on multimodal AI, integrating data streams from text, images, speech, and video to enhance AI’s cognitive abilities. 🧠 They have made significant advancements in natural language processing (NLP), computer vision, and deep learning.  Their work also addresses AI governance, ensuring transparency, fairness, and compliance in AI systems.  They focus on practical applications in digital healthcare, where multimodal data fusion has improved diagnostic accuracy and patient care.  Additionally, they have applied AI innovations to financial markets, optimizing decision-making through advanced algorithms and risk assessment models.

Conclusion

This candidate demonstrates exceptional qualifications for the Best Researcher Award, thanks to their pioneering work in embodied intelligence, multimodal AI models, and cross-sector applications. Their leadership in AI innovation, coupled with their significant academic influence and contributions to AI ethics, makes them a standout nominee. By leveraging further commercial application and broadening international collaborations, they can continue to push the boundaries of AI research, solidifying their position as a leading researcher in the global AI community.

Publication  Top Notes

Development Paradigm of Artificial Intelligence in China from the Perspective of Digital Economics 📊: Z Liu, Y Zheng explore the AI development in China’s digital economy. (Journal of Chinese Economic and Business Studies, 2022)

Evolving Financial Markets: The Impact and Efficiency of AI-Driven Trading Strategies 💹: Z Liu, K Zhang, D Miao discuss the role of AI in enhancing trading efficiency. (International Conference on Intelligence Science, 2024)

Research on Intelligent Computing and Trustworthy Machine Learning in Financial Complex Systems 🤖: Z Liu, K Zhang, Y Zheng, S Xu, J Qu investigate AI applications in financial systems. (2024 International Conference on Data-Driven Optimization)

Application Methods of Large Language Model Interpretability in FinTech Scenarios 💼: Z Liu, K Zhang, Y Zheng, Z Sun study LLM interpretability in financial technology. (2024 International Conference on Computer Communication and Artificial Intelligence)

Application of Visualization Methods in Neural Network Training Processes 👁️: Z Liu, K Zhang, Y Zheng, L Zheng examine neural network training visualization techniques. (2024 International Symposium on AI)

A New Era of Financial Services: How AI Enhances Investment Efficiency 💼📈: Z Liu, K Zhang, H Zhang explore AI’s role in improving investment practices. (International Studies of Economics, 2024)

Wenwei Liu | Terahertz Metamaterials | Best Researcher Award

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Assoc Prof Dr. Wenwei Liu | Terahertz Metamaterials | Best Researcher Award

Assoc Prof Dr at Nankai University, China

Assoc. Prof. Dr. Wenwei Liu is a distinguished researcher at Nankai University, specializing in optics and light-matter interactions. With over 60 publications and multiple high-impact papers in renowned journals like Nano Letters and Optica, he has made significant contributions to the field of informational photonics. He has also secured two Chinese and two US patents, showcasing his innovative prowess. Dr. Liu’s research is widely recognized, and he has received prestigious awards such as the Wang Daheng Optics Award and the Top Ten Innovation Achievements from the National Postdoctoral Program.

Publication Profile

scholar

Education🎓

Dr. Wenwei Liu earned his Ph.D. in Optics from the School of Physics, Nankai University (2013.9 – 2018.6), where he conducted groundbreaking research on subwavelength micro-/nano-structures.  He holds an impressive academic background, completing both his graduate and doctoral studies at Nankai University, one of China’s premier institutions in physical sciences. 📘 His research excellence led to his postdoctoral studies at the same institution, further deepening his expertise in optical information transmission and imaging systems. 📈

Professional Experience🌐

Dr. Liu has served as an Associate Professor at the School of Physics, Nankai University, since December 2021. 🏫 Prior to this role, he completed a prestigious postdoctoral fellowship at the same institution (2018.7 – 2023.7). His professional journey reflects a steady rise in the field of optical engineering, with increasing responsibilities and contributions to both academia and industry. 🔬 Throughout his career, he has been involved in cutting-edge research projects, successfully leading teams and producing influential studies in light-matter interactions and optical fields coherence control.

Awards and Honors 🏆

Dr. Liu has been honored with multiple prestigious awards throughout his career. 🏅 In 2021, he earned the Top Ten Innovation Achievements of National Postdoctoral Program for Innovative Talents. 🌍 Additionally, his doctoral research garnered a National Optical Excellent Doctoral Dissertation Nomination in 2020. As a student, he also received the Wang Daheng Optics Award for College Students in 2019, awarded by the Chinese Optical Society. 🌟 These accolades highlight his dedication and contributions to optics and photonics research, solidifying his reputation as an innovator in the field.

Research Focus🔬

Dr. Liu’s research focuses on light-matter interactions at subwavelength scales using micro-/nano-structures.  His work in informational photonics has led to advancements in multifunctional optical information transmission, coherence control, and metalens arrays for aberration-free positioning. 💻 He has pioneered several projects under the National Postdoctoral Program for Innovative Talents, as well as the National Natural Science Foundation of China. His work in imaging systems and optical field modulation has practical applications in fields ranging from telecommunications to biomedical imaging. 📡

Publication  Top Notes

Metasurface‐Empowered Optical Multiplexing and Multifunction – Advanced Materials (2020), 253 citations. 📄

Broadband Cross-Polarization Conversion in Transmission Mode – Optics Letters (2015), 247 citations. 📡

High-Quality-Factor Multiple Fano Resonances for Refractive Index Sensing – Optics Letters (2018), 206 citations. 🔬

Ultrahighly Saturated Structural Colors Enhanced by Multipolar-Modulated Metasurfaces – Nano Letters (2019), 184 citations. 🌈

Broadband Linear-to-Circular Polarization Converter – Scientific Reports (2015), 177 citations. 🌐

From Single-Dimensional to Multidimensional Manipulation of Optical Waves – Advanced Materials (2019), 172 citations. 🔄

Metasurface Enabled Wide-Angle Fourier Lens – Advanced Materials (2018), 157 citations. 🔍

Dynamically Tunable Broadband Infrared Anomalous Refraction – Advanced Optical Materials (2015), 145 citations. 🔥

Polarization-Sensitive Structural Colors – Advanced Optical Materials (2018), 131 citations. 🎨

Optical Polarization Encoding Using Graphene‐Loaded Plasmonic Metasurfaces – Advanced Optical Materials (2016), 115 citations.

Conclusion

Assoc. Prof. Dr. Wenwei Liu is an outstanding candidate for the Best Researcher Award, given his innovative research, high-impact publications, and leadership in advancing the field of optics. His work in light-matter interactions and micro/nano-structured systems is both theoretically advanced and practically relevant. While he may benefit from greater international collaboration and an emphasis on technology transfer, his current achievements position him as a strong contender for the award. His demonstrated excellence in research, combined with his potential for future breakthroughs, aligns well with the award’s objectives.

Yan Yang | cognitive impairment | Best Researcher Award

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Assist Prof Dr. Menghao Yang | Machine Learning | Best Researcher Award

Assistant Professor at Tongji University, China

A dedicated researcher with a Ph.D. in Materials Science and Engineering from Tsinghua University, this individual has made significant contributions to the fields of solid-state batteries and material interfaces. Their professional journey includes postdoctoral research at prestigious institutions like Stanford University, University of Maryland, and Iowa State’s Ames Laboratory. Currently an Assistant Professor at Tongji University, they focus on cutting-edge materials engineering, specializing in AI-driven material simulations, electrochemical modeling, and energy storage. Their commitment to advancing materials science is reflected in numerous accolades, including national scholarships and outstanding student awards.

Publication Profile

scholar

Education📚 

Ph.D. in Materials Science and Engineering (2013.08 – 2018.05): Earned at Tsinghua University, this advanced degree provided deep expertise in solid-state physics, quantum mechanics, and materials science. Their Ph.D. research honed their skills in AI-driven simulations and electrochemical modeling, particularly in battery materials. Bachelor’s Degree in Materials Science and Engineering (2009.08 – 2013.07): Northwestern Polytechnical University laid the foundation for their passion for materials science, blending theoretical knowledge with practical experience in materials development, simulation, and testing.

Professional Experience🔬 

Assistant Professor, Tongji University (2023.03 – Present): Leading research in materials science, particularly focusing on battery technologies and solid electrolytes.
👨‍🔬 Visiting Scholar/Postdoctoral Associate, Stanford University (2022.05 – 2023.02): Conducted advanced research in chemical engineering with a focus on electrochemical systems. Postdoctoral Research Associate, University of Maryland (2019.08 – 2022.04): Focused on the development of solid-state battery materials and interface modeling.
⚛️ Postdoctoral Research Associate, Ames Laboratory, Iowa State University (2018.06 – 2019.07): Worked on the physics of material interfaces and advanced catalytic modeling.

Awards and Honors🏅 

Undergraduate National Scholarship (2011.09): Awarded for academic excellence during their bachelor’s studies. Graduate National Scholarship (2017.09): Recognized for their exceptional research achievements during Ph.D. studies.Outstanding Student Award of Beijing (2015.09): Honored as one of Beijing’s top students for research and academic accomplishments.Excellent Graduate Student Award (2018.06): Commended upon completing their Ph.D. for outstanding research contributions.

Research Focus🔋

Solid-State Batteries: Investigating the interfacial atomistic mechanisms of metal stripping and plating in solid-state batteries. Inorganic Solid Electrolytes: Designing and developing new inorganic solid electrolytes to enhance battery performance. Electrochemical Modeling: Focused on simulating and calculating electrochemical properties of innovative battery materials.Catalytic Materials: Predicting the catalytic performance of layered oxide materials through advanced simulations.Cell Membranes: Studying the interface transport mechanisms in phospholipid bilayers to understand cellular interactions better.

Publication  Top Notes

  • Denary oxide nanoparticles as highly stable catalysts for methane combustion
    🧪 T. Li, Y. Yao, Z. Huang, P. Xie, Z. Liu, M. Yang, et al. (2021). Nature Catalysis, 4(1), 62-70.
    Citations: 218
  • Multi-principal elemental intermetallic nanoparticles synthesized via a disorder-to-order transition
    ⚛️ M. Cui, C. Yang, S. Hwang, M. Yang, et al. (2022). Science Advances, 8(4), eabm4322.
    Citations: 77
  • Interfacial atomistic mechanisms of lithium metal stripping and plating in solid‐state batteries
    🔋 M. Yang, Y. Liu, A. M. Nolan, Y. Mo. (2021). Advanced Materials, 33(11), 2008081.
    Citations: 73
  • Effect of pressure on elastic, mechanical and electronic properties of WSe2: A first-principles study
    🔬 L. Feng, N. Li, M. Yang, Z. Liu. (2014). Materials Research Bulletin, 50, 503-508.
    Citations: 62
  • Fundamental link between β relaxation, excess wings, and cage-breaking in metallic glasses
    🌐 H.B. Yu, M.H. Yang, et al. (2018). The Journal of Physical Chemistry Letters, 9(19), 5877-5883.
    Citations: 59
  • Predicting complex relaxation processes in metallic glass
    🧑‍💻 Y. Sun, M.H. Yang, et al. (2019). Physical Review Letters, 123(10), 105701.
    Citations: 43
  • Facilitating alkaline hydrogen evolution reaction on the hetero-interfaced Ru/RuO2 through Pt single atoms doping
    ⚡ Y. Zhu, M. Klingenhof, M. Yang, et al. (2024). Nature Communications, 15(1), 1447.
    Citations: 40
  • Interfacial defect of lithium metal in solid‐state batteries
    🔋 M. Yang, Y. Mo. (2021). Angewandte Chemie International Edition, 60(39), 21494-21501.
    Citations: 31
  • Lithium crystallization at solid interfaces
    ⚛️ M. Yang, Y. Liu, Y. Mo. (2023). Nature Communications, 14(1), 2986.
    Citations: 24

Conclusion

The candidate’s expertise in materials science, particularly in solid-state batteries, coupled with their strong computational skills and global research experience, makes them a standout contender for the Best Researcher Award. While focusing on enhancing their leadership, publication record, and industry collaborations could bolster their profile, their current trajectory reflects a deep commitment to advancing the field of energy storage and materials innovation. Given their accomplishments and potential for future breakthroughs, they are a highly deserving candidate for this prestigious award.

alain R THIERRY | Data Science and Deep Learning | Excellence in Research

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Prof. alain R THIERRY  | Data Science and Deep Learning | Excellence in Research

Director of Research, INSERM U1194, France

Dr. alain R THIERRY, a distinguished biologist, and cancer researcher, is a Director of Research at INSERM and a key figure at the Institut de Recherche en Cancérologie de Montpellier. With an impressive track record in molecular biology, gene therapy, and cancer research, Dr. alain R THIERRY has held numerous influential positions in academia and the biotechnology sector, including roles at NIH and Georgetown University. A prolific author and scientific leader, they have also founded biotech companies like MedinCell and DiaDx. Dr. alain R THIERRYcontinues to drive innovative therapeutic solutions, recognized by international honors and awards.

Publication Profile

scholar

Education🎓 

2003: Habilitation à Diriger les Recherches (HDR) in Biology-Health, Université Montpellier II 1987: CES in Human Biology (Oncology), Faculté de Médecine Paris-Sud 1986: PhD in Biochemistry, Cellular & Molecular Pharmacology, Université Montpellier II 1983: MSc in Cellular & Molecular Biology, Université de Clermont-Ferrand II 1983: Diplôme d’Ingénieur, Université Clermont-Fd II 1982: BSc in Biological Sciences & Technology, Université Clermont-Fd

Professional Experience💼 

208-present: Director of Research, INSERM, Institut de Recherche en Cancérologie, Montpellier 2001-2007: Associate Professor, Université Montpellier II2003-2004: Director of R&D, MedinCell SA, Montpellier 1997-2000: Scientific Director, Gene Therapy Dept., Biovector Therapeutics 1992-1996: Scientist, Tumor Cell Biology Lab, NCI/NIH, Bethesda 1992-1994: Adjunct Assistant Professor, Lombardi Cancer Institute, Washington DC 1988-1992: Postdoctoral Fellow, Lombardi Cancer Center, Georgetown University

Awards and Honors🏆 

1994: Federal Technology Award, NIH, USA ($10,000) 2002: Prix National de l’Innovation, Ministry of Education and Research, Paris (€300,000) 2016: Grand Prix de l’Innovation Thérapeutique, Fondation B. Denys & FRM, Montpellier (€50,000) 2022: Finalist, Prix Innovation Unicancer 2022: Innovation Award, Montpellier Université Excellence

Research Focus 🔬 

Molecular Oncology: Pioneer in understanding the molecular pathways of cancer and therapeutic gene delivery Gene Therapy: Focus on targeted gene therapy to treat cancers, with expertise in vectors and delivery systems Circulating DNA: Breakthrough research in non-invasive biomarkers for early cancer detection
Therapeutics Innovation: Key developer of novel therapeutic strategies, including drug delivery systems and cancer diagnostics
Collaborative Research: Strong interdisciplinary collaborations in biotechnology and cancer research

Publication  Top Notes

  • Origins, structures, and functions of circulating DNA in oncology
    AR Thierry, S El Messaoudi, PB Gahan, P Anker, M Stroun
    Cancer and Metastasis Reviews, 2016 | 812 citations
  • Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA
    AR Thierry, F Mouliere, S El Messaoudi, C Mollevi, E Lopez-Crapez
    Nature Medicine, 2014 | 735 citations
  • Nomenclature for synthetic gene delivery systems
    PL Felgner, Y Barenholz, JP Behr, SH Cheng, P Cullis, L Huang, AR Thierry
    Human Gene Therapy, 1997 | 652 citations
  • High fragmentation characterizes tumour-derived circulating DNA
    F Mouliere, B Robert, E Arnau Peyrotte, M Del Rio, M Ychou, F Molina, AR Thierry
    PLOS One, 2011 | 627 citations
  • Circulating cell-free DNA: preanalytical considerations
    S El Messaoudi, F Rolet, F Mouliere, AR Thierry
    Clinica Chimica Acta, 2013 | 602 citations

Conclusion:

This individual is highly suitable for the Best Researcher Award. Their long-standing career in oncology research, leadership in both academic and biotech sectors, and recognition through awards place them in an elite category of researchers. Continued engagement in broader interdisciplinary fields and public communication could further elevate their profile. Overall, their qualifications, contributions, and leadership make them a strong candidate for excellence in research awards.

Aaron Brunk | Applied and Numerical Analysis | Best Researcher Award

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Dr. Aaron Brunk | Applied and Numerical Analysis | Best Researcher Award

Dr. Johannes-Gutenberg University, Germany

Dr. Aaron Brunk is a Post-Doc Research Fellow at Johannes Gutenberg-University Mainz, specializing in numerical mathematics under Prof. Dr. Maria M. Lukácová-Medvid’ová. He focuses on thermodynamically consistent fluid modeling, parabolic cross-diffusion system analysis, and structure-preserving method construction. Dr. Brunk completed his PhD with magna cum laude in 2022, studying viscoelastic phase separation. His work includes multiple DFG projects, with roles ranging from PhD student to Principal Investigator. He is an active academic contributor, organizing seminars and workshops, presenting at international conferences, and engaging in research stays and academic self-administration. His current research projects involve variational quantitative phase-field modeling and spinodal decomposition of polymer-solvent systems.

 

Professional Profiles:

Googlescholar

🎓 Education

Nov. 2017 – Feb. 2022: Ph.D. in Mathematics (Dr. rer. nat.), Johannes Gutenberg-University Mainz, GermanyDissertation: Viscoelastic phase separation: Well-posedness and numerical analysisDisputation: 11.02.2022Degree: Magna cum laudeSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováOct. 2015 – Nov. 2017: M.Sc. in Mathematics, Johannes Gutenberg-University Mainz, GermanyThesis: Numerische Behandlung von zeitgebrochenen DiffusionsgleichungenSupervisor: Prof. Dr. Thorsten RaaschOct. 2012 – Oct. 2015: B.Sc. in Mathematics, Johannes Gutenberg-University Mainz, GermanyThesis: Mathematische Modellierung von PhosphorylierungssystemenSupervisor: Prof. Dr. Alan Rendall

🎓 Professional Experience

Feb. 2022 – Present: Post-Doc Research Fellow, Institute of Mathematics, Johannes Gutenberg-University Mainz, GermanyGroup: Numerical MathematicsSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováActivities:🧪 Modelling of thermodynamically consistent complex fluids📊 Analysis of parabolic cross-diffusion systems🔧 Construction of structure-preserving methods for cross-diffusion systems👨‍🏫 Assistant in various tutorials and seminars📚 Independent lecturingNov. 2017 – Feb. 2022: Research Assistant, Institute of Mathematics, Johannes Gutenberg-University Mainz, GermanyGroup: Numerical MathematicsSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováActivities:🧪 Modelling and analysis of viscoelastic phase separation👨‍🏫 Assistant in various tutorials and seminars

📚 Third Party Projects

Sep. 2023 – Aug. 2026: German Research Foundation (DFG) – Principal InvestigatorProject: Variational quantitative phase-field modeling and simulation of powder bed fusion additive manufacturing within the DFG Priority Programme 2256Collaborator: B.-X. Xu, Technical University Darmstadt, Material ScienceFunded Ph.D. positionFeb. 2022 – Feb. 2026: German Research Foundation (DFG) – Postdoctoral ResearcherProject: Spinodal decomposition of polymer-solvent systems within the TRR 146 Multiscale Simulation Methods for Soft Matter SystemsPrincipal Investigators: M. Lukáčová-Medvid’ová, B. DünwegNov. 2017 – Feb. 2022: German Research Foundation (DFG) – Ph.D. studentProject: Spinodal decomposition of polymer-solvent systems within the TRR 146 Multiscale Simulation Methods for Soft Matter SystemsPrincipal Investigators: M. Lukáčová-Medvid’ová, B. Dünweg, H. Egger

✍️Publications Top Note :

Analysis of a Viscoelastic Phase Separation Model

Authors: A Brunk, B Dünweg, H Egger, O Habrich, M Lukáčová-Medvid’ová, …

Journal: Journal of Physics: Condensed Matter 33 (23), 234002, 2021

Citations: 19

Global Existence of Weak Solutions to Viscoelastic Phase Separation Part: I. Regular Case

Authors: A Brunk, M Lukáčová-Medvid’ová

Journal: Nonlinearity 35 (7), 3417, 2022

Citations: 14

Modelling Cell-Cell Collision and Adhesion with the Filament Based Lamellipodium Model

Authors: N Sfakianakis, D Peurichard, A Brunk, C Schmeiser

Journal: arXiv preprint arXiv:1809.07852, 2018

Citations: 10

Global Existence of Weak Solutions to Viscoelastic Phase Separation: Part II. Degenerate Case

Authors: A Brunk, M Lukáčová-Medvid’ová

Journal: Nonlinearity 35 (7), 3459, 2022

Citations: 9

Systematic Derivation of Hydrodynamic Equations for Viscoelastic Phase Separation

Authors: D Spiller, A Brunk, O Habrich, H Egger, M Lukáčová-Medvid’ová, …

Journal: Journal of Physics: Condensed Matter 33 (36), 364001, 2021

Citations: 9

Existence, Regularity and Weak-Strong Uniqueness for the Three-Dimensional Peterlin Viscoelastic Model

Authors: A Brunk, Y Lu, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2102.02422, 2021

Citations: 9

Chemotaxis and Haptotaxis on Cellular Level

Authors: A Brunk, N Kolbe, N Sfakianakis

Journal: Theory, Numerics and Applications of Hyperbolic Problems I: Aachen, Germany, …

Citations: 4

On Existence, Uniqueness and Stability of Solutions to Cahn–Hilliard/Allen–Cahn Systems with Cross-Kinetic Coupling

Authors: A Brunk, H Egger, TD Oyedeji, Y Yang, BX Xu

Journal: Nonlinear Analysis: Real World Applications 77, 104051, 2024

Citations: 3

Stability and Discretization Error Analysis for the Cahn–Hilliard System via Relative Energy Estimates

Authors: A Brunk, H Egger, O Habrich, M Lukáčová-Medviďová

Journal: ESAIM: Mathematical Modelling and Numerical Analysis 57 (3), 1297-1322, 2023

Citations: 3

Existence and Weak-Strong Uniqueness for Global Weak Solutions for the Viscoelastic Phase Separation Model in Three Space Dimensions

Authors: A Brunk

Journal: arXiv preprint arXiv:2208.01374, 2022

Citations: 3

Relative Energy and Weak–Strong Uniqueness of a Two‐Phase Viscoelastic Phase Separation Model

Authors: A Brunk, M Lukáčová‐Medvid’ová

Journal: ZAMM‐Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte …, 2023

Citations: 2

Viscoelastic Phase Separation: Well-Posedness and Numerical Analysis

Authors: A Brunk

Journal: Dissertation, Mainz, Johannes Gutenberg-Universität Mainz, 2022

Citations: 2

Relative Energy Estimates for the Cahn-Hilliard Equation with Concentration Dependent Mobility

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2102.05704, 2021

Citations: 2

Stability, Convergence, and Sensitivity Analysis of the FBLM and the Corresponding FEM

Authors: N Sfakianakis, A Brunk

Journal: Bulletin of Mathematical Biology 80, 2789-2827, 2018

Citations: 2

Fundamentals of the Oldroyd-B Model Revisited: Tensorial vs. Vectorial Theory

Authors: A Brunk, J Chaudhuri, M Lukacova-Medvidova, B Duenweg

Journal: arXiv preprint arXiv:2308.01326, 2023

Citations: 1

On Uniqueness and Stable Estimation of Multiple Parameters in the Cahn–Hilliard Equation

Authors: A Brunk, H Egger, O Habrich

Journal: Inverse Problems 39 (6), 065002, 2023

Citations: 1

A Second-Order Fully-Balanced Structure-Preserving Variational Discretization Scheme for the Cahn-Hilliard Navier-Stokes System

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2209.03849, 2022

Citations: 1

Structure-Preserving Approximation of the Cahn-Hilliard-Biot System

Authors: A Brunk, M Fritz

Journal: arXiv preprint arXiv:2407.12349, 2024

Error Analysis for a Viscoelastic Phase Separation Model

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2407.01803, 2024

Nonisothermal Cahn-Hilliard Navier-Stokes System

Authors: A Brunk, D Schumann

Journal: arXiv preprint arXiv:2405.13936, 2024