Haichen Zhou | Artificial Intelligence | Best Researcher Award

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Dr. Haichen Zhou | Artificial Intelligence | Best Researcher Award

Senior Engineer | Automation Research and Design Institute of Metallurgical Industry | China

Dr. Haichen Zhou is a distinguished metallurgical researcher and Senior Quality Engineer at the Automation Research and Design Institute of Metallurgical Industry Co., Ltd., under the China Iron & Steel Research Institute Group Co., Ltd. He received his Ph.D. from the University of Science and Technology Beijing (USTB), a leading institution renowned for metallurgy and materials science. Over the course of his career, Dr. Zhou has established himself as an expert in steelmaking and metallurgical process optimization, with a strong focus on inclusions control in liquid steel and slab quality improvement. His professional expertise spans physical simulation, numerical modeling, and the integration of artificial intelligence into metallurgical research and industrial practice. Dr. Zhou has authored 14 papers published in highly regarded journals such as Metallurgical and Materials Transactions B (MMTB), ISIJ International, Steel Research International, Ironmaking and Steelmaking, and Metallurgical Research & Technology (MRT). His research contributions have not only advanced theoretical understanding but also delivered practical solutions to improve steel quality and process reliability. Combining academic depth with industrial experience, he continues to play a key role in bridging science, engineering, and innovation in modern steel manufacturing.

Professional Profile

Orcid

Education

Dr. Haichen Zhou earned his doctoral degree in metallurgical engineering from the University of Science and Technology Beijing (USTB), a globally recognized institution for research in materials science, metallurgy, and engineering. During his Ph.D. studies, he specialized in steelmaking processes with a particular focus on inclusions control technology, steel slab quality assessment, and advanced metallurgical process simulations. His academic training combined theoretical knowledge with experimental and computational methods, allowing him to address both fundamental and applied aspects of metallurgical phenomena. At USTB, Dr. Zhou carried out extensive research on the thermodynamics and kinetics of inclusions formation, the influence of microstructural defects on steel properties, and the use of physical simulation for understanding process behavior. In addition, he explored the potential of numerical simulation and artificial intelligence to predict, optimize, and control complex metallurgical processes, thereby merging traditional metallurgy with emerging computational approaches. His Ph.D. thesis provided valuable insights into steel quality improvement, combining laboratory-scale investigations with industrial applications. This solid academic foundation not only prepared him for his current research and engineering responsibilities but also positioned him as a specialist capable of leading interdisciplinary advancements in metallurgical science and steelmaking technology.

Experience

Dr. Haichen Zhou has accumulated extensive professional experience as a metallurgical engineer and researcher. He currently serves as a Senior Quality Engineer at the Automation Research and Design Institute of Metallurgical Industry Co., Ltd., part of the China Iron & Steel Research Institute Group Co., Ltd. In this capacity, he is responsible for developing and implementing advanced technologies for steel quality improvement, defect prevention, and metallurgical process optimization. His work encompasses inclusions control in liquid steel, continuous casting process refinement, and slab defect mitigation, with the overarching goal of producing high-performance steels for industrial applications. Dr. Zhou’s expertise also extends to physical simulation, which he uses to replicate and study metallurgical phenomena under controlled conditions, as well as numerical simulation for predictive modeling of steelmaking processes. More recently, he has contributed to applying artificial intelligence in metallurgy, utilizing machine learning for process monitoring, quality prediction, and optimization. Prior to his current role, his academic research and collaborative projects provided him with strong exposure to both laboratory studies and industrial challenges. His career demonstrates a seamless integration of academic knowledge with industrial practice, ensuring impactful contributions to both scientific progress and steel industry advancements.

Awards and Honors

Throughout his career, Dr. Haichen Zhou has earned recognition for his research contributions, publications, and industrial innovations in metallurgical engineering. While completing his Ph.D. at the University of Science and Technology Beijing (USTB), he was commended for his doctoral research on steel quality improvement and inclusions control technology. His published works in high-impact journals, including Metallurgical and Materials Transactions B, ISIJ International, and Steel Research International, have attracted attention from the global metallurgy community, highlighting his role as a rising expert in his field. At the China Iron & Steel Research Institute Group, Dr. Zhou has been involved in major research and development projects, earning professional acknowledgment for his role in advancing inclusions control methods and integrating artificial intelligence into steel manufacturing practices. His ability to merge classical metallurgical knowledge with modern computational technologies positions him as an innovative thinker in steel engineering. Although specific awards are not listed, his 14 peer-reviewed publications, professional designations, and continued contributions to steel process optimization represent significant milestones of achievement. These accomplishments reflect both his scientific rigor and his dedication to advancing the steel industry’s pursuit of higher quality, efficiency, and sustainability.

Research Focus

Dr. Haichen Zhou’s research focuses on advancing steelmaking and metallurgical science through a combination of experimental, computational, and data-driven approaches. His primary expertise lies in inclusions control technology in liquid steel, which is crucial for improving the purity, mechanical properties, and performance of final steel products. He has extensively studied steel slab quality, analyzing the causes of defects during solidification and developing strategies to minimize flaws, thereby enhancing steel consistency and reliability. His research also integrates physical simulation techniques to reproduce metallurgical processes under controlled laboratory conditions, providing critical insights into inclusions behavior and slab defect evolution. Complementing these experimental approaches, Dr. Zhou applies numerical simulation to predict and optimize complex steelmaking phenomena, offering accurate process models for industrial use. In recent years, he has expanded his work to include artificial intelligence applications in steel manufacturing. By using machine learning and data analytics, he has developed predictive models for defect formation, real-time monitoring systems, and process optimization frameworks. His interdisciplinary approach, combining metallurgy with computational intelligence, contributes to both fundamental metallurgical knowledge and industrial innovation. Ultimately, his research seeks to enhance steel quality, improve production efficiency, and support the sustainable development of advanced steel technologies.

Publication Top Notes 

Mathematical Simulation and Industrial Implications of Swirling Gas-Solid Distributor in the Bottom-Blowing O2–CaO Steelmaking Converter Process
Year: 2025

Development of Ca‐Containing Ferrosilicon Instead of Ca Treatment in High Silicon Steels during Ladle Refining
Year: 2025

Mathematical modeling of the effect of SEN outport shape on the bubble size distribution in a wide slab caster mold
Year: 2025

Optimization of Vortex Slag Entrainment during Ladle Teeming Process in the Continuous Casting of Automobile Outer Panel
Year: 2025

Conclusion

Overall, Dr. Haichen Zhou is a strong candidate for recognition as a Best Researcher, particularly in metallurgical process engineering and steel quality control. His track record of publications, technical expertise, and innovative integration of artificial intelligence into steelmaking research represent clear strengths. With further expansion of international visibility, leadership roles, and demonstration of broader impact, he has the potential to stand out as an exceptional awardee. At this stage, he is certainly a worthy nominee, and with continued contributions, he could establish himself as a leading figure in the global metallurgy research community.

Dr. Giuseppe D’Albis | Intelligenza Artificiale | Excellence in Research Award

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Dr. Giuseppe D’Albis | Intelligenza Artificiale | Excellence in Research Award

Resident in Oral Surgery, University of Bari Aldo Moro, Italy

Giuseppe D’Albis is a dedicated dental professional with a strong academic background. Born on October 27, 1991, he has pursued various specializations in dentistry, including oral surgery, prosthodontics, and implantology. Currently, he is a resident in Oral Surgery at Bari Aldo Moro University. Giuseppe has participated in numerous scientific courses and conferences, showcasing his commitment to continuous learning and professional development.

Professional Profile

ORCID

🎓 Education

Giuseppe D’Albis has an impressive educational background in dentistry. He earned his Degree in Dentistry and Dental Prosthetics from the European University of Madrid. He then pursued multiple second-level master’s degrees in specialized fields, including Prosthodontics and New Technologies, Osseointegrated Implantology, Integrated Clinical Approach in Periodontology and Implantology, and Oral and Emergency Dental Surgery. His academic pursuits demonstrate his dedication to advancing his knowledge and skills in dentistry.

👩‍🏫 Experience

As a resident in Oral Surgery, Giuseppe D’Albis has gained valuable clinical experience in diagnosing and treating various oral health issues. He has participated in numerous training courses and conferences, staying up-to-date with the latest techniques and advancements in dentistry. His experience in different areas of dentistry, including prosthodontics, implantology, and oral surgery, makes him a well-rounded professional.

🏆 Awards and Honors

Although specific awards and honors are not mentioned in the provided CV, Giuseppe D’Albis’s participation in various scientific courses and conferences demonstrates his commitment to excellence in dentistry. His involvement in continuous learning and professional development showcases his dedication to providing high-quality patient care.

🔬 Research Interests

Giuseppe D’Albis’s research focus appears to be in the areas of oral surgery, prosthodontics, and implantology. His master’s thesis on “Intraoral Transmission of Bacteria and Its Relationship to Periimplantitis” suggests an interest in investigating the causes and consequences of periimplantitis. His participation in conferences and training courses related to these topics further highlights his research focus.

📚Top Noted Publications

1. Utilization of Platelet-Rich Plasma in Oral Surgery: A Systematic Review of the Literature 📚
2. Adjunctive Effects of Diode Laser in Surgical Periodontal Therapy: A Narrative Review of the Literature 💡
3. Odontogenic Myxoma Associated to Unerupted Mandibular Molar in a Pediatric Patient: A New Case Description with Comprehensive Literature Analysis 👦
4. Diagnostic Challenges of Traumatic Ulcerative Granuloma with Stromal Eosinophilia in the Hard Palate 🔍
5. Immediate Loading Implants in Fixed Partial Dentures 💯
6. The Role and Applications of Artificial Intelligence in Dental Implant Planning: A Systematic Review 🤖
7. Periodontal Health and Its Relationship with Psychological Stress: A Cross-Sectional Study 🤯
8. Single-implant-supported zirconia fixed partial denture with a mesial cantilever extension: a case report 💼
9. Augmented Reality-Assisted Surgical Exposure of an Impacted Tooth: A Pilot Study 🔥
10. Implant-supported zirconia fixed partial dentures cantilevered in the lateral-posterior area: A 4-year clinical results 📊
11. Use of hyaluronic acid for regeneration of maxillofacial bones 💊
12. SINGLE IMPLANT-SUPPORTED TWO-UNIT IN THE POSTERIOR AREA: CASE REPORT AND LITERATURE REVIEW 📄
13. Orientation of digital casts according to the face-bow arbitrary plan 🎨
14. Tunnel access for ridge augmentation: A review 📖
15. The Role and Applications of Artificial Intelligence in Dental Implant Planning (Working paper) 🤖

Conclusion

Giuseppe D’Albis demonstrates potential as a researcher in the field of dentistry, with a strong educational background and clinical experience. While there are areas for improvement, his participation in scientific courses and conferences showcases his commitment to continuous learning. With focused efforts on publishing research and exploring interdisciplinary collaborations, he could become a strong candidate for the Best Researcher Award.

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.

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

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Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic, University of Belgrade, Serbia

Dr. Katarina Đorđević holds a PhD in Physics and is an expert in the physics of condensed matter and photoacoustics. She has significant experience in applying neural networks for material characterization, supervised machine learning, and solving inverse problems. Dr. Đorđević is skilled in numerical testing and developing measurement procedures, as well as utilizing computational intelligence algorithms in various applications. Her work involves a blend of theoretical and practical approaches, leveraging advanced computational techniques to enhance understanding and innovation in material sciences.

 

Professional Profiles:

Google Scholar

Intelligence 🚀

Dr. Katarina Đorđević, PhD in Physics, is a renowned expert with extensive experience in the physics of condensed matter, photoacoustics, and the application of neural networks in material characterization. Her diverse expertise spans multiple cutting-edge fields, making her a leading figure in both theoretical and applied physics.

🌟 Physics of Condensed Matter:

Dr. Đorđević’s work in condensed matter physics delves into the intricate properties of matter in various states, contributing to a deeper understanding of material behavior under different conditions.

🔊 Photoacoustics:

She is well-versed in photoacoustics, a technique that combines light and sound to probe the properties of materials. This innovative approach allows for non-invasive, highly precise material characterization.

🤖 Neural Networks & Material Characterization:

Leveraging neural networks, Dr. Đorđević has advanced the field of material characterization. Her research utilizes these artificial intelligence systems to analyze and predict material properties with unprecedented accuracy.

💻 Supervised Machine Learning:

A significant portion of her work involves supervised machine learning, where she trains models to recognize patterns and make predictions based on extensive datasets. This has vast applications in materials science and beyond.

🔄 Inverse Problem Solving:

Dr. Đorđević excels in solving inverse problems, which involve determining unknown causes from known consequences. This is crucial in many scientific and engineering disciplines, where direct measurement is challenging or impossible.

🔢 Numerical Testing & Measurement Procedures:

Her expertise extends to numerical testing and developing precise measurement procedures, ensuring accuracy and reliability in experimental physics.

🧠 Computational Intelligence Algorithms:

She applies advanced computational intelligence algorithms to tackle complex problems in physics and material science, driving innovation and efficiency in her research.Dr. Katarina Đorđević’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. 🌍🔬✨

📖 Publications Top Note :

1. Photoacoustic Measurements of the Thermal and Elastic Properties of n-type Silicon Using Neural Networks

Authors: КL Djordjević, DD Markushev, ŽМ Ćojbašić, KL Djordjević
Journal: Silicon 12 (6), 1289-1300, 2020
Citations: 21

2. Computationally Intelligent Description of a Photoacoustic Detector

Authors: MI Jordovic-Pavlovic, AD Kupusinac, KL Djordjevic, SP Galovic, …
Journal: Optical and Quantum Electronics 52, 1-14, 2020
Citations: 19

3. Development and Comparison of Techniques for Solving the Inverse Problem in Photoacoustic Characterization of Semiconductors

Authors: M Nesic, M Popovic, K Djordjevic, V Miletic, M Jordovic-Pavlovic, …
Journal: Optical and Quantum Electronics 53, 1-16, 2021
Citations: 17

4. Photoacoustic Optical Semiconductor Characterization Based on Machine Learning and Reverse-Back Procedure

Authors: КL Djordjevic, SP Galovic, MI Jordovic-Pavlovic, MV Nesic, MN Popovic, …
Journal: Optical and Quantum Electronics 52, 1-9, 2020
Citations: 16

5. Influence of Data Scaling and Normalization on Overall Neural Network Performances in Photoacoustics

Authors: КLj Djordjević, MI Jordović-Pavlović, ŽM Ćojbašić, SP Galović, MN Popović …
Journal: Optical and Quantum Electronics 54 (501), 31-35, 2022
Citations: 14*

6. Photothermal Response of Polymeric Materials Including Complex Heat Capacity

Authors: KL Djordjevic, D Milicevic, SP Galovic, E Suljovrujic, SK Jacimovski, …
Journal: International Journal of Thermophysics 43 (5), 68, 2022
Citations: 14

7. Estimation of Linear Expansion Coefficient and Thermal Diffusivity by Photoacoustic Numerical Self-Consistent Procedure

Authors: MV Nesic, MN Popovic, SP Galovic, KL Djordjevic, MI Jordovic-Pavlovic, …
Journal: Journal of Applied Physics 131 (10), 2022
Citations: 13

8. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials

Authors: A Terzić, N Đorđević, M Mitrić, S Marković, K Đorđević, VB Pavlović
Journal: Science of Sintering 49 (1), 23-37, 2017
Citations: 13

9. Inverse Problem Solving in Semiconductor Photoacoustics by Neural Networks

Authors: KL Djordjevic, DD Markushev, ŽM Ćojbašić, SP Galović
Journal: Inverse Problems in Science and Engineering 29 (2), 248-262, 2021
Citations: 11

10. Use Neural Network in Photoacoustic Measurement of Thermoelastic Properties of Aluminum Foil

Authors: К Lj Djordjević, SP Galović, MN Popović, MV Nešić, IP Stanimirović, ZI …
Journal: Measurement, 111537, 2022
Citations: 10