Manar Hamza | Computer Science Data mining | Best Researcher Award

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

professor atΒ  Prince Sattam bin Abd El Aziz University, China

πŸ‘©β€πŸ« Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. πŸ’» 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 πŸŽ“

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

Experience πŸ–₯️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). πŸ‘©β€πŸ’Ό Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). πŸ‡ΈπŸ‡© Lecturer at Omdurman Islamic University, Sudan (2005–2012). πŸ‘©β€πŸ”¬ E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors πŸ†

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

Research Focus πŸ”

Data mining, text mining, and information security are core research areas. πŸ“Š Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. πŸ›‘οΈ 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. πŸ“Š 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. πŸ’» Their leadership in AI governance and multimodal model development has solidified their role as a key player in the AI landscape. πŸ€– 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 πŸŽ“

They are pursuing an IMBA at the University of Hong Kong Business School (2024-2026).Β  They completed their Doctorate in Intelligent Manufacturing at ISTEC Paris (2021-2024).Β  Their undergraduate education is in Computer Science and Technology from Beijing University of Posts and Telecommunications (2007-2011).Β  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 πŸ”§

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 πŸ†Β 

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.Β  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. πŸ‡¨πŸ‡³ 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. πŸ… Their accolades reflect their contributions to AI ethics, governance, and research.

Research FocusΒ  πŸ”¬

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. Β Their work also addresses AI governance, ensuring transparency, fairness, and compliance in AI systems. Β They focus on practical applications in digital healthcare, where multimodal data fusion has improved diagnostic accuracy and patient care. Β 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.

PublicationΒ  Top Notes

Development Paradigm of Artificial Intelligence in China from the Perspective of Digital Economics πŸ“Š: 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 πŸ’Ή: 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 πŸ€–: 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 πŸ’Ό: 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 πŸ‘οΈ: 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 πŸ’ΌπŸ“ˆ: 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

EducationπŸŽ“

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.Β  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. πŸ“˜ His research excellence led to his postdoctoral studies at the same institution, further deepening his expertise in optical information transmission and imaging systems. πŸ“ˆ

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. πŸ”¬ 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 πŸ†

Dr. Liu has been honored with multiple prestigious awards throughout his career. πŸ… 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 FocusπŸ”¬

Dr. Liu’s research focuses on light-matter interactions at subwavelength scales using micro-/nano-structures. Β His work in informational photonics has led to advancements in multifunctional optical information transmission, coherence control, and metalens arrays for aberration-free positioning. πŸ’» 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. πŸ“‘

PublicationΒ  Top Notes

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

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

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

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. πŸ”„

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

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

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

EducationπŸ“šΒ 

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 ExperienceπŸ”¬Β 

Assistant Professor, Tongji University (2023.03 – Present): Leading research in materials science, particularly focusing on battery technologies and solid electrolytes.
πŸ‘¨β€πŸ”¬ 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.
βš›οΈ 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 HonorsπŸ…Β 

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 FocusπŸ”‹

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.

PublicationΒ  Top Notes

  • Denary oxide nanoparticles as highly stable catalysts for methane combustion
    πŸ§ͺ 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
    βš›οΈ 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
    πŸ”‹ 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
    πŸ”¬ L. Feng, N. Li, M. Yang, Z. Liu. (2014). Materials Research Bulletin, 50, 503-508.
    Citations: 62
  • Fundamental link between Ξ² 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
    πŸ§‘β€πŸ’» 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
    πŸ”‹ M. Yang, Y. Mo. (2021). Angewandte Chemie International Edition, 60(39), 21494-21501.
    Citations: 31
  • Lithium crystallization at solid interfaces
    βš›οΈ 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 ĐorΔ‘eviΔ‡ 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. ĐorΔ‘eviΔ‡ 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 πŸš€

Dr. Katarina ĐorΔ‘eviΔ‡, 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. ĐorΔ‘eviΔ‡’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.

πŸ”Š 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.

πŸ€– Neural Networks & Material Characterization:

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

πŸ’» 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.

πŸ”„ Inverse Problem Solving:

Dr. ĐorΔ‘eviΔ‡ 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.

πŸ”’ 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 ĐorΔ‘eviΔ‡’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. πŸŒπŸ”¬βœ¨

πŸ“–Β Publications Top Note :

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

Authors: КL DjordjeviΔ‡, DD Markushev, ŽМ Δ†ojbaΕ‘iΔ‡, KL DjordjeviΔ‡
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 DjordjeviΔ‡, MI JordoviΔ‡-PavloviΔ‡, Ε½M Δ†ojbaΕ‘iΔ‡, SP GaloviΔ‡, MN PopoviΔ‡ …
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 TerziΔ‡, N ĐorΔ‘eviΔ‡, M MitriΔ‡, S MarkoviΔ‡, K ĐorΔ‘eviΔ‡, VB PavloviΔ‡
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 Ćojbaőić, 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 DjordjeviΔ‡, SP GaloviΔ‡, MN PopoviΔ‡, MV NeΕ‘iΔ‡, IP StanimiroviΔ‡, ZI …
Journal: Measurement, 111537, 2022
Citations: 10