Prof. Chong Hyun Lee | Deep Learning | Best Researcher Award

Published on 28/10/202528/10/2025 by Mechanics Awards

Prof. Chong Hyun Lee | Deep Learning | Best Researcher Award

Professor | Jeju National University | South Korea

Dr. Chong Hyun Lee is a distinguished researcher and academic in the fields of electronics, power transfer systems, ocean system engineering, and applied signal processing, with a prolific research record and recognized scientific excellence. As a long-standing IEEE member, Dr. Lee has made significant contributions to the advancement of electronic and communication technologies through innovation, leadership, and collaborative research. His work has been recognized with prestigious honors, including the Best Science and Technology Paper Award from the Korean Federation of Science and Technology Societies (KOFST) and the Best Paper Award in Ocean System Engineering from the Institute of Electronics and Information Engineers in South Korea, reflecting his high academic impact and technical expertise. Dr. Lee’s research encompasses a wide range of advanced topics, including compact impedance matching circuits for wideband power transfer in Janus Helmholtz transducers, weakly supervised graph neural networks for line spectrum extraction, and DC power boosting circuits for triboelectric nanogenerators with high intrinsic impedance and multi-harmonic output. His interdisciplinary work bridges marine engineering, electronics, and nanogenerator technologies, offering practical applications in sustainable energy systems, signal processing, and sensor innovation.

Profile: Scopus | Orcid | Google Scholar

Featured Publications:

Lee, C. H., & co-authors. (2024). DC power boosting circuit for freestanding-sliding triboelectric nanogenerators with high intrinsic impedance and multi-harmonic output. Advanced Materials Technologies.

Lee, C. H., & co-authors. (2024). Passive sonar signal classification using graph neural network based on image patch. Journal of the Acoustical Society of Korea.

Lee, C. H., & co-authors. (2023). Encoding and decoding-based normalizing flows for image anomaly localization. Electronics Letters.

Lee, C. H., & co-authors. (2023). Abnormal sonar signal detection using recurrent neural network and vector quantization. Journal of the Acoustical Society of Korea.

Yin Fei Xu | Deep Learning | Excellence in Research Award

Published on 26/09/202526/09/2025 by Mechanics Awards

Assoc. Prof. Dr. Yin Fei Xu | Deep Learning | Excellence in Research Award

Associate Professor | Southeast University | China

Yinfei Xu is an Associate Researcher in the Department of Signal Processing, School of Information Science and Engineering at Southeast University, a master’s and doctoral supervisor and a Zhishan Young Scholar of Southeast University. He received his PhD in signal and information processing from Southeast University and carried out research as a research assistant and postdoctoral fellow at the Chinese University of Hong Kong and as a visiting PhD scholar at McMaster University in Canada. His research is deeply rooted in statistical signal processing, information theory, machine-learning-driven algorithmic design, optimization for real-world scenarios, statistical data analysis, and the development of artificial-intelligence models for image, speech, and multimodal applications. He has led or participated in more than ten national, provincial, industrial, and laboratory research projects and has published over seventy academic papers in high-impact international journals. As first author he has contributed to a number of influential publications including New Proofs of Gaussian Extremal Inequalities With Applications in IEEE Transactions on Information Theory, Information Embedding With Stegotext Reconstruction in IEEE Transactions on Information Forensics and Security, Secret Key Generation From Vector Gaussian Sources With Public and Private Communications in IEEE Transactions on Information Theory, Vector Gaussian Successive Refinement With Degraded Side Information in IEEE Transactions on Information Theory, Asymptotical Optimality of Change Point Detection With Unknown Discrete Post-Change Distributions in IEEE Signal Processing Letters, The Sum Rate of Vector Gaussian Multiple Description Coding with Tree-Structured Covariance Distortion Constraints in IEEE Transactions on Information Theory.

Profile: Orcid

Featured Publications:

Zhang, J., Xu, H., Zheng, A., Cao, D., Xu, Y., & Lin, C. (2025). Transmitting status updates on infinite capacity systems with eavesdropper: Freshness advantage of legitimate receiver. Entropy.

Zhang, J., & Xu, Y. (2022). Age analysis of status updating system with probabilistic packet preemption. Entropy.

Xu, Y., Zu, Y., & Zhang, H. (2021). Optimal inter-organization control of collaborative advertising with myopic and far-sighted behaviors. Entropy.

Zhang, J., & Xu, Y. Age analysis of status updating system with probabilistic packet preemption.

Zinah Saeed | Deep Learning | Best Researcher Award

Published on 24/09/202524/09/2025 by Mechanics Awards

Ms. Zinah Saeed | Deep Learning | Best Researcher Award

Universiti Sains Malaysia | Iraq

Saeed ZR is a dedicated researcher and academic with a strong background in computer science, networking technology, and innovative applications of artificial intelligence, currently pursuing his doctoral studies in computer science at the School of Computer Sciences, Universiti Sains Malaysia, after completing a master’s degree in networking technology at Universiti Teknikal Malaysia Melaka and a bachelor’s degree in computer science at Mustansiriyah University in Baghdad, building his academic journey on a foundation of technical expertise and analytical thinking, his research interests cover metaheuristic algorithms, artificial intelligence, deep learning, gesture recognition, assistive technologies, human–computer interaction, and networking security, he has contributed to the academic community with impactful publications including a hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language, a systematic review on systems-based sensory gloves for sign language pattern recognition, and research on improving cloud storage security using three layers of cryptography algorithms, his professional journey includes significant teaching experience as a lecturer at the Iraqi Police Academy where he worked to advance education and training, and his ongoing research and doctoral studies have strengthened his ability to design, implement, and test intelligent systems addressing real-world challenges, his technical skills encompass proficiency in computer software, Microsoft Office applications, and operating systems across Windows and Mac environments, alongside practical programming expertise in Python for scripting and data processing, he is also experienced with widely used research and software tools such as Jupyter, Colab, Git, SPSS, and basic MATLAB, beyond his professional life he nurtures a passion for reading, research, and continuous learning, qualities that support his growth as a thoughtful academic and innovative researcher, his multidisciplinary focus, combined with a strong commitment to impactful scientific contributions, reflects a future-oriented career in advancing artificial intelligence and human-centered technologies.

Profile: Google Scholar

Featured Publications:

Saeed, Z. R., Ibrahim, N. F., Zainol, Z. B., & Mohammed, K. K. (2025). A hybrid improved IRSO–CNN algorithm for accurate recognition of dynamic gestures in Malaysian sign language. Journal of Electrical and Computer Engineering, 2025(1), 6430675.

Saeed, Z. R., Zainol, Z. B., Zaidan, B. B., & Alamoodi, A. H. (2022). A systematic review on systems-based sensory gloves for sign language pattern recognition: An update from 2017 to 2022. IEEE Access, 10, 123358–123377.

Saeed, Z. R., Zakiah Ayop, N. A., & Baharon, M. R. (2018). Improved cloud storage security using three layers cryptography algorithms. International Journal of Computer Science and Information Security, 16(10), 11–18.

Tao Hu | Artificial Intelligence| Best Researcher Award

Published on 17/09/202517/09/2025 by Mechanics Awards

Dr. Tao Hu | Artificial Intelligence | Best Researcher Award

The Affiliated Yuyao Yangming Hospital of Medical School of Ningbo University | China

Dr. Tao Hu is a highly accomplished medical professional and researcher from China, serving at The Affiliated Yuyao Yangming Hospital of the Medical School of Ningbo University, with specialization in thyroid surgery, breast surgery, and anorectal surgery. Having completed his doctoral education in health sciences, Dr. Hu has developed an expertise in combining surgical practice with advanced computational methods, particularly artificial intelligence and machine learning applications in clinical diagnostics and predictive modeling. His professional experience includes independently completing over surgical operations and contributing to multiple provincial-level scientific research projects, including support from the Zhejiang Health Information Association Research Program , which highlights his ability to bridge medical practice with innovative research applications. Dr. Hu’s research interests lie primarily in developing predictive tools that integrate clinical information data with artificial intelligence to forecast disease occurrence, progression, and postoperative risks, especially in thyroid carcinoma, where his recent work has introduced novel models for preoperative risk stratification and lymph node metastasis prediction. His research skills are demonstrated through proficiency in clinical data analysis, ultrasound imaging interpretation, radiomics, and the application of machine learning frameworks to enhance diagnostic accuracy and surgical decision-making. In recent years, Dr. Hu has published several impactful articles in high-quality, peer-reviewed journals such as Endocrine, Frontiers in Endocrinology, and the Journal of Clinical Ultrasound, marking him as a significant contributor to evidence-based surgical practices. While his awards and honors primarily reflect academic and clinical achievements, his recognition through this nomination underscores his growing international reputation as a leader in health sciences research. In conclusion, Dr. Hu’s blend of clinical excellence, innovative research in artificial intelligence applications, and dedication to improving surgical outcomes make him a highly deserving recipient of the Best Researcher Award, as his work holds great promise for advancing both scientific knowledge and patient care globally.

Profile: Orcid

Featured Publications:

Hu, T., Cai, Y., Zhou, T., Zhang, Y., Huang, K., Huang, X., Qian, S., Wang, Q., & Luo, D. (2025). Machine learning‐based prediction of lymph node metastasis and volume using preoperative ultrasound features in papillary thyroid carcinoma. Journal of Clinical Ultrasound. Advance online publication.

Hu, T., Zhou, T., Zhang, Y., Zhou, L., Huang, X., Cai, Y., Qian, S., Huang, K., & Luo, D. (2024). The predictive value of the thyroid nodule benign and malignant based on the ultrasound nodule‐to‐muscle gray‐scale ratio. Journal of Clinical Ultrasound, 52(1).

Zhao, L., Hu, T., Cai, Y., Zhou, T., Zhang, W., Wu, F., Zhang, Y., & Luo, D. (2023). Preoperative risk stratification for patients with ≤ 1 cm papillary thyroid carcinomas based on preoperative blood inflammatory markers: Construction of a dynamic predictive model. Frontiers in Endocrinology, 14, 1254124.

Zhou, T., Xu, L., Shi, J., Zhang, Y., Lin, X., Wang, Y., Hu, T., Xu, R., Xie, L., & Sun, L., et al. (2023). US of thyroid nodules: Can AI-assisted diagnostic system compete with fine needle aspiration? European Radiology. Advance online publication.

Zhou, T., Hu, T., Ni, Z., Yao, C., Xie, Y., Jin, H., Luo, D., & Huang, H. (2023). Comparative analysis of machine learning-based ultrasound radiomics in predicting malignancy of partially cystic thyroid nodules. Endocrine. Advance online publication.

Sheeba Rachel S | Machine Learning | Best Researcher Award

Published on 12/09/202512/09/2025 by Mechanics Awards

Mrs. Sheeba Rachel S | Machine Learning| Best Researcher Award

Assistant Professor | Sri Sai Ram Engineering College | India

S. Sheeba Rachel has contributed extensively to the fields of artificial intelligence, machine learning, deep learning, healthcare technologies, smart devices, image processing, cloud computing, and Internet of Things with publications including Cardiovascular Disease Prediction Using Machine Learning and Deep Learning, Heart Disease Prediction of an Individual Using SVM Algorithm, Automated Driving License Testing System, Real-Time Face Detection and Identification Using Machine Learning Algorithm for Improving the Security in Public Places Using Closed Circuit Television, LEARNAUT – Upgraded Learning Environment and Web Application for Autism Environment Using AR-VR, VATTEN – A Smart Water Monitoring System, Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model, EDSYS – A Smart Campus Management System, TRACKME – Smart Watch for Women, Women’s Safety with a Smart Foot Device, Mental Health Monitoring Using Sentimental Analysis, Facilitation of Multipurpose Gloves for Impaired People, Extending OVS with Deep Packet Inspection Functionalities, Courier Service Management and Tracking Using Android Application, Detecting the Abandoned Borewell Using Image Processing, Smart Hospitals E-Medico Management System, ADROIT LIMB – Brain Controlled Artificial Limb, Autonomous Movable Packrat for Habitual Chores, Postal Bag Tracking and Alerting System, Applying Social Network Aided Efficient Live Streaming System for Reducing Server Overhead, Image Fusion of MRI Images Using Discrete Wavelet Transform, Probabilistic Flooding Based File Search in Peer to Peer Network, Multi Stage for Informative Gene Selection, Mutual Information in Stages for Informative Gene Selection, Computation of Mutual Information in Stages for Gene Selection from Microarray Data, and several other impactful studies in international journals and conferences indexed in Scopus, IEEE, and UGC; she has further contributed to innovation through consultancy projects such as AI-based pre-examination dental software and non-invasive sugar detection using eye retina, authored books and chapters including Fundamentals of Machine Learning, Management Analytics and Software Engineering, Recent Trends in Engineering and Technology – Edge Computing, and secured patents like Artificial Intelligence Based Heart Rate Monitoring Device for Sports Training, IOT Based Washing Machine for Agricultural Crops, Human Identity Recognition System Using Cloud Machine Learning and Deep Learning Algorithms, Gesture Based Anti-Rape Device, while also holding active memberships with IEEE, ISTE, IEI, UACEE, IAENG, and IACSIT; her academic journey has been marked by mentorship of award-winning projects, reviewer and session chair responsibilities in international conferences, and recognition such as the Best Faculty Advisor Award demonstrating her influence in advancing technology-driven solutions for healthcare, safety, smart systems, and education through research, teaching, patents, and community engagement.

Profile: Google Scholar

Featured Publications:

Sudhan, M. B., Sinthuja, M., Pravinth Raja, S., Amutharaj, J., & Rachel, S. S. Segmentation and Classification of Glaucoma Using U‐Net with Deep Learning Model. Journal of Healthcare Engineering, 2022 (1), Article ID 1601354.

Raja, S. P., & Rachel, S. S. Women’s Safety with a Smart Foot Device. Proceedings of the 4th International Conference on Computing and Communications Technologies (ICCCT).

Raj, S. P., Kavitha, N. S., Rachel, S. S., & Suganthi, P. Smart Hospitals E-Medico Management System. International Journal of Recent Technology and Engineering, 8 (3), 4651–4655.

Rachel, S., Buvana, C., & Srinithi, S. LEARNAUT – Upgraded Learning Environment and Web Application for Autism Environment Using AR-VR. Proceedings of the 7th International Conference on Computing, Communication, Control and Automation (ICCUBEA).

Godwin, S., & Rachel, S. Mental Health Monitoring Using Sentimental Analysis. Annals of the Romanian Society for Cell Biology, 25 (5), 4397–4404.

Rachel, S. S., Azhagumeena, S., Rajakumari, S., & Madhumidha, A. Autonomous Movable Packrat for Habitual Chores. International Journal of Engineering and Technology, 429–431.

Gracia, S. V. J. B., Ponsam, J. G., Rachel, S. S., & Gayathiri, R. Software Robot for Next Generation Industries Using RPA. In Hyperautomation for Next‐Generation Industries, 35–53.

Rachel, S., Saranya, A., & Yashika, R. Automated Driving License Testing System. Proceedings of the International Conference on Power, Energy, Control and Transmission Systems (ICPECTS).

Sinthuja, M., Pravinth Raja, S., Rachel, S. S., & Suganthi, P. Vision Enhancement Using Image Processing. Grenze International Journal of Engineering & Technology (GIJET), 10.

Sinthuja, M., Buvana, C., & Srinithi, S. Trackme – Smart Watch for Women Safety. Proceedings of the International Conference on Power, Energy, Control and Transmission Systems (ICPECTS).

Rachel, S. S., & Kumar, P. Edsys: A Smart Campus Management System. Proceedings of the 1st International Conference on Computational Science and Technology (ICCST).

Rachel, S. Facilitation of Multipurpose Gloves for Impaired People. International Journal of Scientific Research in Engineering and Management, 5.

Rachel, S. S. Detecting the Abandoned Borewell Using Image Processing. Journal of Critical Review, 7 (14).

Rachel, S. S. Adroit Limb – Brain Controlled Artificial Limb. Journal of Emerging Technologies and Innovative Research, 6 (4).

Rachel, S. S. Postal Bag Tracking and Alerting System. In Proceedings of the International Conference on Knowledge Discovery and Computational Intelligence.

Rachel, S. R., & Azhagmeena, S. Image Fusion of MRI Images Using Discrete Wavelet Transform. Frontiers of Current Trends in Engineering and Technology, ISBN: 978-1537313573.

Sheeba Rachel, S., Tharunna, S. N., & Agathiya, V. K. Applying Social Network Aided Efficient Live Streaming System for Reducing Server Overhead. In Proceedings of the National Conference on Instrumentation, Electrical and Electronics Engineering (NCIEEE)

Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

Published on 08/05/202508/05/2025 by Mechanics Awards

Mr. Oussama El Othmani | Data Science and Deep Learning | Excellence in Research

Computer Engineering, Tunisia Polytechnic School, Tunisia

This individual is a promising researcher and software engineer with a strong background in computer science. Currently pursuing a PhD in ETIC at Tunisia Polytechnic School, University of Carthage La Marsa, they have a solid foundation in computer engineering from the Tunisian Military Academy. With experience as a software engineer at the Tunisian Ministry of National Defense, they have developed expertise in software development, collaboration, and problem-solving. Their research interests lie at the intersection of technology and innovation, with potential applications in various fields.

Profile

orcid

🎓 Education

– *PhD in ETIC*: Tunisia Polytechnic School, University of Carthage La Marsa, Tunis (2024 – Present)- *Computer Engineering*: Tunisian Military Academy, Fondik Jdid (2020-2023)- *Preparatory Mathematics-Physics*: Tunisian Military Academy, Fondik Jdid (2018-2020)- *Relevant Coursework*: Advanced Learning Algorithms, Artificial Intelligence, Computer Architecture, Database Management, Software Methodology, Project Management Fundamentals

👨‍🔬 Experience

– *Software Engineer*: Tunisian Ministry of National Defense (August 2023 – Present) – Participated in the full software development lifecycle – Collaborated with system engineers, hardware designers, and integration/test engineers – Developed optimized code for specific hardware platforms – Applied Agile development methodologies and object-oriented architectures

🔍 Research Interest

The individual’s research focus is not explicitly stated, but based on their education and experience, they may be interested in exploring topics related to artificial intelligence, computer architecture, and software methodology. Potential research areas could include machine learning, data science, and software engineering.

Awards and Honors🏆

No information is available on awards and honors received by the individual.

📚 Publications

Rough Set Theory and Soft Computing Methods for Building Explainable and Interpretable AI/ML Models

Développement d’un système de détection des anomalies des cellules sanguines et son utilisation en télémédecine

BloodScan

Conclusion

The candidate shows promise for the Best Researcher Award with their relevant education, professional experience, and technical skills. However, additional research experience, interdisciplinary knowledge, and a stronger publication record would significantly enhance their application. With focused effort in these areas, the candidate could become a strong contender for the award.

Wenwei Liu | Terahertz Metamaterials | Best Researcher Award

Published on 28/09/202428/09/2024 by Mechanics Awards

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

Published on 28/09/202428/09/2024 by Mechanics Awards

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

Published on 20/06/202420/06/2024 by Mechanics Awards

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