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.

Christian Caamaño Carrillo | Deep Learning | Best Researcher Award

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Dr. Christian Caamaño Carrillo | Deep Learning | Best Researcher Award

Docente Depto | Universidad del Bío-Bío | Chile

Dr. Christian Caamaño Carrillo is a Chilean statistician specializing in spatial statistics, semiparametric models, time series, and distribution theory. Currently serving as an Assistant Professor at the Department of Statistics, Universidad del Bío-Bío, Dr. Christian Caamaño Carrillo has built an extensive academic career combining advanced statistical theory with practical applications in environmental and economic data modeling. They hold a Ph.D. in Statistics from the Universidad de Valparaíso, where their research focused on modeling and estimating non-Gaussian random fields. With a strong background in both teaching and research,Dr. Christian Caamaño Carrillo has contributed to the training of future statisticians at undergraduate and graduate levels, delivering courses in geostatistics, linear models, and predictive modeling. Their work has been published in international journals, reflecting an ongoing commitment to methodological innovation and interdisciplinary collaboration. Dr. Christian Caamaño Carrillo continues to advance statistical methods for real-world data, particularly in environmental and spatial applications.

Professional Profile

Orcid

Scholar

Education

Dr. Christian Caamaño Carrillo earned their Ph.D. in Statistics from the Institute of Statistics, Universidad de Valparaíso, Chile, defending their thesis on the “Modeling and estimation of some non-Gaussian random fields” in May under the supervision of Dr. Moreno Bevilacqua and Dr. Carlo Gaetan. They completed an M.Sc. in Mathematics with a specialization in Statistics at the Universidad del Bío-Bío, with a thesis on estimating the Chilean Quarterly GDP Series, advised by Dr. Sergio Contreras. Prior to this, they qualified as a Statistical Engineer at the same institution in, with a thesis on panel data analysis applied to corporate strategies. Their academic journey began with a Bachelor’s degree in Statistics from Universidad del Bío-Bío. This robust educational background has provided them with expertise in statistical modeling, time series analysis, and spatial statistics, forming the foundation, research, and consulting activities.

Experience

Dr. Christian Caamaño Carrillo has been an Assistant Professor at the Department of Statistics, Universidad del Bío-Bío since August, where they teach and supervise both undergraduate and graduate students. From, they served as a Part-time Lecturer in the same department, delivering a wide range of courses in probability, statistical inference, and geostatistics. In parallel, they worked as a Part-time Lecturer at the Department of Mathematics and Applied Physics, Universidad Católica de la Santísima Concepción, focusing on foundational courses in statistics and probability. Their teaching portfolio spans undergraduate courses such as Linear Models, Random Variables, and Statistical Computing, as well as graduate-level instruction in Geostatistical Methods, Semiparametric Models, and Predictive Modeling. They have also contributed to specialized programs at Universidad Adolfo Ibáñez and Universidad de Valparaíso. Alongside their teaching, Dr. Christian Caamaño Carrillo maintains an active research agenda in spatial statistics and environmental data analysis.

Research Focus

Dr. Christian Caamaño Carrillo focuses on developing and applying advanced statistical methods to solve complex real-world problems. Their main research areas include spatial statistics, where they work on modeling spatial and spatio-temporal processes; semiparametric models, which offer flexible approaches for data with both structured and unstructured components; time series analysis, particularly in economic and environmental contexts; and distribution theory, addressing the properties and applications of probability distributions beyond standard Gaussian assumptions. A notable part of their work involves modeling environmental and geostatistical data using robust techniques that handle skewness and heavy-tailed behavior, such as skew-t processes. They are also engaged in methodological innovations for composite likelihood estimation and nearest-neighbor approaches in large spatial datasets. Through interdisciplinary collaborations, Dr. Christian Caamaño Carrillo applies these methods to areas such as environmental monitoring, mineral deposit modeling, and economic indicator estimation, bridging theory and practice in statistical science.

Awards and Honors

Dr. Christian Caamaño Carrillo has earned recognition in the academic community through sustained contributions to spatial statistics and applied statistical modeling. Their doctoral research on non-Gaussian random fields has been cited as a significant methodological advancement in environmental and geostatistical applications. As a faculty member, they have played a key role in developing and teaching specialized statistical courses, shaping the next generation of statisticians in Chile. They have been invited to collaborate with national and international researchers, leading to peer-reviewed publications in respected journals such as Environmetrics. Through graduate thesis supervision and involvement in interdisciplinary projects, Dr. Christian Caamaño Carrillo has contributed to advancing statistical applications in environmental sciences, mining, and economics. While formal awards were not listed, their academic trajectory demonstrates consistent professional excellence and recognition through publications, collaborations, and contributions to statistical education and methodology.

Publication Top Notes

Conclusion

Caamaño-Carrillo is a qualified and accomplished researcher, with a strong academic background, research experience, and teaching expertise. Their research areas are relevant and important in the field of statistics, and their publication record demonstrates their potential for making significant contributions to their field. With continued research and publication efforts, C. Caamaño-Carrillo has the potential to make a meaningful impact in their field and is a strong candidate for the Best Researcher Award.

Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

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Prof. Dr. Jasenka Gajdoš Kljusurić | Data Science and Deep Learning | Best Researcher Award

Prof, Faculty of Food Technology and Biotechnology at University of Zagreb, Croatia

Sylvain S. Guillou is a Full Professor of Fluid Mechanics at the University of Caen Normandy, France. He is the Director of the Applied Science Laboratory LUSAC and has over 176 publications, 38,900 reads, and 1,692 citations. His research focuses on computational physics, fluid dynamics, and geophysics, particularly in tidal turbines and marine renewable energies ¹.

Profile

orcid

🎓 Education

– *HDR – Fluid Mechanics*, University of Caen (2004-2005)- Ph.D. in Applied Mathematics – Mechanics, University of Paris Pierre & Marie Curie (1993-1996)- (link unavailable) in Dynamics of Fluids – Numerical Modeling, Ecole Centrale de Nantes (1992-1993)

👨‍🔬 Experience

– *Full Professor*, University of Caen Normandy (2017-present)- *Associate Professor*, University of Caen Normandy (2005-2017)- *Assistant Professor*, University of Caen Normandy (1999-2005)- *Post-doctoral Researcher*, University of Caen (1996-1997)

🔍 Research Interest

– *Computational Physics*: Numerical simulations of complex fluid flows- *Fluid Dynamics*: Turbulence, sediment transport, and environmental fluid mechanics- *Geophysics*: Marine renewable energies, tidal turbines, and offshore wind energies

Awards and Honors 🏆

Although specific awards and honors are not detailed, Guillou’s editorial roles and conference organization demonstrate his recognition in the field ¹ ²: – *Associate Editor*, Energies, La Houille Blanche, and International Journal for Sediment Research- *Organizer*, International Conference on Estuaries and Coasts (ICEC-2018) and other conferences

📚 Publications 

– Numerical modeling of the effect of tidal stream turbines on the hydrodynamics and the sediment transport–Application to the Alderney Race (Raz Blanchard), France 🌊
– Modelling turbulence with an Actuator Disk representing a tidal turbine 🌟
– A two-phase numerical model for suspended-sediment transport in estuaries 🌴
– Wake field study of tidal turbines under realistic flow conditions 💨
– Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio 🌊

Conclusion

Sylvain S. Guillou’s impressive research record, leadership roles, and editorial activities make him an excellent candidate for the Best Researcher Award. His contributions to computational physics, fluid dynamics, and geophysics have significantly advanced our understanding of these fields. With some potential for interdisciplinary collaborations and exploring emerging topics, Guillou is well-suited to receive this award ¹ ².

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.

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

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

Director of Research, INSERM U1194, France

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

Publication Profile

scholar

Education🎓 

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

Professional Experience💼 

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

Awards and Honors🏆 

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

Research Focus 🔬 

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

Publication  Top Notes

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

Conclusion:

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

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

 

Prof. Yang Zhao | Meteorology Artificial Intelligence | Young Scientist Award

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Prof. Yang Zhao | Meteorology Artificial Intelligenc | Young Scientist Award

Prof. Yang Zhao, Ocean University of China, China

Prof. Yang Zhao is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles:

Google scholar

Orcid

Educational Background🎓

2016.09 – 2019.06: Ph.D. in Meteorology Chinese Academy of Meteorological Sciences, China & Nanjing University of  Science & Technology, Ch Supervisor: Prof. Xiangde Xu 2013.09 – 2016.06: Master of Science in Meteorology Chinese Academy of Meteorological Sciences, China Supervisor: Prof. Xiangde Xu 2009.09 – 2013.06: Bachelor of Science in Atmospheric Science Chengdu University of  Technology, China

Honors and Major Awards🏆

Outstanding Graduate Student, Chinese Academy of Meteorological Sciences (2019)Outstanding Graduate Student, Nanjing University of  Science & Technology (2019)Presidential Scholarship, Nanjing University of Science & Technology (2018)
National Scholarship, Nanjing University of  Science & Technology (2018) First Class Scholarship for Ph.D. Student, Nanjing Universityof  Science & Technology (2018) The First Prize of Outstanding Graduate Student Award, China Meteorological Administration (2017) Excellent Organization Award of Summer School, Chinese Academy of Meteorology (2015)

🔬 Research Area: 

Synoptic-scale Atmospheric Dynamics (Jet, Front, Storm Tracks, Cyclones, Rossby waves)  Atmospheric Water Cycle (Moisture sources, Moisture channel, Atmospheric Rivers) Machine Learning and Deep Learning (Atmospheric Rivers) Climate Dynamics; Future precipitation prediction (ENSO-Volcano; CMIP6)

📖 Publications  Top Note :

The third atmospheric scientific experiment for understanding the earth–atmosphere coupled system over the Tibetan Plateau and its effects

Authors: P Zhao, X Xu, F Chen, X Guo, X Zheng, L Liu, Y Hong, Y Li, Z La, H Peng, …

Bulletin of the American Meteorological Society, 99(4), 757-776, 2018

Spatiotemporal variation in the impact of meteorological conditions on PM2.5 pollution in China from 2000 to 2017

Authors: Yanlin Xu, Wenbo Xue, Yi Lei, Qing Huang, Yang Zhao, Shuiyuan Cheng, Zhenhai …

Atmospheric Environment, 77, 2020

Impact of Meteorological Conditions on PM2.5 Pollution in China during Winter

Authors: Y Xu, W Xue, Y Lei, Y Zhao, S Cheng, Z Ren, Q Huang

Atmosphere, 9(11), 429, 2018

Effect of the Asian Water Tower over the Qinghai-Tibet Plateau and the characteristics of atmospheric water circulation

Authors: X Xu, L Dong, Y Zhao, Y Wang

Chin. Sci. Bull, 64(27), 2830-2841, 2019

Vertical structures of dust aerosols over East Asia based on CALIPSO retrievals

Authors: D Liu, T Zhao, R Boiyo, S Chen, Z Lu, Y Wu, Y Zhao

Remote Sensing, 11(6), 701, 2019

Trends in observed mean and extreme precipitation within the Yellow River Basin, China

Authors: Y Zhao, X Xu, W Huang, Y Wang, Y Xu, H Chen, Z Kang

Theoretical and applied climatology, 136, 1387-1396, 2019

Enhancement of the summer extreme precipitation over North China by interactions between moisture convergence and topographic settings

Authors: Yang Zhao, Deliang Chen, Jiao Li, Dandan Chen, Yi Chang, Juan Li, Rui Qin

Climate Dynamics, 38, 2020

Extreme precipitation events in East China and associated moisture transport pathways

Authors: Y Zhao, XD Xu, TL Zhao, HX Xu, F Mao, H Sun, YH Wang

Science China Earth Sciences, 59, 1854-1872, 2016

The large‐scale circulation patterns responsible for extreme precipitation over the North China plain in midsummer

Authors: Y Zhao, X Xu, J Li, R Zhang, Y Kang, W Huang, Y Xia, D Liu, X Sun

Journal of Geophysical Research: Atmospheres, 124(23), 12794-12809, 2019

Are precipitation anomalies associated with aerosol variations over eastern China?

Authors: X Xu, X Guo, T Zhao, X An, Y Zhao, J Quan, F Mao, Y Gao, X Cheng, …

Atmospheric Chemistry and Physics, 17(12), 8011-8019, 2017