Assist. Prof. Dr. Neli Sirakova | Mathematics | Best Researcher Award |

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Assist. Prof. Dr. Neli Sirakova | Mathematics | Best Researcher Award |

Chief Assistant Professor, PhD , at Technical University of Sofia, Bulgaria.

Dr. Neli Dimitrova Sirakova is a distinguished Bulgarian mathematician and educator, currently serving as an Assistant Professor in the Department of Differential Equations at the Technical University of Sofia. With over three decades of experience in mathematics education and research, she has made significant contributions to both theoretical mathematics and its practical applications in engineering and education.

Professional Profile

Scopus 

🎓 Education 

Dr. Sirakova’s academic journey began at the Mathematical Gymnasium in Veliko Tarnovo (1979–1983). She earned her Master’s degree in Mathematics from Sofia University “St. Kliment Ohridski” (1983–1988). Her commitment to continuous learning led her to obtain additional teaching qualifications, including Fourth and Fifth Professional Qualification Degrees from the Central University for Teacher Improvement in Sofia. In 2016, she completed her Ph.D. in Mathematics at the Technical University of Sofia, focusing on boundary-value problems for nonlinear differential equations.

💼 Experience 

Dr. Sirakova’s professional career commenced as a programmer in the development of integrated circuits (1989–1991). She then transitioned into education, teaching mathematics at various institutions, including “Nikola Vaptsarov” Primary School and the High School of Mathematics and Natural Sciences “Acad. Prof. Dr. Asen Zlatarov” in Botevgrad. From 2006 to 2012, she served as a Senior Mathematics Teacher at the Professional High School of Computer Technologies and Systems in Pravets. Since 2012, she has been affiliated with the Technical University of Sofia, progressing from Assistant to Chief Assistant Professor in the Faculty of Applied Mathematics and Informatics.

🔬 Research Interests

Dr. Sirakova’s research interests lie at the intersection of pure and applied mathematics. Her work primarily focuses on boundary-value problems for nonlinear differential equations, asymptotic analysis, and mathematical modeling in engineering contexts. Additionally, she explores the pedagogical aspects of mathematics education, investigating factors influencing student motivation and competence in programming and systems programming disciplines..

Honors & Awards 

While specific awards are not listed, Dr. Sirakova’s extensive publication record and active participation in international conferences underscore her recognition in the academic community. Her contributions have been featured in proceedings of the American Institute of Physics and other reputable platforms, reflecting her esteemed status among peers.

Top Noted Publications:

Dr. Sirakova has authored and co-authored numerous scholarly works, including:

  • “Boundary-Value Problems for Almost Regular and Weakly Perturbed Nonlinear Systems”

  • “Asymptotic Expansion of Solutions for Almost Regular Nonlinear Systems”

  • “Conditionally Stable Case for Nonlinear Two-Point Boundary Value Problems with Double Singularity”

  • “Minimization of a Quadratic Objective Function with Linear Constraints by the Method of Goldfarb and Idnani”

  • Studies on electronic, distance, and blended learning methodologies during the COVID-19 pandemic

Conclusion:

Assistant Professor Dr. Neli Sirakova exemplifies a dedicated scholar and educator, seamlessly integrating rigorous mathematical research with innovative teaching practices. Her contributions have significantly advanced the understanding of complex mathematical problems and enriched the pedagogical approaches in mathematics education. Dr. Sirakova’s ongoing commitment to excellence continues to inspire both her students and the broader academic community.

Prof. Jean-pierre Michel | Health Professions | Outstanding Educator Award |

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Prof. Jean-pierre Michel | Health Professions | Outstanding Educator Award |

Director Federation of Geriatric Education , at International Association Gerontology and Geriatri, Switzerland.

Prof. Jean-Pierre Michel is a globally respected expert in geriatric medicine and aging. As an Emeritus Professor of Medicine and former Head of the Academic Geriatric Department at the University of Geneva, he has dedicated his life to advancing the science, education, and policy of aging medicine worldwide. His leadership has shaped the global landscape of gerontology, with significant contributions to research, international training programs, and institutional development. With a remarkable academic and professional legacy, Prof. Michel continues to influence the field as a thought leader, educator, and researcher.

Professional Profile

Scopus 

🎓 Education 

Prof. Michel pursued his medical education and specialization in internal medicine and geriatrics in France and Switzerland. His academic foundation in medicine was complemented by further specialization in aging-related fields, leading him to become a pioneer in interdisciplinary geriatric education and policy.

💼 Experience 

Prof. Michel served as the Head of the Academic Geriatric Department at Geneva Hospitals and Medical University. He also held honorary and adjunct professorships at Limoges University (France), Beijing University Hospital (China), and McGill University (Canada). He has been instrumental in establishing global academies dedicated to the aging population, including the European Academy for Medicine of Ageing (EAMA) and several others across Asia, the Middle East, and Latin America. As Director of the International Association of Gerontology and Geriatrics–World (IAGG-W) Federation of Geriatric Education, he currently leads the IAGG e-TRIGGER online global training program in gerontology and geriatrics.

🔬 Research Interests

Prof. Michel’s research primarily focuses on healthy aging, prevention of age-related disability, geriatric education, and global aging policy. His work spans clinical, educational, and policy-related domains, aiming to enhance the quality of life of older adults worldwide. He played a key role in the WHO’s “Aging and Life Course” program and co-authored the first WHO Global Report on Ageing and Health.

Honors & Awards 

Prof. Michel’s distinguished career has earned him numerous prestigious honors, including:

  • City of Vienna Life Achievement Award (1998)

  • China Foreign Friendship Award (2002), presented at the Great People’s Hall in Beijing

  • World Award for Global Achievement in Geriatrics (2013, IAGG World Congress, Seoul)

  • British Medical Association Book Award for the Oxford Textbook of Geriatric Medicine (2018)

He is a member of the French National Academy of Medicine, Real Academia de Medicina de España, and has served as President of the European Union Geriatric Medicine Society (EUGMS)

Top Noted Publications:

Title: The First French Fall Prevention Day for Elderly People
Authors: H. Blain, P.B. Huy, J.P. Michel, N. Durand, M. Emerriault
Citations: 0
Index/Journal: Gériatrie et Psychologie Neuropsychiatrie du Vieillissement
Year of Publication: 2025

Title: Defining the Role and Reach of a Geriatrician
Authors: M. Cesari, J. Amuthavalli Thiyagarajan, A. Cherubini, A. Banerjee, J.W. Rowe
Citations: 3
Index/Journal: Not specified
Year of Publication: Not specified

Title: Foundations and Implications of Human Aging Omics: A Framework for Identifying Cumulative Health Risks from Embryo to Senescence
Authors: X. Zheng, B. Su, Y. Zhao, J.P. Michel, R. Shao
Citations: 0
Index/Journal: Not specified
Year of Publication: Not specified

Title: Dementia, Infections and Vaccines: 30 Years of Controversy
Authors: F.B. Ecarnot, V. Boccardi, A. Calcagno, N. Veronese, S. Maggi
Citations: 14
Index/Journal: Not specified
Year of Publication: Not specified

Title: The Implications of Vaccines in Older Populations
Authors: J.P. Michel, E. Frangos
Citations: 6

Conclusion:

Prof. Jean-Pierre Michel stands as a towering figure in global geriatric medicine, combining academic excellence, international leadership, and impactful research. His lifelong commitment to promoting healthy aging and geriatric education across continents has helped shape the present and future of aging societies. He is a role model and a deserving candidate for any international recognition in research and education in the field of medicine and aging.

Dr. Abobakr Mohamed | Analytical chemistry | Best Researcher Award |

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Dr. Abobakr Mohamed | Analytical chemistry | Best Researcher Award

Fayoum University, Egypt.

Dr. Abobakr A. Mohamed is a dedicated academic and researcher in the field of analytical chemistry. Currently serving as a Lecturer at the Faculty of Pharmacy, Fayoum University, Egypt, he has made significant contributions to the development of innovative analytical methods, particularly in fluorescence-based detection techniques. His work is characterized by a commitment to enhancing the sensitivity and specificity of analytical procedures, with applications spanning pharmaceuticals, environmental monitoring, and food safety

Professional Profile

Scopus 

Google Scholar

🎓 Education 

Dr. Mohamed’s academic foundation is rooted in pharmaceutical sciences. He earned his Bachelor’s degree in Pharmaceutical Sciences from Assiut University, followed by a Master’s degree in Pharmaceutical Analytical Chemistry from Minia University. He further advanced his expertise by completing a Ph.D. in Pharmaceutical Analytical Chemistry at Minia University, where he focused on developing novel spectrofluorimetric methods for drug analysis.

💼 Experience 

Dr. Mohamed began his academic career as a research analytical chemist at the Universities of Assiut and Minia between 2010 and 2018. In 2019, he joined Fayoum University as a Lecturer in the Department of Analytical Chemistry. In this role, he has been instrumental in teaching courses such as chromatography, electrochemistry, spectroscopy, instrumental analysis, quality control of pharmaceuticals, and food analysis. His teaching is complemented by his active engagement in research and mentorship of students.

🔬 Research Interests

Dr. Mohamed’s research interests are centered on the development of sensitive and selective analytical methods for the determination of pharmaceutical compounds in various matrices. He specializes in spectrofluorimetric techniques, exploring mechanisms like photoinduced electron transfer (PET) and twisted intramolecular charge transfer (TICT) to enhance fluorescence signals. His work also encompasses environmental analysis of metals and elements, food analysis, and the design of fluorescent probes for analytical applications.

Honors & Awards 

Dr. Mohamed’s contributions to analytical chemistry have been recognized through various accolades. He has been invited to review manuscripts for esteemed journals such as the Microchemical Journal, Spectrochimica Acta Part A, Luminescence, Journal of Fluorescence, RSC Advances, and Scientific Reports. His expertise and dedication to research excellence have established him as a respected figure in his field.

Top Noted Publications:

Title: Development and validation of highly sensitive stability indicating spectrofluorimetric method for determination of amlodipine in pharmaceutical preparations and human plasma
Authors: AMI Mohamed, MA Omar, MA Hammad, AA Mohamed
Citations: 32
Journal: Journal of Fluorescence
Year: 2016

Title: Spectrofluorimetric and micelle-enhanced spectrofluorimetric methods for determination of Felodipine and Nimodipine in pharmaceutical preparations and human plasma
Authors: AMI Mohamed, MA Omar, MA Hammad, AA Mohamed
Citations: 31
Journal: Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Year: 2015

Title: Green innovative fluorescence approach for the feasible and reliable assay of thiol-containing drugs; captopril as a model
Authors: SM Derayea, DM Nagy, KMB El-Din, TZ Attia, E Samir, AA Mohamed, …
Citations: 30
Journal: RSC Advances
Year: 2022

Title: An efficient spectrofluorimetric method adopts doxazosin, terazosin and alfuzosin coupling with orthophthalaldehyde: Application in human plasma
Authors: MA Omar, AMI Mohamed, SM Derayea, MA Hammad, AA Mohamed
Citations: 27
Journal: Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Year: 2018

Title: Innovative thin-layer chromatographic method combined with fluorescence detection for specific determination of Febuxostat: Application in biological fluids
Authors: AMI Mohamed, MA Omar, SM Derayea, MA Hammad, AA Mohamed
Citations: 23
Journal: Talanta
Year: 2018

Conclusion:

Dr. Abobakr A. Mohamed demonstrates high research productivity, innovation in analytical techniques, and strong dedication to teaching and scientific collaboration. With slight improvements in international visibility and professional communication, he stands as a compelling nominee for the Best Researcher Award in his domain.

Mr. Fuhao Chang | Generative Artificial Intelligence | Best Researcher Award |

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Mr. Fuhao Chang | Generative Artificial Intelligence | Best Researcher Award

Master’s student at China Agricultural University, Beijing, China.

Mr. Fuhao Chang is a talented and rapidly emerging researcher in the field of Generative Artificial Intelligence, with a strong academic and technical foundation in computer technology and IoT engineering. Currently pursuing his Master’s degree at China Agricultural University, he is recognized for his innovative contributions to generative modeling, multimodal AI systems, and time-series simulation. With a passion for deep learning, diffusion models, and transformer architectures, Fuhao combines academic rigor with hands-on expertise, actively contributing to both research and industry-relevant AI applications.

Professional Profile

Scopus 

Google Scholar

🎓 Education 

Mr. Chang is a graduate student at China Agricultural University, a top-tier “985” institution in China, where he is pursuing a Master’s degree in Computer Technology (2023–2026). He entered the program as a recommended student (保送生), reflecting his academic excellence. Prior to this, he completed his undergraduate studies at Wuhan University of Engineering, majoring in the Internet of Things Engineering. With a GPA of 3.68/4.0, he graduated as an Outstanding Graduate within the top 5% of his class.

💼 Experience 

Fuhao gained valuable industry experience during his internship at Beijing Century Good Future Education Technology Co., Ltd., where he worked on the integration of large-scale multimodal models with Stable Diffusion for geometric image editing. His contributions included vocabulary extension of LLaVA models, fine-tuning through LoRA, and the development of bi-directional interactive modules for precise alignment between image and text features. He has also been involved in the deployment of several cutting-edge models such as LLaMA2, Qwen2-VL, SAM2, and FLUX, using multi-GPU/NPU distributed training environments.

🔬 Research Interests

Mr. Chang’s research centers on generative AI, multimodal interaction, and time-series forecasting. He has worked extensively with diffusion models, transformer-based architectures, and probabilistic forecasting techniques. A major focus of his work has been on improving the decoder and loss functions of diffusion transformers to enhance temporal dynamic simulation, integrating Fourier transforms and polynomial fitting into attention mechanisms. His innovations have led to performance improvements of over 30% in uncertainty and temporal accuracy. His recent work on stochastic weather simulation for photovoltaic integration has been well-received by top journals.

Honors & Awards 

Fuhao has earned numerous accolades at both national and provincial levels. He is a certified System Architect (高级工程师) and Software Designer, and holds CET-6 English language certification (Score: 476). His awards include the National Second Prize in the 2023 China University Digital Skills Competition, the Third Prize in the 2022 Lanqiao Cup National Software Competition, and another National Second Prize in the 2021 National University Computer Skills Challenge. He also holds more than nine provincial and five university-level honors.

Top Noted Publications:

1. Crop Pest Image Recognition Based on the Improved ViT Method
Authors: X. Fu, Q. Ma, F. Yang, C. Zhang, X. Zhao, F. Chang, L. Han
Citations: 59
Index: SCI – Information Processing in Agriculture
Year: 2024

2. Simulation and Forecasting of Fishery Weather Based on Statistical Machine Learning
Authors: X. Fu, C. Zhang, F. Chang, L. Han, X. Zhao, Z. Wang, Q. Ma
Citations: 11
Index: SCI – Information Processing in Agriculture
Year: 2024

3. Stochastic Scenario Generation Methods for Uncertainty in Wind and Photovoltaic Power Outputs: A Comprehensive Review
Authors: K. Zheng, Z. Sun, Y. Song, C. Zhang, C. Zhang, F. Chang, D. Yang, X. Fu
Citations: 1
Index: SCI – Energies
Year: 2025

4. Revolutionising Agri‐Energy: A Comprehensive Survey on the Applications of Artificial Intelligence in Agricultural Energy Internet
Authors: X. Fu, W. Ye, X. Li, X. Zeng, Y. Wang, F. Chang, J. Zhang, R. Liu
Citations: 1
Index: SCI – Energy Internet
Year: 2024

5. Knowledge-Integrated GAN Model for Stochastic Time-Series Simulation of Year-Round Weather for Photovoltaic Integration Analysis
Authors: X. Fu, F. Chang, H. Sun, P. Zhang, Y. Zhang
Citations: Not yet indexed
Index: SCI – IEEE Transactions on Power Systems
Year: 2025

Conclusion:

Mr. Fuhao Chang is a standout example of a new generation of AI researchers who blend deep technical understanding with practical, impactful innovation. His strong academic background, research achievements, and commitment to advancing AI technologies make him a worthy candidate for prestigious recognitions such as the Best Researcher Award. With continued growth in global collaboration and communication, Fuhao is poised to make significant contributions to the field of AI on both national and international stages.

KyongHo Sim | Materials Science and Technology | Best Researcher Award

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Prof. KyongHo Sim | Materials Science and Technology | Best Researcher Award

Professor at Kim Chaek University of Technology, North Korea.

Prof. Kyong Ho Sim is a materials scientist and academic at Kim Chaek University of Technology, where he has contributed to the field of advanced structural materials since 2010. His doctoral work, completed in collaboration with Harbin Institute of Technology, focused on the microstructural development and mechanical performance of ultra-high strength alloys using powder metallurgy techniques. His expertise in modeling hot deformation behavior and developing processing routes for next-generation materials places him at the forefront of metallurgical research in the region. Prof. Sim is especially known for his work on Ti₂AlNb alloys, which are key materials for aerospace and high-performance applications.

Professional Profile

Scopus 

Orcid

🎓 Education 

  • B.Sc. in Materials Science and Technology, Kim Chaek University of Technology, North Korea, 2006

  • Ph.D. in Materials Science and Engineering, Jointly pursued at Kim Chaek University of Technology and National Key Laboratory of Precision Hot Processing of Metals, Harbin Institute of Technology, China, awarded in 2022

💼 Experience 

Prof. Kyong Ho Sim has been serving as a researcher at the Faculty of Materials Science and Technology, Kim Chaek University of Technology since 2010. Over the years, he has specialized in the thermo-mechanical processing of advanced engineering materials. His academic progression culminated in the successful completion of a Ph.D. program in 2022, during which he conducted research at the prestigious Harbin Institute of Technology’s National Key Laboratory. Prof. Sim has contributed significantly to the development of ultra-fine grained materials and constitutive modeling, with a focus on titanium-based and aluminum alloys used in high-strength and high-temperature applications.

🔬 Research Interests

  • Thermo-mechanical processing of advanced engineering materials

  • Powder metallurgy of ultra-fine grained alloys

  • Hot deformation behavior of titanium alloys, ultra-high strength steels, and nickel-based superalloys

  • Spark plasma sintering and mechanical alloying

  • Constitutive modeling (Zerilli-Armstrong, Khan-Huang-Liang models)

  • Microstructural evolution and mechanical property optimization of Ti₂AlNb-based intermetallics

Author Metrics

  • Publications: Multiple articles published in SCI-indexed journals, especially in Journal of Alloys and Compounds and Vacuum

  • Citation Highlights:

    • Microstructure and mechanical properties of a Ti-22Al-25Nb alloy fabricated from elemental powders by mechanical alloying and spark plasma sintering, Journal of Alloys and Compounds, 704, 425–433 (2017)

    • Modified Zerilli-Armstrong and Khan-Huang-Liang constitutive models to predict hot deformation behavior in a powder metallurgy Ti-22Al-25Nb alloy, Vacuum, 210, 111749 (2023)

  • Areas of Impact: Powder metallurgy, thermomechanical processing, constitutive modeling, and advanced alloy design

  • Collaborations: Cross-institutional research with Harbin Institute of Technology and regional research laboratories

Top Noted Publications:

1. Modified Zerilli-Armstrong and Khan-Huang-Liang Constitutive Models to Predict Hot Deformation Behavior in a Powder Metallurgy Ti-22Al-25Nb Alloy

  • Journal: Vacuum

  • Publication Year: 2023

  • DOI: 10.1016/j.vacuum.2022.111749

  • EID (Scopus): 2-s2.0-85146430765

  • ISSN: 0042-207X

  • Authors: Sim, K.H.; Ri, Y.C.; Jo, C.H.; Kim, O.J.; Kim, R.S.; Pak, H.

  • Publisher: Elsevier

  • Abstract Summary: This study applies modified Zerilli-Armstrong and Khan-Huang-Liang models to characterize the hot deformation behavior of a Ti-22Al-25Nb alloy processed via powder metallurgy, offering accurate predictions of flow stress under various thermomechanical conditions.

2. Constitutive Modeling of a Fine-Grained Ti₂AlNb-Based Alloy Fabricated by Mechanical Alloying and Subsequent Spark Plasma Sintering

  • Journal: Advanced Engineering Materials

  • Publication Year: 2021

  • DOI: 10.1002/adem.202000987

  • EID (Scopus): 2-s2.0-85097672128

  • ISSN: 1527-2648 (Print), 1438-1656 (Online)

  • Authors: Sim, K.-H.; Li, Y.C.; Li, C.-H.; Kim, M.-O.; Kim, H.-C.

  • Publisher: Wiley-VCH

  • Abstract Summary: The article investigates the flow stress behavior and constitutive equations for a fine-grained Ti₂AlNb alloy fabricated via mechanical alloying and spark plasma sintering, contributing to its potential applications in aerospace.

3. Effect of Sb–Ba–Ce–Si–Fe Post Inoculants on Microstructural and Mechanical Properties of As-Cast Pearlitic Ductile Iron

  • Journal: Steel Research International

  • Publication Year: 2019

  • DOI: 10.1002/srin.201800530

  • EID (Scopus): 2-s2.0-85059352544

  • ISSN: 1869-344X (Print), 1611-3683 (Online)

  • Authors: Lia, B.-G.; Sim, K.-H.; Kim, R.-C.

  • Publisher: Wiley-VCH

  • Abstract Summary: This work evaluates how different post-inoculant combinations affect the microstructure and mechanical performance of as-cast pearlitic ductile iron, optimizing properties for industrial applications.

4. FE Simulation of the Influence of Roll Diameter Difference on the Plate Curvature During Hot Plate Rolling

  • Journal: Steel Research International

  • Publication Year: 2019

  • DOI: 10.1002/srin.201800007

  • EID (Scopus): 2-s2.0-85044867339

  • ISSN: 1869-344X (Print), 1611-3683 (Online)

  • Authors: Son, R.-C.; Sim, K.-H.; Sin-Ho, O.

  • Publisher: Wiley-VCH

  • Abstract Summary: Finite element simulation is used to study how differences in roll diameter influence plate curvature during hot rolling, with implications for flatness control in steel production.

5. Status of Titanium Alloy Industry for Aviation in the World and Development Strategy of Chinese Enterprises

  • Journal: DEStech Transactions on Social Science, Education and Human Science

  • Publication Date: January 22, 2019

  • DOI: 10.12783/dtssehs/emse2018/27191

  • ISSN: 2475-0042

  • Authors: Kyong-Ho Sim; Guo-feng Wang; Tae-Jong Kim

  • Publisher: DEStech Publications

  • Abstract Summary: This article provides a strategic analysis of the global titanium alloy industry for aviation, with a focus on China’s competitive development and industrial outlook.

Conclusion:

Prof. KyongHo Sim exemplifies a high-impact researcher in the field of Materials Science and Technology, with a strong academic foundation, innovative modeling work, and significant contributions to next-generation alloy development. His demonstrated expertise in ultra-fine grained materials, thermo-mechanical processing, and constitutive modeling make him an excellent nominee for the Research for Best Researcher Award.

He is particularly deserving of recognition in categories such as:

  • Advanced Alloy Research Award

  • Best Researcher in Metallurgical Engineering Award

  • Thermo-Mechanical Materials Innovation Award

  • Titanium Alloy Research Excellence Award

With minor strategic improvements in global outreach and interdisciplinary expansion, he could become a leading voice in the global materials science research landscape.

Desislava Ivanova | Quantum Computing | Best Researcher Award

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Prof. Desislava Ivanova | Quantum Computing | Best Researcher Award

Desislava Ivanova at Technical University of Sofia, Bulgaria.

Prof. Desislava Ivanova is a prominent Bulgarian computer scientist and expert in high-performance and quantum computing. As a professor and dean at the Technical University of Sofia, she has played a pivotal role in shaping the university’s research in informatics, parallel computing, and applied AI. Her academic journey is highlighted by international fellowships and research engagements in Germany, Italy, Spain, and the United States, including at Carnegie Mellon University.

Prof. Ivanova is an active member of several scientific communities, including IEEE Computer Society, Informatics Europe, and the Union of Automation and Informatics, and serves as AWS Coordinator and EuT+ Data Science Institute Coordinator for TU-Sofia. Her contributions span both foundational research and practical systems for healthcare and business informatics.

Professional Profile

Scopus 

Orcid

Google Scholar

🎓 Education 

  • Master’s Degree in Automation and Information Technologies, University of Chemical Technology and Metallurgy, Sofia, 2004

  • Ph.D. in Computer Systems, Complexes and Networks, Faculty of Computer Systems and Control, Technical University of Sofia, 2014

💼 Experience 

Prof. Desislava Ivanova has built an illustrious academic career at the Technical University of Sofia, where she currently serves as a Professor and Dean of the Faculty of Applied Mathematics and Informatics. From 2014 to 2017, she held the position of Chief Assistant Professor in the Computer Systems Department. In 2018, she was promoted to Associate Professor and later became Dean in 2019. As of 2025, she holds the title of Full Professor, demonstrating a consistent trajectory of academic leadership and excellence.

Her global academic engagement is underscored by research collaborations and specializations at prestigious institutions, including Carnegie Mellon University (USA), Technical University of Kaiserslautern (Germany), CINECA Supercomputing Center (Italy), and University of Granada (Spain).

🔬 Research Interests

  • Primary Areas:

    • High Performance Computing (HPC)

      • Supercomputer Architectures and Applications

      • System Area Networks

      • Parallel Programming and Algorithms

      • In-Situ Visualization

    • Bioinformatics

    • Machine Learning

    • Cloud Computing

    • Quantum Computing

  • Additional Areas:

    • Information Systems for Health Care and Business Management

    • Component-Based Control Systems

    • Formal Methods (Verification & Validation)

Author Metrics

  • Publications: Numerous peer-reviewed articles and technical reports in high-performance computing, parallel algorithms, and machine learning

  • Collaborations: Active international research links with top institutions across Germany, Italy, Spain, and the USA

  • Recognition:

    • DAAD Alumni

    • Member of Carnegie Mellon University’s Software Research Network

    • Recognized academic leader in HPC systems research in Eastern Europe

Top Noted Publications:

1. Ant Colony Optimization Applied for Multiple Sequence Alignment

  • Authors: S. Tsvetanov, D. Ivanova, B. Zografov

  • Journal: Biomath Communications, Volume 2, Issue 1, 2015

  • Summary: This study introduces an ant colony optimization (ACO) algorithm tailored for multiple sequence alignment (MSA) in bioinformatics. Drawing inspiration from the foraging behavior of ants, the algorithm seeks optimal alignments of biological sequences. The authors demonstrate that their ACO-based approach achieves competitive alignment quality compared to traditional MSA methods, highlighting its potential in computational biology applications.

2. Intelligent Method for Adaptive In Silico Knowledge Discovery Based on Big Genomic Data Analytics

  • Authors: Plamenka Borovska, Desislava Ivanova

  • Conference: 44th International Conference on Applications of Mathematics in Engineering and Economics (AMEE’18), AIP Conference Proceedings 2048, 2018

  • Summary: The paper presents an intelligent method for adaptive in silico knowledge discovery (KDD) leveraging big genomic data analytics, aimed at supporting precision medicine. The proposed method comprises two overlapping phases: a machine learning phase and an operational phase, both utilizing scientific analytics workflows. A software system architecture based on this method is proposed, with applicability illustrated through a conceptual model for personalized breast cancer diagnostics and therapy recommendations. The method’s effectiveness is validated through case studies involving gene finding and mutation detection.

3. In Silico Knowledge Data Discovery in the Context of IoT Ecosystem Security Issues

  • Authors: Plamenka Borovska, Desislava Ivanova

  • Conference: 46th International Conference on Applications of Mathematics in Engineering and Economics (AMEE’20), AIP Conference Proceedings 2333, 2021

  • Summary: This paper explores the application of in silico knowledge data discovery methods within the context of Internet of Things (IoT) ecosystem security. The authors discuss the integration of big data analytics and machine learning techniques to identify and mitigate security vulnerabilities in IoT systems. The study emphasizes the importance of adaptive and intelligent data analysis frameworks to enhance the resilience and security of interconnected devices and networks.

4. Hybrid Parallel Multiple Sequence Alignment Based on Artificial Bee Colony on the Supercomputer JUQUEEN

  • Authors: Plamenka Borovska, Veska Gancheva, Ivailo Georgiev, Desislava Ivanova

  • Conference: 2017 European Conference on Electrical Engineering and Computer Science (EECS)

  • Summary: The authors present a hybrid parallel implementation of multiple sequence alignment (MSA) using the Artificial Bee Colony (ABC) algorithm on the JUQUEEN supercomputer. By combining MPI and OpenMP parallelization techniques, the study achieves significant performance improvements in aligning biological sequences. The results demonstrate the scalability and efficiency of the hybrid approach, making it suitable for large-scale bioinformatics applications.

5. Usability Strategy and Guidelines for Building an Accessible Web Portal

  • Authors: Desislava Ivanova, Daniel Mitev

  • Conference: 46th International Conference on Applications of Mathematics in Engineering and Economics (AMEE’20), AIP Conference Proceedings 2333, 2021

  • Summary: This paper outlines a usability strategy for developing an accessible web portal dedicated to Bulgarian cultural and historical heritage. The strategy is grounded in the Web Content Accessibility Guidelines (WCAG) 2.0 and incorporates usability studies involving assistive technologies. The authors provide comprehensive guidelines to ensure the portal is accessible to users with disabilities, aiming to create an inclusive digital experience for all visitors.

Conclusion:

Prof. Desislava Ivanova embodies the core values of the Research for Best Researcher Award—innovation, collaboration, academic leadership, and global impact. Her work intersects quantum computing, HPC, and AI-driven bioinformatics, positioning her as a pioneer in multidisciplinary computing research.

While deeper specialization in quantum-specific publications and expanded industry outreach could further elevate her profile, her proven record of impactful, interdisciplinary work fully merits recognition through this prestigious award.

Lei Zhan | Automotive Part Lightweight Research | Best Researcher Award

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Prof. Dr. Lei Zhan | Automotive Part Lightweight Research | Best Researcher Award

Professor at Jilin Communications Polytechnic, China.

Prof. Dr. Lei Zhan is a distinguished material science and vehicle engineering expert with over two decades of experience in both academia and industry. His work focuses on the development and application of lightweight and composite materials in automotive manufacturing. Recognized for his innovation, he has earned numerous national awards and holds a robust portfolio of patents. Currently a professor at Jilin Communications Polytechnic, he continues to advance sustainable and high-performance automotive solutions through collaborative research and technology development.

Professional Profile

Scopus 

Orcid

🎓 Education 

  • Ph.D. in Material Processing Engineering, Jilin University, China (2005–2010)

  • B.Sc. in Vehicle Engineering, Lanzhou Jiaotong University, China (1997–2001)

💼 Experience 

Prof. Dr. Lei Zhan is currently a Professor at Jilin Communications Polytechnic (since January 2024), where he leads research on lightweight technologies for automotive components. From 2010 to 2023, he served as Product Director at Faway Company, contributing to product strategy, technological innovation, and advanced research on automotive components. Earlier in his career (2001–2005), he worked at CRCC as a Product Engineer, focusing on the design and development of subway vehicles.

🔬 Research Interests

  • Lightweight alloy materials for automotive applications: synthesis, microstructure control, and mechanical properties

  • Development of novel ceramic materials, intermetallics, and cermets

  • Combustion synthesis and phase evolution mechanisms in ceramic/metal composites

  • Design and integration of composite materials in automotive, aerospace, and machining systems

🏆 Honors and Recognitions

Prof. Dr. Lei Zhan’s contributions to the field have been recognized through various awards and honors:

  • First Prize, China National Innovation Method Competition (2019)

  • First Prize, Jilin Province Division of the National Innovation Method Competition (2021)

  • Second Prize, Outstanding Innovation Achievements of Employees in the Fourth Changchun City (2023)

  • May-First Labor Medal, Changchun City (2018)

  • Multiple awards for outstanding technological innovation achievements at provincial and city levels

Author Metrics

  • Publications: 21 peer-reviewed international papers

  • Intellectual Property: 80 applied patents, 69 granted

  • Notable Collaborations: NSFC, Jilin Province, Ministry of Education (China)

Top Noted Publications:

The mechanism of combustion synthesis of (TiCₓNᵧ–TiB₂)/Ni from a Ni–Ti–C–BN system

👨‍🔬 Authors:

  • Lei Zhan

  • Ping Shen

  • Qichuan Jiang

📚 Journal:

Powder Technology, 2011

📊 Citations:

17 citations (as per current database info)

🧪 Abstract (summary of study):

This study investigates the combustion synthesis mechanism for producing ceramic–metal composites of (TiCₓNᵧ–TiB₂)/Ni using a Ni–Ti–C–BN powder system. The research focuses on the reaction pathway, microstructure evolution, and phase formation. It helps clarify how the combustion reaction propagates and forms complex hard phases useful for high-performance materials, particularly for automotive and cutting tool applications.

Conclusion:

Prof. Dr. Lei Zhan is a highly qualified candidate for the Best Researcher Award in Automotive Part Lightweight Research. His sustained contributions across academia and industry, combined with innovation-driven recognition, position him as a leading force in developing sustainable automotive technologies.

With minor enhancements in international collaboration and publication strategy, his already-strong profile could evolve into global leadership in this critical research domain. His nomination is strongly recommended for the award.

Qinglei Chong | Chemistry | Innovative Research Award

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Mr. Qinglei Chong | Chemistry | Innovative Research Award

Associate Professor at Chinese Academy of Sciences, China.

Mr. Qinglei Chong is an accomplished synthetic chemist specializing in asymmetric catalysis and transition metal-based reaction methodologies. With a strong academic foundation from the Chinese Academy of Sciences and postdoctoral mentorship under China’s leading chemists, he has steadily advanced through key research roles at the Shanghai Institute of Organic Chemistry. His contributions are recognized by top-tier journals, and in 2019, he was honored as an Outstanding Postdoctoral Fellow by SIOC. Currently serving as an Associate Researcher, Mr. Chong continues to lead and collaborate on impactful research in metal-catalyzed asymmetric transformations.

Professional Profile

Scopus 

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🎓 Education 

  • 2005.9 – 2009.6: Bachelor of Science in Chemistry, Nanjing Normal University

  • 2009.9 – 2014.6: Ph.D. (Combined MSc–Ph.D. Program), Dalian Institute of Chemical Physics, Chinese Academy of Sciences

💼 Experience 

  • 2014.9 – 2016.9: Postdoctoral Researcher, Nankai University, under the mentorship of Academicians Qilin Zhou and Kuiling Ding

  • 2016.9 – 2016.12: Assistant Researcher, Shanghai Institute of Organic Chemistry (SIOC), CAS

  • 2016.12 – 2019.4: Postdoctoral Researcher, SIOC, CAS

  • 2019.4 – 2019.9: Assistant Researcher, SIOC, CAS

  • 2019.9 – Present: Associate Researcher, SIOC, CAS

🔬 Research Interests

  • Transition Metal Catalysis

  • Asymmetric Catalytic Methodologies

  • Development of Organometallic Complexes for Selective Synthesis
    Mr. Chong’s research focuses on innovating asymmetric catalytic processes utilizing transition metal catalysts to enable high-selectivity reactions in organic synthesis.

Top Noted Publications:

1. Cobalt-Catalyzed Diastereo- and Enantioselective Reductive Allyl Additions to Aldehydes with Allylic Alcohol Derivatives via Allyl Radical Intermediates

  • Journal: Journal of the American Chemical Society

  • Year: 2021

  • Volume: 143

  • Pages: 12755–12765

  • DOI: 10.1021/jacs.1c05690

  • Summary: This study presents a cobalt-catalyzed method for the diastereo- and enantioselective reductive allyl addition to aldehydes, utilizing allylic alcohol derivatives. The reaction proceeds via allyl radical intermediates, offering a novel approach to construct chiral homoallylic alcohols with high selectivity.ACS Publications+1PubMed+1

2. Chiral Cyclohexyl-Fused Spirobiindanes: Practical Synthesis, Ligand Development, and Asymmetric Catalysis

3. N-Heterocyclic Carbene–Cu-Catalyzed Enantioselective Allenyl Conjugate Addition

4. Cobalt-Catalyzed Atom-Economical, Diastereo- and Enantioselective Coupling of Aldimines and Cyclopropanols

  • Journal: Science China Chemistry

  • Year: 2021

  • Volume: 64

  • Pages: 1750–1755

  • DOI: 10.1007/s11426-021-1062-y

  • Summary: This research describes a cobalt-catalyzed coupling of aldimines and cyclopropanols, achieving high diastereo- and enantioselectivity. The reaction offers an atom-economical route to β-amino ketones, valuable intermediates in organic synthesis.SpringerLink

5. Photoredox/Cobalt-Catalyzed Chemo-, Regio-, Diastereo-, and Enantioselective Reductive Coupling of 1,1-Disubstituted Allenes and Cyclobutenes

Conclusion:

Mr. Qinglei Chong exemplifies the core criteria for the Research for Innovative Research Award in Chemistry: original, high-impact research that pushes synthetic boundaries while addressing real-world chemical challenges. His track record in asymmetric catalysis and transition metal chemistry is both robust and transformative. With growing visibility and continued excellence, he is well-positioned not only to receive the award but to be a future global leader in sustainable synthetic chemistry.

Yingxia Chen | Image processing | Best Researcher Award

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Prof. Yingxia Chen | Image processing | Best Researcher Award

Yingxia Chen at Yangtze University, China.

Prof. Yingxia Chen is a leading Chinese scholar in software engineering, specializing in machine learning and image processing. As a professor and department director, he combines academic leadership with high-impact research and mentorship of doctoral students. A prolific contributor to national scientific initiatives, he has led over 20 research projects and published extensively in top-tier SCI journals. His affiliations with IEEE and major Chinese scientific societies underscore his prominence in both national and international research communities.

Professional Profile

Orcid

🎓 Education 

Dr. Yingxia Chen earned his doctoral degree in a field aligned with computer science and engineering, with a specialization in machine learning and image processing. His academic journey laid a strong foundation for his subsequent contributions to advanced research and leadership in software engineering.

💼 Experience 

Prof. Yingxia Chen is a distinguished academic and researcher, currently serving as a Professor, Doctoral Supervisor, and Director of the Department of Software Engineering. He is a member of IEEE, China Artificial Intelligence Society, and the China Image and Graphics Society. Additionally, he is recognized as an expert in the Hubei Science and Technology Expert Database and the Jingzhou Science and Technology Expert Database.

As a leading contributor to national research, Prof. Chen has participated in four major national projects, including the 973 Project, National Natural Science Foundation Key Project, and Major Projects. He has independently led over 20 research projects and actively contributed to China’s scientific and technological innovation landscape.

Prof. Chen has also served as a reviewer for several SCI-indexed journals, maintaining a strong presence in academic peer review and quality control in scientific publishing.

🔬 Research Interests

  • Machine Learning

  • Image Processing

  • Pattern Recognition

  • Artificial Intelligence Applications

  • Computer Vision Systems

📊 Author Metrics

  • Total Publications: 40+

  • SCI-Indexed Papers: 30+

  • Research Projects Led: 20+

  • National Key Projects Participated: 4

  • Journal Reviewer Roles: Multiple SCI-indexed journals

  • Professional Affiliations: IEEE, CAIS, CIGS, Hubei and Jingzhou Tech Expert Databases

Top Noted Publications:

1. AMS: A Hyperspectral Image Classification Method based on SVM and Multi-modal Attention Network

  • Journal: Knowledge-Based Systems

  • Publication Date: February 2025

  • DOI: 10.1016/j.knosys.2025.113236

  • ISSN: 0950-7051

  • Contributors: Yingxia Chen, Zhaoheng Liu, Zeqiang Chen

  • Summary:
    This paper introduces AMS, a novel classification method for hyperspectral images that integrates Support Vector Machines (SVM) with a multi-modal attention mechanism. The approach aims to enhance the discriminative ability of spectral-spatial features in hyperspectral image (HSI) classification tasks.

2. CSLP: A Novel Pansharpening Method Based on Compressed Sensing and L-PNN

  • Journal: Information Fusion

  • Publication Date: February 6, 2025

  • DOI: 10.1016/j.inffus.2025.103002

  • ISSN: 1566-2535

  • Contributors: Yingxia Chen, Zhenglong Wan, Zeqiang Chen, Mingming Wei

  • Summary:
    The paper proposes CSLP, a new pansharpening method that utilizes Compressed Sensing (CS) techniques and Lagrangian Projected Neural Networks (L-PNN) to fuse high-resolution panchromatic and low-resolution multispectral images. The model enhances spatial and spectral fidelity for remote sensing applications.

3. A Method Based on Hybrid Cross-Multiscale Spectral-Spatial Transformer Network for Hyperspectral and Multispectral Image Fusion

  • Journal: Expert Systems with Applications

  • Publication Date: November 10, 2024

  • DOI: 10.1016/j.eswa.2024.125742

  • ISSN: 0957-4174

  • Contributors: Yingxia Chen, Mingming Wei, Yan Chen

  • Summary:
    This research develops a hybrid cross-multiscale transformer network for fusing hyperspectral and multispectral data, improving both spatial detail retention and spectral accuracy. It leverages attention-based transformer modules to capture rich multi-level dependencies across modalities.

4. MMCMOO: A Novel Multispectral Pansharpening Method

  • Journal: Mathematics

  • Publication Date: July 2024

  • DOI: 10.3390/math12142255

  • Publisher: Multidisciplinary Digital Publishing Institute (MDPI)

  • Contributors: Yingxia Chen, Yingying Xu

  • Summary:
    The MMCMOO method (Multi-scale Multichannel Mixed Optimization Objective) introduces an advanced pansharpening technique using multiscale optimization and mixed spectral-spatial objective functions. This method aims to preserve image fidelity across complex multispectral datasets.

5. DPDU-Net: Double Prior Deep Unrolling Network for Pansharpening

  • Journal: Remote Sensing

  • Publication Date: June 2024

  • DOI: 10.3390/rs16122141

  • Publisher: MDPI

  • Contributors: Yingxia Chen, Yuqi Li, Tingting Wang, Yan Chen, Faming Fang

  • Summary:
    DPDU-Net is a deep learning-based pansharpening network that incorporates double prior knowledge—spectral and spatial—to guide the deep unrolling optimization process. It achieves superior performance in resolution enhancement while minimizing distortions in remote sensing images.

Conclusion:

Prof. Yingxia Chen is a top-tier candidate for the Best Researcher Award in Image Processing. His innovative contributions, leadership roles, and deep commitment to national and academic advancement reflect the qualities of a transformative researcher. With his proven record of excellence, Prof. Chen stands out as a role model in computational imaging and AI-based visual intelligence.

Assist. Prof. Dr. Kaan Koçali | Occupational Health and Safety | Best Researcher Award |

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Assist. Prof. Dr. Kaan Koçali | Occupational Health and Safety | Best Researcher Award

Istanbul Gelisim University, Occupational Health and Safety, Turkey.

Assist. Prof. Dr. Kaan Koçali is a dynamic academic and researcher in the fields of Occupational Health and Safety, Mining Engineering, and Engineering Management. With a multidisciplinary educational background and a strong focus on applied research, he brings together legal, technical, and managerial expertise to address workplace safety and innovation in industrial systems. Dr. Koçali currently serves as a faculty member at Istanbul Gelişim University, where he actively contributes to both academia and industry through education, consultancy, and R&D projects.

Professional Profile

Scopus

Orcid

GoogleScholar

🎓 Education 

Dr. Koçali holds a Ph.D. in Occupational Health and Safety from Istanbul Aydın University (2021), where his dissertation focused on defining the legal responsibilities of permanent supervisors in mines in the context of Turkish mining and occupational safety laws, along with the development of a software-based certificate tracking system. He also holds two Master’s degrees: one in Mining Engineering (Thesis-based) from Istanbul University and another in Occupational Health and Safety (Non-thesis) from Istanbul Aydın University. Additionally, he completed undergraduate studies in Mining Engineering, Business Administration (Open Education), and Entrepreneurship at respected Turkish institutions, including Istanbul University, Anadolu University, and Istanbul Kültür University.

💼 Experience 

Dr. Koçali has held the position of Assistant Professor at Istanbul Gelişim University since 2021, teaching and conducting research in the Department of Property Protection and Security, with a specialization in Occupational Safety and Health. He has also participated in international academic mobility programs under the Erasmus+ framework, receiving training at institutions in Germany and North Macedonia. These experiences have enriched his cross-cultural and multidisciplinary research outlook. He previously served as a project leader on several nationally supported R&D initiatives under KOSGEB and TEKMER, demonstrating his leadership in both academic and industrial research.

🔬 Research Interests

Dr. Koçali’s research focuses on occupational safety regulations, mining technologies, safety system software, and industrial innovation. His doctoral work combined legal analysis with engineering software development, reflecting a unique interdisciplinary blend. He is especially interested in improving health and safety mechanisms in hazardous industries through legal compliance and technology integration. His projects often emphasize practical outcomes, such as software tools, safety machinery, and sector-specific digital platforms.

🏆 Honors & Awards

Dr. Koçali has received support from leading national programs such as KOSGEB’s R&D and Innovation Support Program, under which he led notable engineering innovation projects. His proactive participation in Erasmus+ academic mobility programs has also earned him international training credentials, highlighting his commitment to continuous development and internationalization.

Top Noted Publications:

1. Standardization of Social Security Institution’s Work Accident Indicators Between 2012–2020
Author: K. Koçali
Citations: 46
Journal: Journal of Academic Approaches, Vol. 12, No. 2, pp. 302–327
Year: 2021

2. Calculation of Occupational Accident Indicators of Türkiye
Author: K. Koçali
Citations: 17
Book: INSAC Social and Education Sciences, pp. 222–250
Year: 2021

3. Investigation of Occupational Health and Safety Culture and Practice in Open Pit Mining Enterprises with Worker Surveys
Author: K. Koçali
Citations: 14
Journal: Scientific Mining Journal, Vol. 57, No. 1, pp. 15–24
Year: 2018

4. Liability and Fault Rates in Mining Accidents
Author: K. Koçali
Citations: 13
Publisher: Nobel Publishing Bookstore
Year: 2021

5. Recommendations on Non-Conformities in Coal Mining in Light of the Şırnak Coal Mine Accident
Author: K. Koçali
Citations: 10
Conference: Türkiye 21st International Coal Congress (ICCET 2018), Proceedings Book, pp. 387–399
Year: 2018

6. How to Perform a Risk Assessment Step by Step for Occupational Health and Safety
Author: K. Koçali
Citations: 8
Journal: EURAS Journal of Engineering and Applied Sciences, Vol. 2, No. 1, pp. 1–19
Year: 2022

Conclusion:

Assist. Prof. Dr. Kaan Koçali is an interdisciplinary scholar and practitioner who combines engineering, law, and management in addressing occupational safety challenges. His research is grounded in real-world applications, and he has demonstrated strong leadership in R&D, international collaboration, and academic training. With a growing international profile and a clear vision for innovation in workplace safety, Dr. Koçali is well-positioned for greater contributions to his field and is a deserving candidate for awards and recognitions in applied research and safety engineering.