Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

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Dr. Ehsan Adibnia | Computer Science | Editorial Board Member

University of Sistan and Baluchestan | Iran

Dr. Ehsan Adibnia is a dedicated researcher in Electrical Engineering with a strong interdisciplinary focus spanning artificial intelligence, machine learning, deep learning, nanophotonics, optics, plasmonics, and photonic device engineering. His research primarily explores the integration of AI-driven approaches in nanophotonic design, optical switching, and biosensing applications, enabling significant advancements in optical computing and sensing technologies. He has made notable contributions to the fields of photonics and deep learning-based optical system design through innovative studies on inverse design, nonlinear plasmonic structures, and photonic crystal encoders. His expertise extends to advanced simulation tools such as Lumerical, COMSOL, and RSoft, as well as programming in MATLAB and Python for modeling and data analysis. Dr. Adibnia has actively contributed to scientific research through multiple peer-reviewed publications in prestigious international journals. According to Google Scholar, he has accumulated 6,540 citations, an h-index of 45, and an i10-index of 156, reflecting his significant academic influence. His Scopus profile records 70 citations across 53 documents with an h-index of 5, highlighting his growing global research impact.

Profiles

Scopus | ORCID | Google Scholar

Featured Publications

Adibnia, E., Mansouri-Birjandi, M. A., & Ghadrdan, M. (2024). A deep learning method for empirical spectral prediction and inverse design of all-optical nonlinear plasmonic ring resonator switches. Scientific Reports, 14, 5787.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2024). Nanophotonic structure inverse design for switching application using deep learning. Scientific Reports, 14, 21094.

Adibnia, E., Ghadrdan, M., & Mansouri-Birjandi, M. A. (2025). Chirped apodized fiber Bragg gratings inverse design via deep learning. Optics & Laser Technology, 181, 111766.

Jafari, B., Gholizadeh, E., Jafari, B., & Adibnia, E. (2023). Highly sensitive label-free biosensor: graphene/CaF2 multilayer for gas, cancer, virus, and diabetes detection. Scientific Reports, 13, 16184.

Soroosh, M., Al-Shammri, F. K., Maleki, M. J., Balaji, V. R., & Adibnia, E. (2025). A compact and fast resonant cavity-based encoder in photonic crystal platform. Crystals, 15, 24.

Dr. Yonglin Ren | Computer Science | Innovative Research Award

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Dr. Yonglin Ren | Computer Science | Innovative Research Award

Senior Project Engineer & Researcher | Concordia University | Canada

Dr. Yonglin Ren is a distinguished Senior Project Engineer and Researcher at Concordia University, recognized for his interdisciplinary expertise in mathematical modeling, logistics optimization, and sustainable engineering systems. His research bridges theoretical optimization frameworks and industrial applications, focusing on metaheuristic algorithms, CAD/CAE-based modeling, and supply chain design for humanitarian and sustainable logistics. Dr. Ren’s contributions have advanced methodologies for capacitated location allocation problems, high-speed rail freight transport, and dynamic mechanical system modeling. His work integrates computational intelligence with real-world challenges in water resource management, transportation networks, and crisis logistics, making a significant impact in both academia and industry. His publications are widely cited, reflecting his influence in the fields of operational research and applied optimization, with a Scopus record of 3 indexed documents, 6 citations, and an h-index of 1, alongside a Google Scholar citation count of 26. Dr. Ren has collaborated on multiple international engineering and research projects, driving innovations that contribute to sustainable development and global resource optimization.

Profile

Scopus

Featured Publications 

Ren, Y., & Awasthi, A. (2014). Investigating metaheuristics applications for capacitated location allocation problem on logistics networks. Chaos Modeling and Control Systems Design, 213–238.

Ren, Y., & Awasthi, A. (2012). Location allocation planning of logistics depots using genetic algorithm. Research in Logistics & Production, 2, 247–257.

Ren, Y. (2011). Metaheuristics for multiobjective capacitated location allocation on logistics networks. Concordia University.

Ren, Y., Hajiebrahimi, S., Azad, M., Awasthi, A., & Salah, S. (2020). Humanitarian aid for Wuhan with crisis logistics management approach. Proceedings of the International Conference on Industrial Engineering and Operations Management.

Ren, Y., & Awasthi, A. (2025). Logistics hub location for high-speed rail freight transport—Case Ottawa–Quebec City corridor. Logistics, 9(4), 158.

Dr. Han Zhang | Computer Science | Best Researcher Award

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Han Zhang | Computer Science | Best Researcher Award

Research Institute of Petroleum Exploration and Development, China

Dr. Han Zhang is a young and dedicated researcher at the China National Petroleum Corporation Research Institute of Petroleum Exploration and Production, where he focuses on advancing intelligent reservoir development and optimization for the future of the energy industry. With a strong educational foundation, he earned his bachelor’s degree in Marine Oil and Gas Engineering from a prestigious petroleum university in China, majoring in reservoir and oil production engineering, before continuing his master’s and doctoral studies in Oil and Gas Field Development Engineering at the same institute. His research centers on the development of advanced mathematical and numerical models that address key challenges in petroleum engineering, particularly intelligent reservoir management. Dr. Zhang has contributed to one national-level and one provincial-level research project and has also taken part in an industry consultancy project, demonstrating his ability to bridge academic research with practical applications. He has published peer-reviewed articles, including a notable study on gated recurrent unit-based dynamic characterization methods for horizontal wells in carbonate reservoirs, as well as a paper on closed-loop optimization systems for evaluating development potential with water-alternating gas flooding. With three patents under process and active membership in the Society of Petroleum Engineers, Dr. Zhang has positioned himself as a rising scholar committed to innovation. His contributions include refining the analytic hierarchy process through coupling with entropy weight methods for more objective production evaluation, as well as pioneering predictive models that enhance reservoir characterization. He aspires to continue developing transformative technologies that promote efficiency, sustainability, and innovation in petroleum exploration and production.

Profile: ORCID 

Featured Publications

Zhang, H. (2025). A closed-loop optimization system for evaluating the development effect and potential of producers with water alternating gas flooding. Processes.

Zhang, H. (2025). A dynamic characterization method for horizontal wells based on the gated recurrent unit: A case study of a carbonate reservoir in the Middle East. In Springer Series in Geomechanics and Geoengineering. Springer.

Yansheng Wu | Computer Science | Best Researcher Award

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Dr. Yansheng Wu | Computer Science | Best Researcher Award

Associate Professor, Nanjing University of Posts and Telecommunications, China

Dr. Yansheng Wu is a distinguished researcher and Associate Professor at the School of Computer Science, Nanjing University of Posts and Telecommunications, China. With a strong background in Pure Mathematics, his expertise lies in Finite Fields, Cryptography, and Coding Theory. He has made significant contributions to algebraic coding theory and applications of algebra in cryptographic systems. Dr. Wu has held esteemed positions as a Postdoctoral Research Fellow at Ewha Womans University and a Visiting Scholar at the Hong Kong University of Science and Technology. His scholarly work is widely recognized, with numerous publications in prestigious journals such as IEEE Transactions on Information Theory and Finite Fields and Their Applications. In addition to his research, he actively contributes as a reviewer for multiple high-impact journals, making him a key figure in the field of applied mathematics and cryptography. 📚✨

Publication Profile

🎓 Education

Dr. Yansheng Wu holds a Ph.D. in Pure Mathematics from Nanjing University of Aeronautics and Astronautics (2019), where he focused on algebra and number theory applications in coding theory. He earned his MSc in Pure Mathematics from Guangxi Teachers Education University (2016), working on matrix rings and finite group rings. His academic journey began with a BSc in Mathematics and Applied Mathematics from Anhui Normal University (2013), where he explored number partitions. His rigorous training in algebra, number theory, and their cryptographic applications has shaped his prolific research career. 🎓🔢

💼 Experience

Dr. Wu’s professional journey includes serving as an Associate Professor at Nanjing University of Posts and Telecommunications since 2020. Prior to that, he completed a postdoctoral fellowship at Ewha Womans University, South Korea, where he collaborated on advanced research in finite fields. His academic engagements also include a visiting scholar position at the Hong Kong University of Science and Technology in 2023-2024, enhancing international collaborations in cryptography and coding theory. He has participated in prestigious research forums, including the East Asian Core Doctoral Forum at The University of Tokyo. 🌍📊

🏆 Awards and Honors

Dr. Wu has secured multiple prestigious research grants, including the National Natural Science Foundation of China (2022-2024) and the Talent Introduction Fund at Nanjing University of Posts and Telecommunications (2021-2023). His research excellence is also recognized through editorial board memberships at leading journals like AIMS Mathematics and numerous reviewing roles for top-tier mathematical and cryptographic journals, including IEEE Transactions on Information Theory and Finite Fields and Their Applications. 🏅🔬

🔬 Research Focus

Dr. Wu’s research interests span Finite Fields, Coding Theory, Cryptography, and Algebraic Structures. His work explores the design and analysis of linear codes, algebraic cryptosystems, and combinatorial structures over finite fields. He has extensively studied the properties of MDS codes, Reed-Solomon codes, and quaternary codes, contributing novel constructions with optimal parameters. His interdisciplinary approach integrates number theory with applied cryptography, making his research pivotal in modern data security and error correction. 🔢🛡️

🔚 Conclusion

Dr. Yansheng Wu is a leading figure in the field of mathematics, cryptography, and coding theory. His contributions to algebraic coding, finite fields, and cryptographic structures have significantly impacted secure communications and data integrity. Through his research, editorial roles, and academic collaborations, he continues to shape the future of cryptographic mathematics, making lasting contributions to theoretical and applied aspects of the discipline. 🚀🔢

📚 Publications

Two classes of twisted generalized Reed-Solomon codes with two twists. Finite Fields and Their Applications, 104, 102595. [Cited by: TBD] 🔗 Link

When Does the Extended Code of an MDS Code Remain MDS? IEEE Transactions on Information Theory, 71(1), 263-272. [Cited by: TBD] 🔗 Link

Two classes of narrow-sense BCH codes and their duals. IEEE Transactions on Information Theory, 70(1), 131-144. [Cited by: TBD] 🔗 Link

Linear Complementary Dual Codes Constructed from Reinforcement Learning. Journal of System Science and Complexity. [Cited by: TBD] 🔗 Link

Two families of linear codes with desirable properties from some functions over finite fields. IEEE Transactions on Information Theory, 70(11), 8320-8342. [Cited by: TBD] 🔗 Link

Optimal few-weight codes and their subfield codes. Journal of Algebra and Its Applications, 23(4), 2450248. [Cited by: TBD] 🔗 Link

Two Infinite Families of Quaternary Codes. IEEE Transactions on Information Theory, 70(12), 8723-8733. [Cited by: TBD] 🔗 Link

Quaternary codes and their binary images. IEEE Transactions on Information Theory, 70(7), 4759-4768. [Cited by: TBD] 🔗 Link

 

Leyi Zhao | Computer Science | Best Researcher Award

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Dr. Leyi Zhao | Computer Science | Best Researcher Award

Doctor, Beijing University of Chinese Medicine, China

Dr. Leyi Zhao is a dedicated clinical doctoral researcher in Integrative Medicine at the prestigious Beijing University of Chinese Medicine. With a keen interest in digestive tract diseases, Dr. Zhao specializes in studying precancerous lesions, tumors, and the intricate relationship between the immune environment and disease progression. Passionate about blending traditional medicine with modern computational techniques, Dr. Zhao integrates computer language and data analysis to establish innovative prognostic models, enhancing clinical applications. With multiple completed and ongoing research projects, Dr. Zhao’s contributions to the field of immunotherapy and colorectal cancer prognosis are highly impactful.

Publication Profile

ORCID

🎓 Education

Dr. Zhao is currently pursuing a doctorate in Integrative Medicine at Beijing University of Chinese Medicine, a renowned institution for traditional and modern medical research. This academic journey has equipped Dr. Zhao with a strong foundation in both traditional Chinese medical practices and cutting-edge clinical research methodologies.

💼 Experience

With extensive research experience, Dr. Zhao has led and contributed to multiple research projects focusing on colorectal cancer, immune microenvironments, and predictive modeling in oncology. Through a blend of experimental studies and computational approaches, Dr. Zhao has contributed significantly to understanding the impact of tertiary lymphoid structures (TLS) on tumor prognosis and immune response. In addition to academic research, Dr. Zhao has been involved in consultancy and industry-based projects, furthering the practical application of scientific findings.

🏆 Awards and Honors

Dr. Zhao’s research excellence has been recognized through publications in high-impact journals indexed in SCI and Scopus. The innovative work in colorectal cancer prognosis and immunotherapy has garnered citations and recognition within the scientific community. As an active contributor to the field, Dr. Zhao has been nominated for the prestigious Best Researcher Award at the Cryogenicist Global Awards.

🔬 Research Focus

Dr. Zhao’s primary research focus lies in immunotherapy for tumors, particularly in colorectal cancer. The groundbreaking research involves developing a TLS-based prognostic model that explores immune cell interactions within tumors. This model holds potential for predicting patient prognosis and treatment responsiveness, offering valuable insights into personalized medicine. Furthermore, Dr. Zhao’s interdisciplinary approach integrates network pharmacology, computational modeling, and traditional Chinese medicine, enhancing the precision and effectiveness of cancer treatments.

🔗 Publications

The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer. Biomedicines, 2025; 13(3):539
🔗 DOI: 10.3390/biomedicines13030539

 Limonin ameliorates indomethacin-induced intestinal damage and ulcers through Nrf2/ARE pathway. Immun Inflamm Dis, 2023; 11(2):e787
🔗 DOI: 10.1002/iid3.787

Chinese patent herbal medicine (Shufeng Jiedu capsule) for acute upper respiratory tract infections: A systematic review and meta-analysis. Integr Med Res, 2021; 10(3):100726
🔗 DOI: 10.1016/j.imr.2021.100726

Deciphering the Mechanism of Siwu Decoction Inhibiting Liver Metastasis by Integrating Network Pharmacology and In Vivo Experimental Validation. Integr Cancer Ther, 2024; 23:15347354241236205
🔗 DOI: 10.1177/15347354241236205

🔚 Conclusion

Dr. Leyi Zhao’s research contributions are shaping the future of colorectal cancer treatment and immune microenvironment analysis. With a strong foundation in integrative medicine and a passion for computational research, Dr. Zhao continues to push the boundaries of medical science, making a profound impact on oncology and personalized medicine. As a nominee for the Best Researcher Award, Dr. Zhao’s work exemplifies innovation, dedication, and a commitment to improving patient outcomes worldwide. 🌍

mourad JABRANE | Computer Science | Best Researcher Award

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Prof Dr. mourad JABRANE | Computer Science | Best Researcher Award

software enginee, sultan moulay slimane university, Morocco

JABRANE Mourad is a state-certified software engineer and a third-year Ph.D. candidate at the National School of Applied Sciences, Sultan Moulay Slimane University. With a passion for designing scalable and efficient systems, Mourad excels in data mining, machine learning, and distributed computing. As an adjunct professor, he effectively conveys complex concepts, making him a valuable contributor to both academia and industry.

Publication Profile

Strengths for the Award:

  1. Solid Academic Background: Jabrane Mourad holds a state-certified software engineering degree and is currently a Ph.D. candidate specializing in Big Data, showcasing a strong academic foundation in cutting-edge technologies.
  2. Research Contributions: His research work focuses on significant areas like entity resolution in Big Data, machine learning, and distributed computing. His publications in reputable journals, such as the Journal of Intelligent Information Systems and Information Systems, highlight his contributions to the field.
  3. Diverse Skill Set: Mourad has extensive expertise in programming languages (Java, Python, JavaScript, etc.), frameworks (Spring, Angular), and software engineering tools (Docker, Jenkins, Kubernetes), making him a well-rounded researcher with practical skills applicable to various domains.
  4. Teaching Experience: As an adjunct professor, Mourad has taught a wide range of subjects including data integration, advanced Java Enterprise Edition, and distributed systems. His teaching experience demonstrates his ability to communicate complex concepts clearly, which is a valuable trait in academia.
  5. International Recognition: The publication of his work in international journals and his participation in global research projects suggest that his research has gained international recognition, making him a strong candidate for the award.

Areas for Improvement:

  1. Broader Impact: While Mourad’s research contributions are significant, further efforts to collaborate on interdisciplinary projects or engage in community outreach could broaden the impact of his work.
  2. Innovation and Patents: Although he has a strong publication record, obtaining patents or developing innovative software solutions could further strengthen his candidacy for a best researcher award.
  3. Networking and Collaborations: Expanding his network and collaborating with more researchers across different institutions could help him gain more visibility and access to diverse research opportunities.

Education

Ph.D. Candidate (2021 – Present): National School of Applied Sciences, Sultan Moulay Slimane University.
Thesis title: Entity Resolution in Big Data. State Software Engineer (2018 – 2021): National School of Applied Sciences, Sultan Moulay Slimane University. MP Higher School Preparatory Classes (2016 – 2018): Centre Ibn Abdoun.
Track title: Mathematics, Physics, and Engineering Sciences.

Experience 💼

JABRANE Mourad has accumulated significant experience as an adjunct professor at the National School of Applied Sciences, where he has taught a variety of subjects including Data Integration, Data Quality, Advanced JEE, Distributed Systems, Python Programming, MATLAB, and C Programming. His roles extend to both regular courses and continuing education programs, demonstrating his versatility and commitment to teaching.

Research Focus 🔬

Mourad’s research is centered around big data, with specific interests in data mining, machine learning, and distributed computing. His Ph.D. work focuses on Entity Resolution in Big Data, where he is exploring innovative approaches to improve accuracy and efficiency in large-scale data matching.

Awards and Honors 🏅

Though the detailed awards and honors list is not provided, Mourad’s academic and professional journey is marked by his selection as a Ph.D. candidate and his appointment as an adjunct professor at a prestigious institution.

Publications 📚

Mourad has contributed extensively to the field of big data and machine learning. Below are some of his notable publications:

  1. “Erabqs: Entity resolution based on active machine learning and balancing query strategy” – Published in Journal of Intelligent Information Systems, March 2024. Cited by 3 articles.
  2. “Enhancing entity resolution with a hybrid active machine learning framework: Strategies for optimal learning in sparse datasets” – Published in Information Systems, November 2024. Cited by 7 articles.
  3. “Enhancing semantic web entity matching process using transformer neural networks and pre-trained language models” – Published in Computing and Informatics, 2024. Cited by 5 articles.
  4. “Sentiment analysis dataset in Moroccan dialect: Bridging the gap between Arabic and Latin scripted dialect” – Published in Language Resources and Evaluation, July 2024. Cited by 4 articles.

 

Conclusion:

Jabrane Mourad presents a strong case for the Best Researcher Award due to his solid academic background, notable research contributions in Big Data and machine learning, and diverse technical skills. His role as an adjunct professor and his extensive teaching experience further emphasize his ability to convey knowledge and contribute to the academic community. To enhance his candidacy, Mourad could focus on increasing the broader impact of his research through interdisciplinary collaborations and innovation. Overall, Mourad is a well-rounded candidate with the potential to make substantial contributions to the field, making him a suitable contender for the award.