Yanxia Jin | Genetics | Best Scholar Award

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Yanxia Jin | Genetics | Best Scholar Award

Associate Professor at Hubei Normal University, China.

Dr. Yanxia Jin is a distinguished associate professor at Hubei Normal University, specializing in biomedical sciences, particularly in cancer treatment and tumorigenesis. Known for her dedication to both research and teaching, she actively mentors graduate students, fostering their growth in life sciences. Her work has received significant recognition through various prestigious awards and honors. Dr. Jin has contributed extensively to the field with over 38 SCI-indexed publications, including numerous first-author and corresponding author roles. Her leadership in high-impact research and commitment to academic excellence make her a valuable asset to the scientific and academic communities.

Publication Profile

Scopus

Educational Background

Dr. Jin has a robust academic foundation in biomedical sciences, which she has furthered through postdoctoral research at prominent institutions. Her postdoctoral studies at Zhongnan Hospital of Wuhan University and Hong Kong Baptist University allowed her to specialize in clinical medicine and traditional Chinese pharmacy. Her educational background has equipped her with a unique blend of interdisciplinary knowledge that she has applied throughout her research and teaching career. This solid academic and research training has set the groundwork for her impactful contributions to cancer research and the life sciences.

Experience

With years of experience as an academic mentor and researcher, Dr. Jin has become a pivotal figure at Hubei Normal University. She has not only led critical projects as Principal Investigator but also collaborated on nationally funded initiatives, such as those supported by the National Natural Science Foundation of China (NSFC) and the Hubei Province Natural Science Foundation. Her experience spans research project management, scientific publication, and graduate mentorship. Her work has established her as a leading expert in her field, contributing to advancements in cancer treatment and biomedical sciences.

Research Focus

Dr. Jin’s research focuses on understanding tumorigenesis and developing innovative cancer treatment approaches. Her work with selenium nanocomposites, biomarker identification, and anti-tumor compounds has shown promise in targeting lung cancer and leukemia. This specialization in molecular oncology and nanomedicine underlines her commitment to addressing pressing health challenges. Dr. Jin’s studies are driven by a goal to translate foundational research into clinical applications, reflecting her dedication to advancing treatment options and improving patient outcomes in oncology.

Awards and honors

Dr. Jin has received several notable awards, including recognition as both a Chutian Scholar and a Hong Kong Scholar, celebrating her contributions to biomedical research and education. Her accomplishments are further highlighted by her leadership in prestigious research projects funded by major foundations. These accolades underscore her dedication to her field and her impact on cancer research and biomedical sciences. Dr. Jin’s honors not only mark her as a researcher of high repute but also as a dedicated educator who inspires the next generation of scientists.

Conclusion

Dr. Yanxia Jin’s exemplary achievements, including her high-impact research, significant grant funding, and dedication to mentorship, make her an exceptional candidate for the Best Scholar Award. Her work on innovative cancer treatments and biomarkers exemplifies her commitment to addressing complex health challenges. With her ongoing dedication to expanding her research and mentorship, Dr. Jin is well-suited to receive this award, embodying both excellence in scholarship and significant contributions to the field of life sciences.

Publication Top Notes

Title: A novel selenium nanocomposite modified by AANL inhibits tumor growth by upregulating CLK2 in lung cancer
Authors: Zhang, Y., Chen, Y., Wang, B., Pan, J., Jin, Y.
Year: 2024
Citations: 0

Title: A diagnostic biomarker of acid glycoprotein 1 for distinguishing malignant from benign pulmonary lesions
Authors: Chen, Y., Zhang, Y., Huang, A., Pan, J., Jin, Y.
Year: 2023
Citations: 0

Title: Preparation and usage of nanomaterials in biomedicine
Authors: Zhang, Y., Ai, L., Gong, Y., Jin, Y.
Year: 2023
Citations: 3

Title: Overexpression of SERPINA3 suppresses tumor progression by modulating SPOP/NF-κB in lung cancer
Authors: Jin, Y., Zhang, Y., Huang, A., Wang, W., Pan, J.
Year: 2023
Citations: 3

Title: Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases
Authors: Jin, Y., Wang, W., Wang, Q., Raza, U., Gong, Y.
Year: 2022
Citations: 27

Title: Evaluation of prognostic staging systems of multiple myeloma in the era of novel agents
Authors: Shang, Y., Jin, Y., Liu, H., Hu, J., Zhou, F.
Year: 2022
Citations: 2

Title: Therapeutic Plateletpheresis in Patients With Thrombocytosis: Gender, Hemoglobin Before Apheresis Significantly Affect Collection Efficiency
Authors: Jiang, H., Jin, Y., Shang, Y., Gong, F., Zhou, F.
Year: 2021
Citations: 3

Title: Synergistic effects of AAGL and anti-PD-1 on hepatocellular carcinoma through lymphocyte recruitment to the liver
Authors: Ye, X., Wang, X., Yu, W., Xu, B., Sun, H.
Year: 2021
Citations: 4

Title: Shengxuening Extracted from Silkworm Excrement Mitigates Myelosuppression via SCF-Mediated JAK2/STAT3 Signaling
Authors: Ding, L., Tan, Y., Xu, L., Huang, T., Zhou, F.
Year: 2021
Citations: 8

salma ayari | Marketing | Best Researcher Award

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salma ayari | Marketing | Best Researcher Award

ESCT at University of Tunis, Tunisia.

Salma Ayari is a Tunisian marketing expert specializing in digital marketing strategies and communication. With a career built on both academia and practical engagement, she brings innovative insights to the field. She has cultivated exceptional communication skills, conveying complex information effectively through her teaching and research roles. Known for her diligence, creativity, and adaptability, Ayari has a proven ability to handle high-pressure environments and diverse settings. Her commitment to continuous learning, combined with her advanced skills in time management, teamwork, and organization, underscores her qualifications for advanced marketing research and education in Tunisia and beyond.

Publication Profile

Scopus

Educational Background

Salma Ayari holds a Ph.D. in Marketing from Ecole Supérieure de Commerce de Tunis, University of Manouba, Tunisia. Her doctoral thesis, defended in 2020, investigates the influence of mental imagery on consumer engagement in online environments, earning a “Very Honorable” mention. She also completed her Master’s in Marketing Research at the same institution in 2014, focusing on mental imagery’s impact on consumer attitudes. Additionally, she earned a Bachelor’s degree in Applied Economics, specializing in International Finance, with honors in 2010, and earlier, a Bachelor’s in Economics and Management in 2006 from Ibn Abi Dhief High School.

Experience

Ayari has extensive teaching experience as a contractual assistant across various Tunisian universities, including the University of Tunis El Manar, University of Jendouba, and ESCT. Since 2017, she has taught a range of marketing courses, including digital marketing, product management, and service marketing. Her roles have also included curriculum design and supervision of final-year undergraduate marketing students, guiding them on topics like digital strategies, e-commerce, and the impact of social media on customer behavior. This blend of teaching, practical assignments, and student mentorship showcases her dedication to advancing marketing education and research.

Research Focus

Ayari’s research centers on the evolving digital marketing landscape, with particular emphasis on consumer engagement through online platforms, customer relationship management (CRM), and social media. Her work explores how mental imagery impacts user interactions on digital platforms and has further extended into areas like interactive and social media marketing, online advertising, and CRM applications. She has also supervised research on contemporary topics such as AI’s role in marketing, e-banking services, and the influence of social media influencers, demonstrating her commitment to investigating the intersection of digital technology and consumer psychology.

Awards and honors

The information provided does not list specific awards or honors that Salma Ayari has received. However, her academic achievements, such as receiving a “Very Honorable” mention for her Ph.D. thesis in marketing, signify recognition of her scholarly excellence within her institution. Additionally, her sustained roles as a contractual assistant across multiple universities, along with her mentorship of students in complex, modern marketing topics, reflect her professional credibility and dedication, which might have earned her informal honors within the academic and research communities.

Conclusion

Dr. Salma Ayari presents a strong case for the Best Researcher Award in her field, especially given her specialization in digital marketing, her dedication to student mentorship, and her academic teaching experience. Her research is timely and applicable, which is essential for impactful contributions in marketing. Focusing on strengthening her publication portfolio and international presence would further solidify her standing and enhance her visibility in the field.

Publication Top Notes

    • “Muslims’ reluctance to social media campaigns about organ donation: an exploratory study”
      • Authors: Nouira, O., Ayari, S.
      • Journal: Journal of Islamic Marketing
      • Year: 2024
      • Volume/Issue/Pages: 15(7), pp. 1706–1721
      • Citations: 0
    • “Understanding the dynamics of unfollowing behaviour on TikTok: implications for interactive marketing”
      • Authors: Ayari, S., Nouira, O., Oueslati, K.
      • Journal: Journal of Decision Systems
      • Year: 2024
      • Citations: 0
    • “A Bibliometric Analysis on Artificial Intelligence in Marketing: Implications for Scholars and Managers”
      • Authors: Oueslati, K., Ayari, S.
      • Journal: Journal of Internet Commerce
      • Year: 2024
      • Volume/Issue/Pages: 23(3), pp. 233–261
      • Citations: 1
    • “Exploring the causes to unfollow social media influencers: A qualitative study”
      • Authors: Ayari, S., Oueslati, K., Ben Yahia, I.
      • Journal: Journal of Human Behavior in the Social Environment
      • Year: 2024
      • Citations: 2
    • “Proposal of a Measurement Scale and Test of the Impacts on Purchase and Revisit Intention”
      • Authors: Ayari, S., Yahia, I.B.
      • Journal: Journal of Telecommunications and the Digital Economy
      • Year: 2023
      • Volume/Issue/Pages: 11(3), pp. 1–18
      • Citations: 0
    • “Impacts of immersion on loyalty to guesthouse websites: The simultaneous effect of 3d decor and avatars in a hyper-real environment”
      • Authors: Ayari, S., Ben Yahia, I.
      • Journal: Journal of Marketing Communications
      • Year: 2023
      • Citations: 2
    • “Measuring E-Browsing Behaviour and Testing its Impact on Online Immersion”
      • Authors: Ayari, S., Yahia, I.B., Debabi, M.
      • Journal: Journal of Telecommunications and the Digital Economy
      • Year: 2022
      • Volume/Issue/Pages: 10(2), pp. 111–125
      • Citations: 2
    • “A specific language for developing business process by refinement based on BPMN 2.0”
      • Authors: Ayari, S., Hlaoui, Y.B., Ayed, L.B.
      • Conference: 16th International Conference on Software Technologies, ICSOFT
      • Year: 2021
      • Pages: pp. 489–496
      • Citations: 0
    • “A grammar based approach to BPMN model semantic preservation using refinement”
      • Authors: Ayari, S., Hlaoui, Y.B., Ayed, L.B.
      • Conference: International Computer Software and Applications Conference
      • Year: 2019
      • Volume/Pages: 2, pp. 549–554
      • Citations: 1
    • “Towards an Automatic Verification of BPMN Model Semantic Preservation During a Refinement Process”
      • Authors: Hlaoui, Y.B., Ayari, S., Ayed, L.J.B.
      • Conference: Communications in Computer and Information Science
      • Year: 2019
      • Volume/Pages: 1077, pp. 397–420
      • Citations: 1

Hafida bouarfa | Computer Science | Excellence in Research

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Mrs. Hafida bouarfa | Computer Science | Excellence in Research

Mrs. Hafida bouarfa, Université de Blida, Algeria

Professor at the Data Processing Department, University of Blida, Algeria, Hafida Bouarfa holds a Ph.D. in Data Processing and a Magister in Information Systems from H.E.C. Montreal. With extensive research on virtual organizations, she has published numerous articles in international journals and conferences, addressing topics like knowledge management and seismic evaluations. Passionate about education, she mentors students and collaborates on innovative projects. Married with two children, she balances her professional and family life while contributing significantly to the field of data processing. 📚✉️

Publication Profile

Google Scholar

Educational Background

Mrs. Hafida Bouarfa has an impressive educational background in Data Processing. She earned her Ph.D. in Data Processing with a focus on Information Systems from ESI (ex.INI) in Algiers, Algeria, in November 2004. Prior to that, she obtained her Magister in Information Systems from H.E.C. Montréal, Canada, in December 1991. Her journey began with an Engineer diploma in Data Processing, also from ESI (ex.INI) in September 1988. She laid a strong foundation with a General Certificate of Education in Mathematics in June 1983. 🎓📚

Research Focus

Mrs. Hafida Bouarfa’s research primarily focuses on the integration of advanced computing techniques in various domains. Her work includes big data analytics 📊, emphasizing decision-making processes and enhancing data-driven strategies. She explores ontology matching 🤖 and neural networks for information systems, aiming to improve knowledge management and retrieval. Additionally, her research addresses Internet of Things (IoT) 🔗 security through physical unclonable functions (PUFs) and mutual authentication protocols, contributing to safe and efficient communication networks. Bouarfa’s contributions to smart cities 🏙️ and fuzzy logic 🌫️ applications reflect her commitment to innovative solutions in technology and information management.

 

Publication Top Notes

  • A new model for integrating big data into phases of decision-making process | Cited by: 49 | Year: 2019 📊
  • Ontology matching using neural networks: survey and analysis | Cited by: 27 | Year: 2018 🤖
  • A survey on silicon PUFs | Cited by: 24 | Year: 2022 🔍
  • PUF-based mutual authentication and session key establishment protocol for IoT devices | Cited by: 23 | Year: 2023 🔐
  • Predicting students performance using decision trees: Case of an Algerian University | Cited by: 22 | Year: 2017 🎓
  • A new collaborative clustering approach for the Internet of vehicles (CCA-IoV) | Cited by: 17 | Year: 2020 🚗
  • Deep embedding learning with auto-encoder for large-scale ontology matching | Cited by: 15 | Year: 2022 🔗
  • Extension of commonKads for virtual organizations | Cited by: 15 | Year: 2003 🏢
  • Fuzzy probabilistic ontology approach: a hybrid model for handling uncertain knowledge in ontologies | Cited by: 13 | Year: 2019 🌫️
  • A new supervised learning based ontology matching approach using neural networks | Cited by: 12 | Year: 2019 📚

K ASHWINI | Computer Science | Best Researcher Award

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K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.

Rafael Natalio Fontana Crespo | Computer Science | Young Scientist Award

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Mr. Rafael Natalio Fontana Crespo| Computer Science | Young Scientist Award

PhD Student,  Politecnico di Torino,  Italy

Rafael Natalio Fontana Crespo is a promising candidate for the Research for Young Scientist Award, showcasing a strong educational foundation and relevant professional experience. Currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, he previously earned a Master’s Degree in Mechatronic Engineering with the highest honors. His thesis focused on developing a software platform for additive manufacturing, highlighting his innovative capabilities. Rafael’s internship at EPEC involved analyzing thermal images to prevent failures, demonstrating his practical application of engineering concepts. Proficient in both Spanish and English, he excels in communication, facilitating collaboration in the global research community. His technical skills in programming and advanced software tools further position him for success in data-driven research. Coupled with his hardworking and sociable nature, Rafael embodies the qualities of a dedicated researcher. Overall, he is well-prepared to make significant contributions to engineering and technology, making him an ideal candidate for the award.

Profile:

Education

Rafael Natalio Fontana Crespo is currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, a program that builds on his solid academic foundation. He previously earned a Master’s Degree in Mechatronic Engineering from the same institution, graduating with top honors (110/110 cum laude). His master’s thesis, titled “Design and Development of a Distributed Software Platform for Additive Manufacturing,” highlights his ability to tackle advanced technological challenges. Prior to this, he studied Electromechanical Engineering at Universidad Nacional de Córdoba in Argentina, further broadening his expertise in engineering disciplines. Throughout his academic journey, Rafael has consistently demonstrated a commitment to excellence and innovation, equipping him with a robust theoretical framework and specialized knowledge essential for impactful research. His diverse educational background positions him to contribute significantly to advancements in engineering and technology.

 

Research Skills

Rafael Natalio Fontana Crespo possesses a diverse and robust set of research skills that position him as a promising candidate for the Research for Young Scientist Award. Currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, he has demonstrated exceptional aptitude in innovative problem-solving through his master’s thesis on a distributed software platform for additive manufacturing. His practical experience at EPEC involved analyzing thermal images of electrical components, showcasing his ability to apply theoretical knowledge to real-world challenges. Proficient in programming languages such as Python and C, as well as advanced software tools like MATLAB and Simulink, Rafael is adept at handling complex data analyses and simulations. Additionally, his strong command of both Spanish and English enhances his collaborative capabilities within the international research community. With his dedication to pushing technological boundaries, Rafael is well-equipped to contribute significantly to future research endeavors.

 

Professional Experiences

Rafael Natalio Fontana Crespo’s professional experience includes a valuable internship at Empresa Provincial de Energía de Córdoba (EPEC) in Argentina, where he contributed to the Statistics and Technical Department. During his time at EPEC, he was responsible for analyzing thermal images of electrical components to identify potential failures and mitigate risks. This work not only showcased his ability to apply engineering principles to practical challenges but also highlighted his proficiency in using data analysis to enhance operational safety. Rafael’s internship provided him with hands-on experience in a real-world industrial setting, complementing his academic studies in engineering. His role involved producing detailed technical reports, further honing his analytical and communication skills. This experience, combined with his advanced knowledge of programming, software tools, and automation systems, demonstrates his capability to integrate technical knowledge into practical solutions, making him well-suited for research-driven initiatives and engineering projects.

Award And Recognition

Rafael Natalio Fontana Crespo is a distinguished candidate for the Research for Young Scientist Award, showcasing remarkable achievements in the fields of engineering and technology. Currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, he has excelled academically, graduating cum laude with a Master’s Degree in Mechatronic Engineering. His innovative thesis on a distributed software platform for additive manufacturing highlights his dedication to advancing engineering practices. Additionally, Rafael’s practical experience at EPEC, where he analyzed thermal images for fault prevention, demonstrates his ability to apply theoretical knowledge to real-world challenges. With strong communication skills in both Spanish and English, along with proficiency in programming and data analysis tools, Rafael exemplifies the qualities of a future leader in research. His hard work, sociability, and passion for collaboration position him as an outstanding candidate for this prestigious award.

 

Conclusion

Rafael Natalio Fontana Crespo is a highly qualified candidate for the Research for Young Scientist Award, given his exceptional academic background, relevant professional experience, and diverse technical skills. Currently pursuing a Ph.D. in Computer and Control Engineering at Politecnico di Torino, he holds a Master’s degree in Mechatronic Engineering, graduating with honors. His thesis on distributed software platforms for additive manufacturing highlights his ability to tackle complex engineering challenges. Professionally, his internship at EPEC, where he analyzed thermal images of electrical components, demonstrates his hands-on experience in applying theoretical knowledge to real-world problems. Rafael is proficient in multiple programming languages, engineering software, and data analysis tools, making him well-suited for advanced research. His fluency in both Spanish and English further supports his ability to collaborate internationally and communicate his findings effectively. With a strong work ethic, problem-solving abilities, and a passion for innovation, Rafael is a standout candidate for this award.

Publication Top Notes

  • “A Comparative Analysis of Machine Learning Techniques for Short-Term Grid Power Forecasting and Uncertainty Analysis of Wave Energy Converters”
    • Authors: Rafael Natalio Fontana Crespo, Alessandro Aliberti, Lorenzo Bottaccioli, Edoardo Pasta, Sergej Antonello Sirigu, Enrico Macii, Giuliana Mattiazzo, Edoardo Patti
    • Year: 2024
    • Type: Journal article (Engineering Applications of Artificial Intelligence)
    • DOI: 10.1016/j.engappai.2024.109352
    • Citations: Not available yet (as of 2024)
  • “A Distributed Software Platform for Additive Manufacturing”
    • Authors: Rafael Natalio Fontana Crespo, Davide Cannizzaro, Lorenzo Bottaccioli, Enrico Macii, Edoardo Patti, Santa Di Cataldo
    • Year: 2023
    • Type: Conference paper (IEEE 28th International Conference on Emerging Technologies and Factory Automation)
    • DOI: 10.1109/etfa54631.2023.10275694
    • Citations: Not available yet (as of 2024)
  • “LSTM for Grid Power Forecasting in Short-Term from Wave Energy Converters”
    • Authors: Rafael Natalio Fontana Crespo, Alessandro Aliberti, Lorenzo Bottaccioli, Enrico Macii, Giorgio Fighera, Edoardo Patti
    • Year: 2023
    • Type: Conference paper (IEEE 47th Annual Computers, Software, and Applications Conference)
    • DOI: 10.1109/compsac57700.2023.00230
    • Citations: Not available yet (as of 2024)

Oussama Mounnan | Computer Science | Best Researcher Award

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Mr. Oussama Mounnan | Computer Science | Best Researcher Award

Mr. Oussama Mounnan, Paris 8 University, France

Based on the detailed information provided about Mr. Oussama Mounnan, he appears to be a strong candidate for the “Best Researcher Award” due to his extensive experience and achievements in the field of cybersecurity, deep learning, and biometric access control. Below is a summary of his qualifications and contributions:

Publication profile

Professional Experience

Mr. Mounnan has been working as a Security Engineer since October 2015 at Weberfly-group in Marrakech, Morocco. He is responsible for managing, administering, and configuring network security systems, including firewalls, routers, switches, and VPN access. His role also includes performing network traffic analysis, implementing security policies, conducting security audits, and managing incidents. Additionally, he has experience in ethical hacking and penetration testing using various tools. Previously, he co-founded OussamaWeb, where he focused on IT maintenance, web development, and application creation from 2007 to 2015.

Research and Academic Background

Mr. Mounnan is currently pursuing a PhD in Computer Science at Ibn Zohr University-Agadir, Morocco, in collaboration with Paris 8 University, France. His research focuses on speech recognition using deep learning for biometric access control, a field that intersects artificial intelligence and cybersecurity. He has previously conducted research at the Oscar laboratory of Cadi Ayyad University, where he designed and tested systems for access control within the context of Big Data.

Technical Skills and Certifications

He has a comprehensive skill set covering programming languages (HTML, C, Python, Java), network security, system administration, virtualization, and data management tools. His certifications include ITIL V4, Prince2 Foundation, and various cybersecurity and machine learning credentials from Google, Coursera, and Fortinet. These certifications underline his commitment to staying updated in the rapidly evolving fields of IT security and data science.

Education

Mr. Mounnan holds a Master’s degree in Services, System Security, and Networks from the University of Lorraine, France, and a Bachelor’s degree in Networks and Telecommunications from Université Littoral Côte d’Opale, France. He has also completed specialized training in software engineering and information systems.

Additional Skills and Interests

He is proficient in English, French, and German at an advanced level. His interests include swimming, martial arts, reading, music, and scientific research, reflecting a well-rounded personality committed to both personal and professional development.

Publication Top Notes

  • Privacy-aware and authentication based on blockchain with fault tolerance for IoT enabled fog computing 🌐🔐 | Cited by: 21 | Year: 2020
  • Decentralized access control infrastructure using blockchain for big data 📊🔗 | Cited by: 10 | Year: 2019
  • Using blockchain based authentication solution for the remote surgery in tactile internet 🏥🖥️ | Cited by: 5 | Year: 2021
  • Anomaly detection for big data security: a benchmark 🔍🔒 | Cited by: 3 | Year: 2021
  • Efficient Distributed Access Control using Blockchain for Big Data in Clouds ☁️📈 | Cited by: 3* | Year: 2019
  • A novel approach based on blockchain to enhance security with dynamic policy updating 🔄🔐 | Cited by: 1 | Year: 2020
  • A Review on Deep Anomaly Detection in Blockchain 📚🛡️  Year: 2024
  • Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control 🎤🧠  Year: 2023
  • Deep Learning-Based Speech Recognition System using Blockchain for Biometric Access Control 🧠🔗 Year: 2022
  • Towards a Privacy preserving Machine Learning based Access Control for the Internet of Things 🌐🤖  Year: 2022


Conclusion

Mr. Oussama Mounnan’s blend of practical experience, academic research, and extensive certifications make him a suitable candidate for the “Best Researcher Award.” His work in cybersecurity and deep learning, particularly in speech recognition for biometric access, highlights his significant contributions to these fields.

Xiaozhou Lei | Computer Science | Best Researcher Award

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Xiaozhou Lei | Computer Science | Best Researcher Award

Dr Xiaozhou Lei, shanghai university, China

Evaluation for the Best Researcher Award: Dr. Xiaozhou Lei.

Publication profile

Orcid

Research Contributions and Innovations

Dr. Xiaozhou Lei has made notable contributions to the field of image enhancement through his pioneering work on the cell vibration energy model. This model, which he first proposed, quantitatively describes the relationship between stimulus intensity and energy during cell photothermal conversion. His work has successfully applied this model to address significant challenges in low-light enhancement and image dehazing, offering a novel approach to these problems. This research represents a unique intersection of biological modeling and image processing, with potential applications across various scientific and technological domains.

Academic Achievements

Dr. Lei has demonstrated a solid academic foundation, having earned his B.S. and M.S. degrees in mechanical design and mechatronic engineering, respectively, from the Wuhan Institute of Technology. He is currently pursuing his Ph.D. in control science and engineering at Shanghai University, which underscores his commitment to advancing his expertise. Despite being early in his academic career, Dr. Lei has completed or is involved in 9 research projects, published 5 papers in SCI-indexed journals, and contributed to the field by serving as a reviewer for the Pattern Recognition Journal.

Industry and Professional Involvement

Dr. Lei’s involvement in 11 consultancy and industry projects highlights his ability to bridge the gap between academic research and practical applications. Although he has not yet published books or patents, his work has significant implications for the fields of image processing and photothermal conversion. His professional network is also expanding, as seen in his reviewer role, although he does not currently hold any editorial appointments or professional memberships.

Conclusion

Dr. Xiaozhou Lei’s innovative research on the cell vibration energy model and its application to image enhancement positions him as a strong candidate for the Best Researcher Award. His work is both original and impactful, demonstrating a deep understanding of both the theoretical and practical aspects of his field. While his academic and professional profile is still developing, his contributions thus far are promising and reflect significant potential for future advancements. Thus, he is a suitable candidate for recognition in this award category.

Publication top notes

Low-light image enhancement based on cell vibration energy model and lightness difference

Low-Light Image Enhancement Using the Cell Vibration Model

 

Huilong Fan | Computer Science | Best Researcher Award

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Dr Huilong Fan |  Computer Science |  Best Researcher Award

assistant researcher at  University of Electronic Science and Technology of China

Huilong Fan is a research assistant at the University of Electronic Science and Technology of China, born in December 1992, and residing in Changsha, Hunan. He specializes in Edge Computing and Artificial Intelligence.

profile

Academic Background:

  • Ph.D. in Computer Science and Technology, Central South University (2019-2023)
    • Major: Satellite multi-intelligence collaborative computing, digital twins, swarm intelligence negotiation, multi-intelligence deep reinforcement learning, online scheduling, artificial intelligence, machine learning.
  • Master in Computer Science and Technology, Guizhou University (2015-2018)
    • Major: Medical big data, big data analysis and prediction, deep learning, multi-label data classification, natural language processing.
  • Bachelor in Network Engineering, Nanyang Institute of Technology (2010-2014)
    • Major: Computer Networks, Principles of Computer Composition, Operating Systems, Algorithm Design.

Professional Experience:

  • Data Analyst, Beijing Ark Hospital (June 2014-Sept 2015; Dec. 2023-Present)
    • Responsibilities: Data cleaning, analysis, and visualization, system development and maintenance, research on satellite networks, collaborative computing, and edge computing.
  • R&D Engineer, Hunan Lisen Data Technology Co Ltd (June 2018-Sept 2019)
    • Responsibilities: Algorithm design, multi-platform software architecture design, software development, database management, interface development and design.

Projects and Leadership:

  • Led projects on mixed integer programming for multi-process production scheduling, satellite and management software R&D, and real-time analysis methods for large-scale multi-source data based on supercomputing.
  • Participated in significant research such as intelligent analysis technology for TFDS images and resource allocation technology based on collaborative perception.

Awards and Patents:

  • Second prize in scientific and technological progress (2020)
  • First prize in the Guizhou Province Innovation and Entrepreneurship Competition (2016)
  • National third prize in the ‘Internet +’ College Students Innovation and Entrepreneurship Competition (2016)
  • Invention Patents: Multi-agent Space-based Information Network Task Scheduling Method (2021), Dynamic Reconfigurable Space-based Information Network Simulation and Computing System (2022).

Skills:

  • Proficient in software architecture design, Java, Python, C, and other programming languages.
  • Experienced in leading R&D teams and writing research project applications.

Research Focus in Computer Science:

Huilong Fan’s research in Computer Science spans several advanced and interdisciplinary areas, primarily focusing on:

  1. Satellite Multi-Intelligence Collaborative Computing:
    • Developing systems that allow multiple intelligent agents to work together effectively in satellite networks.
    • Utilizing collaborative algorithms to improve the efficiency and reliability of satellite communications and operations.
  2. Digital Twins:
    • Creating digital replicas of physical systems to simulate and analyze their real-world counterparts.
    • Applying digital twin technology to monitor, diagnose, and optimize satellite and network operations.
  3. Swarm Intelligence Negotiation:
    • Investigating algorithms that enable decentralized agents to coordinate and negotiate within a swarm.
    • Using swarm intelligence for tasks such as resource allocation and scheduling in dynamic environments.
  4. Multi-Intelligence Deep Reinforcement Learning:
    • Developing deep learning models that enable multiple intelligent agents to learn and adapt to complex environments.
    • Applying these models to solve problems in satellite networks and edge computing.
  5. Online Scheduling:
    • Researching methods for real-time scheduling of tasks and resources in dynamic and distributed systems.
    • Focusing on optimizing the allocation of contact windows in satellite communication networks.
  6. Artificial Intelligence and Machine Learning:
    • Applying AI and ML techniques to solve complex problems in big data analysis, prediction, and decision-making.
    • Emphasizing multi-label data classification and natural language processing for diverse applications.
  7. Medical Big Data:
    • Analyzing and predicting trends in medical data using big data technologies.
    • Developing models for deep learning and multi-label classification to enhance medical data interpretation and application.
  8. Graph-Driven Resource Allocation:
    • Utilizing graph theory and cooperative game theory to optimize resource allocation in Internet of Things (IoT) and satellite networks.
    • Developing adaptive scheduling algorithms for real-time and dynamic environments.

Through his extensive research, Huilong Fan aims to push the boundaries of what is possible in satellite communication, edge computing, and AI, contributing significantly to advancements in these fields.

Publication Top Notes:

  • Dynamic Network Resource Autonomy Management and Task Scheduling Method Li, X., Yang, J., Fan, H.
    Mathematics, 2023, 11(5), 1232. Citations: 6
  • A novel multi-satellite and multi-task scheduling method based on task network graph aggregation Fan, H., Yang, Z., Zhang, X., Long, J., Liu, L.
    Expert Systems with Applications, 2022, 205, 117565. Citations: 15
  • A Spatio-Temporal Graph Neural Network Approach for Traffic Flow Prediction Li, Y., Zhao, W., Fan, H.
    Mathematics, 2022, 10(10), 1754. Citations: 6
  • Quantum Digital Signature with Continuous-Variable Deng, X., Zhao, W., Shi, R., Ding, C., Fan, H.
    International Journal of Theoretical Physics, 2022, 61(5), 144. Citations: 3