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.

Yanwei Fu | Computer Science | Best Researcher Award

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Yanwei Fu | Computer Science | Best Researcher Award

Dr Yanwei Fu ,Fudan University ,China

Based on the comprehensive profile provided, Prof. Dr. Yanwei Fu is indeed a highly qualified candidate for the Best Researcher Award. His achievements, research contributions, and academic standing illustrate his significant impact on the field of computer science, particularly in machine learning and computer vision.

Publication profile

google scholar

Educational Background

Prof. Fu holds a Ph.D. in Computer Science with a specialization in Computer Vision from Queen Mary University of London (2011-2014). His earlier education includes a Master’s degree from Nanjing University and a Bachelor’s degree from Nanjing University of Technology. This solid foundation in computer science has equipped him with the skills necessary for cutting-edge research.

Awards and Recognitions

Prof. Fu’s accolades demonstrate his prominence in the academic community:

  • DECRA Fellow by the Australian Research Council (2016)
  • Distinguished Professor of Eastern Scholar at Shanghai Institutions of Higher Learning (2017)
  • 1000 Young Innovative Talent Professional Fellow by NSFC (2018)
  • Winner of the Best Paper Award at the IEEE International Conference on Multimedia and Expo (ICME) (2019)
  • Recipient of the ACM China SIGAI Rising Star Award (2018) and ACM Shanghai Rising Star Award (2019)
  • Fellow of the British Computer Society (2022)

These recognitions highlight his significant contributions to research and academia, establishing him as a leader in his field.

Research Interests

Prof. Fu’s research interests span various crucial topics in machine learning and computer vision:

  1. Learning from Small Samples: He focuses on statistical sparsity and has developed methods for one-shot and few-shot learning.
  2. 3D/4D Object Reconstruction: His work includes innovative techniques for 3D model reconstruction and robotic grasping.
  3. Artificial Intelligence and Generative Models: He explores foundation models for image manipulation and advanced applications in robotic tasks.

His diverse research portfolio reflects his commitment to advancing knowledge in these areas, driving innovation through interdisciplinary approaches.

Positions Held

Prof. Fu’s career includes prestigious positions such as:

  • DECRA Fellow (2017-2020)
  • Visiting Professor at renowned institutions, including Tencent AI Lab and AItricks.com
  • Associate Professor and Professor at Fudan University since 2016

These roles not only underscore his expertise but also his ability to contribute to and lead significant research projects.

Selected Publications

Prof. Fu has authored numerous influential papers, contributing substantially to the field. Some notable publications include:

  • “Pixel2mesh: Generating 3D Mesh Models from Single RGB Images” – A pioneering work in 3D modeling.
  • “An End-to-End Architecture for Class-Incremental Object Detection with Knowledge Distillation” – Recognized with a best paper award, showcasing his innovative approach to object detection.

Publication Top Notes

Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers

Pixel2mesh: Generating 3d mesh models from single rgb images

Soft filter pruning for accelerating deep convolutional neural networks

Transductive Multi-view Zero-Shot Learning

Pose-normalized image generation for person re-identification

Chained-tracker: Chaining paired attentive regression results for end-to-end joint multiple-object detection and tracking

Multi-scale deep learning architectures for person re-identification

Multi-level semantic feature augmentation for one-shot learning

Transductive multi-view embedding for zero-shot recognition and annotation

Conclusion

Given his extensive educational background, numerous prestigious awards, impactful research interests, and significant contributions to the field of computer vision, Prof. Dr. Yanwei Fu stands out as an exemplary candidate for the Best Researcher Award. His work not only advances theoretical knowledge but also has practical implications that push the boundaries of current technology.

Imtiaz Ahmad | Computer Science | Best Researcher Award

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Imtiaz Ahmad | Computer Science | Best Researcher Award

Mr Imtiaz Ahmad, Hazara University Mansehra, Pakistan

Based on the provided information, Mr. Imtiaz Ahmad demonstrates significant potential as a candidate for the “Best Researcher Award.” Here’s an assessment of his qualifications:

Publication profile

Orcid

Educational Background

Mr. Imtiaz Ahmad holds a Master of Science in Computer Science from Hazara University Mansehra, graduating with an impressive CGPA of 3.71/4.00. His thesis focused on developing an adaptive and priority-based data aggregation and scheduling model for wireless sensor networks, showcasing his ability to tackle complex problems in this area. His Bachelor’s degree in Information Technology from the University of Malakand further laid the foundation for his technical expertise, although his CGPA of 2.95/4.00 was more modest. Nonetheless, his final year project on an online hospital management system reflects his ability to apply academic knowledge to real-world problems.

Research Contributions

Mr. Ahmad has made meaningful contributions to the field of computer science, particularly in wireless sensor networks and mobile edge computing. His publication in the Knowledge-Based Systems journal on adaptive and priority-based data aggregation and scheduling for wireless sensor networks is a strong indicator of his research capabilities. Additionally, his work on mobility prediction-based adaptive task migration in mobile edge computing, published in VFAST Transactions on Software Engineering, highlights his focus on cutting-edge issues in computer science. These publications in reputable journals underline his research aptitude and commitment to advancing the field.

Professional Experience

Mr. Ahmad has accumulated valuable teaching and technical experience through various roles. As a visiting lecturer at Hazara University and a computer science lecturer at other institutions, he has been responsible for planning and delivering lectures, assessing student work, and supervising final year projects. His involvement in these educational roles suggests a deep engagement with the academic community and a commitment to nurturing future researchers. His previous internship at Hazara University, where he addressed technical issues and assisted in setting up multimedia for conferences, adds to his practical experience.

Awards and Certifications

Mr. Ahmad has been recognized for his research potential early in his academic career, receiving the Best Student Researcher Award from the Department of Computer Science at Hazara University in 2020. Additionally, he was awarded a laptop through the Prime Minister’s Laptop Scheme for high achievers, which is a testament to his academic excellence. His professional certifications, including Microsoft Office Specialist and vocational training in computers, further bolster his technical skill set.

Conclusion

In conclusion, Mr. Imtiaz Ahmad’s solid academic background, impactful research publications, teaching experience, and recognized achievements make him a strong candidate for the “Best Researcher Award.” His work in wireless sensor networks and mobile edge computing is both relevant and innovative, positioning him well for continued contributions to the field of computer science. Therefore, he is indeed suitable for consideration for this prestigious award.

Publication top notes

Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Network

A Mobility Prediction Based Adaptive Task Migration in Mobile Edge Computing

 

 

Larbi Boubchir | Computer Science Award | Best Researcher Award

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Prof. Larbi Boubchir | Computer Science Award | Best Researcher Award

Prof. Larbi Boubchir, University of Paris 8, France

Prof. Larbi Boubchir appears to be a strong candidate for the “Research for Best Researcher Award” based on several key factors:

Publication profile

Academic and Professional Achievements

Prof. Boubchir is a Full Professor of Computer Science at the University of Paris 8, France, where he has held multiple significant roles, including Deputy Director of the LIASD laboratory and Head of the IUSD research group. His academic background includes a Ph.D. in Signal and Image Processing and an HDR degree in Computer Science, showcasing a solid foundation in his field.

Research Expertise

His research interests are diverse and highly relevant, covering artificial intelligence, biometrics, biomedical signal processing, and image processing. His expertise in advanced areas such as machine learning, deep learning, and feature engineering, coupled with practical applications in biometric security and health-related fields, highlights his significant contributions to cutting-edge technology.

Publication 

  • Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities 📉 – Cited by 155, 2005
  • Face–iris multimodal biometric identification system 🕵️‍♂️ – Cited by 104, 2020
  • Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters ✋ – Cited by 89, 2016
  • Multivariate statistical modeling of images with the curvelet transform 📊 – Cited by 79, 2005
  • A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with … ⏱️ – Cited by 74, 2012
  • A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate α-stable prior 📈 – Cited by 64, 2006
  • Wavelet Denoising Based on the MAP Estimation Using the BKF Prior With Application to Images and EEG Signals 🧠 – Cited by 57, 2013
  • EEG epileptic seizure detection and classification based on dual-tree complex wavelet transform and machine learning algorithms ⚡ – Cited by 50, 2020
  • A review of feature extraction for EEG epileptic seizure detection and classification 🔬 – Cited by 49, 2017
  • Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states 🔍 – Cited by 45, 2020
  • Robust model-free gait recognition by statistical dependency feature selection and globality-locality preserving projections 🚶‍♂️ – Cited by 39, 2016
  • Human gait recognition based on Haralick features 🚶‍♀️ – Cited by 38, 2017
  • Face–iris multi-modal biometric system using multi-resolution Log-Gabor filter with spectral regression kernel discriminant analysis 📸 – Cited by 37, 2018
  • Palm vein recognition based on competitive coding scheme using multi-scale local binary pattern with ant colony optimization 🖐️ – Cited by 36, 2020
  • Human gait recognition using GEI-based local multi-scale feature descriptors 🕺 – Cited by 36, 2019

Awards and Recognition

He has received several prestigious awards, including IEEE Access Outstanding Associate Editor accolades and Best Paper awards at international conferences. These honors reflect his high impact and recognition in the research community.

Leadership and Teaching

In addition to his research, Prof. Boubchir has made substantial contributions to education as the head of Master’s programs in Cyber Security, Data Science, and Big Data. His leadership in these programs demonstrates his commitment to advancing knowledge and mentoring future professionals.

Conclusion

Prof. Boubchir’s extensive research contributions, leadership roles, and accolades make him a highly suitable candidate for the Research for Best Researcher Award.

Mr. Shofiqul Islam | Computer Science | Best Researcher Award

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Mr. Shofiqul Islam | Computer Science | Best Researcher Award

Mr Shafiqul Islam ,    Deakin University , Australia

Md. Shofiqul Islam, born in May 1989, is a resident of Highton, Geelong, Australia. Originally hailing from Chutipur, Notipota, Dhamuruda-7220, Chuadanga, Bangladesh, he has established himself in Australia while maintaining ties to his permanent address in Bangladesh. Shofiqul Islam is the son of Md. Abdul Khaleque. He stands 5 feet 7.5 inches tall and weighs 78 kilograms. As a male citizen of Bangladesh, he holds a National ID with the number 1813183458130.

Publication profile
Educational Background

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a program he began in May 2024. Prior to this, he completed a Master of Science (M.Sc) by Research at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), Pahang, Malaysia, in November 2022, achieving an impressive 80% mark. He earned his Bachelor of Science (B.Sc) in Computer Science and Engineering from Islamic University, Kushtia, Bangladesh, in 2014, where he graduated with a CGPA of 3.69 out of 4.00, securing 2nd position among 45 students. His academic journey began at Notipota High School in Dhamurhuda, Chuadanga, Bangladesh, where he obtained his Secondary School Certificate (SSC) in Science in 2005 with a GPA of 4.06 out of 5.00. He then completed his Higher Secondary Certificate (HSC) in Science at Chuadanga Govt. College in 2007, with a GPA of 4.70 out of 5.00.

Research and Work Experience

Md. Shofiqul Islam is currently pursuing a Ph.D. in AI-Based Haptic Robotic Control in Medical Tele-Surgery at Deakin University, Australia, a journey he began in May 2024. Before embarking on his Ph.D., he served as an Assistant Professor in the Department of Computer Science and Engineering at the Military Institute of Science and Technology (MIST) in Dhaka, Bangladesh, from March 2023 to April 15, 2024. Prior to this role, he was a Senior Lecturer at the World University of Bangladesh (WUB) for a brief period from January 2023 to April 2023. His academic career also includes a significant tenure as a Graduate Research Assistant at the Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA), where he contributed to research from October 2018 to June 2022. Earlier, he held positions as a Lecturer in Computer Science and Engineering at Atish Dipankar University of Science and Technology from October 2016 to September 2018, and at First Capital University of Bangladesh (FCUB) from February 2015 to June 2016. His extensive experience in academia reflects his deep commitment to advancing knowledge in computer science and engineering.

 

Awards and Recognitions

Md. Shofiqul Islam has been awarded a prestigious fully funded Ph.D. scholarship from the Australian Government, supporting his research at Deakin University from May 2022 to May 2027. This scholarship enables him to pursue advanced studies in AI-Based Haptic Robotic Control in Medical Tele-Surgery. Prior to this, he received a Graduate Research Assistantship (GRA) at Universiti Malaysia Pahang, Malaysia, where he contributed to significant research projects from March 2018 to November 2022. His academic excellence was also recognized during his undergraduate studies, where he received a Merit Scholarship each year from 2009 to 2014 while pursuing a B.Sc. in Computer Science and Engineering at Islamic University, Bangladesh. These achievements reflect his consistent dedication and outstanding performance throughout his academic career.

Publication Top Notes

  • HARDC: A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention-based dual structured RNN with dilated CNN
    Authors: MS Islam, KF Hasan, S Uddin, JMW Quinn, MA Moni
    Journal: Neural Networks, Volume 162, Pages 271-287, 2023
    Citations: 30
  • A review on video classification with methods, findings, performance, challenges, limitations and future work
    Authors: MS Islam, U Kumar Roy, J Al Mahmud
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 6, Pages 47-57, 2020
    Citations: 30
  • New hybrid deep learning approach using BiGRU-BiLSTM and multilayered dilated CNN to detect arrhythmia
    Authors: MS Islam, MN Islam, N Hashim, M Rashid, BS Bari, F Al Farid
    Journal: IEEE Access, Volume 10, Pages 58081-58096, 2022
    Citations: 26
  • A review on recent advances in Deep learning for Sentiment Analysis: Performances, Challenges and Limitations
    Authors: MS Islam, N Ab Ghani, MM Ahmed
    Journal: Journal of COMPUSOFT, 2020
    Citations: 16
  • A Novel BiGRUBiLSTM Model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM
    Authors: MS Islam, NA Ghani
    Book Series: Lecture Notes in Electrical Engineering (LNEE), Springer, 2021
    Citations: 15
  • HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text
    Author: MS Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, April 2021
    Citations: 14
  • Machine Learning-Based Music Genre Classification with Pre-Processed Feature Analysis
    Authors: MS Islam, MM Hasan, MA Rahim, AM Hasan, M Mynuddin, I Khandokar, …
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Issue 3, Pages 491-502, 2021
    Citations: 10
  • Applications of Artificial Neural Networks in Engine Cooling System
    Authors: MM Hasan, MS Islam, SA Bakar, MM Rahman, MN Kabir
    Conference: 2021 International Conference on Software Engineering & Computer Systems (ICSECS), IEEE
    Citations: 7
  • Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach
    Authors: MS Islam, MN Kabir, NA Ghani, KZ Zamli, NSA Zulkifli, MM Rahman, …
    Journal: Artificial Intelligence Review, Volume 57, Issue 3, Pages 62, 2024
    Citations: 6
  • Machine Learning Methods to Predict and Analyse Unconfined Compressive Strength of Stabilised Soft Soil with Polypropylene Columns
    Authors: HRS Ikramul Hoque, Muzamir Hasan, Shofiqul Islam, Moustafa Houda, Mirvat Houda
    Journal: Cogent Engineering, Volume 10, Issue 1, 2023
    Citations: 6
  • New Hybrid Deep Learning Method to Recognize Human Action from Video
    Authors: MS Islam, MJ Islam
    Journal: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI), Volume 7, Pages 306-313, 2021
    Citations: 4

 

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