Shiping Wang | Computer Science | Research Excellence Award

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Shiping Wang | Computer Science | Research Excellence Award

Fuzhou University | China

Prof. Shiping Wang is a Full Professor in the field of computer and data science and serves as the Director of a provincial key laboratory focused on intelligent metro systems. His research centers on machine learning, deep learning, graph neural networks, feature representation, and graph foundation models. He has published over 200 papers in leading journals and conferences, accumulating more than 6,200 citations, and his work appears in top venues such as IEEE TPAMI, TIP, TMM, CVPR, AAAI, and ACM MM. He has held key leadership and organizational roles in international conferences, including general chair, regional chair, and session chair positions, and regularly serves as a program committee member and reviewer for major AI and computer vision conferences and journals. His research has been supported by multiple projects funded by the National Natural Science Foundation of China.

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Junaid Akram | Computer Science | Research Excellence Award

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Junaid Akram | Computer Science | Research Excellence Award

Unsw College | Australia

Dr. Junaid Akram is a researcher in decentralized systems and trustworthy AI, with a PhD from the University of Sydney. His work focuses on building secure, privacy-preserving, and reliable trust mechanisms for safety-critical, crowdsourced platforms, particularly in drone-based services for environmental monitoring and emergency response. His research integrates blockchain and decentralized public key infrastructures, verifiable credentials, adversarial machine learning, and data analytics to improve security, fairness, and resilience in multi-sided ecosystems. Through frameworks such as decentralized identity management, tamper-resistant reputation systems, anomaly detection, and robust graph learning, his contributions aim to reduce operational risk while enhancing participation and service quality in emerging digital platforms.

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Fabrice Vidal | Computer Science | Research Excellence Award

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Fabrice Vidal | Computer Science | Research Excellence Award

Hospital center|France

Dr. Fabrice Vidal is a hospital pharmacist with extensive experience in hospital pharmacy management, medication safety, and healthcare quality systems. Since 2014, he has served as a Hospital Practitioner and Head of the Pharmacy for Internal Use at the Centre Hospitalier de Dax, where he plays a central role in ensuring the safe, efficient, and compliant use of medicines and medical devices. His responsibilities include the management of medical devices, oversight of pharmaceutical logistics, and active participation in the quality management of medication use and the overall medication care pathway. He has contributed significantly to the modernization of hospital pharmacy operations through involvement in the implementation of a Warehouse Management System and the development and deployment of computerized prescribing decision-support software. His expertise also extends to the validation of chemotherapy prescriptions, ensuring adherence to clinical protocols and patient safety standards. In addition, he has participated in pharmaceutical on-call duties related to medication safety and emergency preparedness. Prior to his permanent appointment, he worked as a full-time contractual Hospital Practitioner at the same institution, gaining strong operational experience within the Pharmacy for Internal Use.


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Yanxia Liang | Computer Science | Research Excellence Award

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Yanxia Liang | Computer Science | Research Excellence Award

西安邮电大学 | China

Dr. Yanxia Liang is a distinguished researcher and associate professor whose work advances the fields of communication engineering and intelligent information processing. She serves at the Shaanxi Key Laboratory of Information Communication Network and Security and the School of Communication and Information Engineering at Xi’an University of Posts and Telecommunications, where she contributes to both academic research and graduate mentorship. Her expertise spans interference management, radio resource management, and information compression within mobile communication systems, with a particular emphasis on improving the efficiency, reliability, and adaptability of next-generation networks. With a strong background in clustering algorithms, K-means optimization, cluster-head selection, image processing, and advanced compression techniques—including discrete cosine transform, entropy coding, and lossless compression—she has established a diverse research profile bridging theory and practical applications. Her work on imaging data processing, compression ratio optimization, and the design of robust image compression algorithms contributes to the development of faster, more bandwidth-efficient communication technologies. Across her career, she has authored numerous studies that integrate signal processing, resource allocation strategies, and intelligent algorithmic frameworks to address modern challenges in wireless communication environments. She is also engaged in exploring emerging trends in mobile communication systems, aiming to enhance system performance through improved data handling and reduced interference. Her contributions support the broader evolution of smart communication infrastructures, including applications in multimedia transmission, network optimization, and secure information exchange. Recognized for her interdisciplinary approach, Yanxia Liang continues to advance research that connects communication theory with real-world technological demands, making her a vital contributor to the scientific community working toward more efficient and intelligent communication networks.

Profile: Scopus

Featured Publications

Liang, Y., Sun, C., Jiang, J., Liu, X., He, H., & Xie, Y. (2020). An efficiency-improved clustering algorithm based on KNN under ultra-dense network. IEEE Access, 8. IEEE.

Liang, Y., Zhao, S., Liu, X., He, H., Zhao, X., & Wang, H. (2024). A balanced energy-efficient clustering strategy for WSNs. IEEE Sensors Journal, 24(22). IEEE.

He, H., Liang, Y., & Li, S. (2021). Clustering algorithm based on azimuth in mmWave massive MIMO–NOMA system. In 2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE.

Liang, Y., Liu, X., Jiang, J., Du, J., Sun, C., & Xie, Y. (2020). A practical dynamic clustering scheme using spectral clustering in ultra-dense network. In 2020 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE.

Liang, Y., Jia, T., Li, N., Liu, X., Jiang, J., Lu, G., & Zhao, M. (2024). Review of static image compression algorithms. In 2024 IEEE 7th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE.

Liu, X., & Liang, Y. (2021). A novel Moore–Penrose-inverse-matrix-based data compression method. In 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE.

Xiaohang Zhao | Computer Science | Best Researcher Award

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Xiaohang Zhao | Computer Science | Best Researcher Award

Dr. Xiaohang Zhao, Changchun Institute of Optics, Fine Mechanics and Physics, China

Xiaohang Zhao is a dedicated Ph.D. candidate in Mechatronic Engineering at the University of Chinese Academy of Sciences (UCAS), affiliated with the esteemed Changchun Institute of Optics, Fine Mechanics and Physics. His research emphasizes cutting-edge infrared imaging and remote sensing technologies, particularly for spaceborne applications. Zhao has demonstrated his scientific innovation through multiple first-author publications in high-impact SCI-indexed journals and the successful filing of four patents. His work addresses critical challenges in image quality, including low-light enhancement, stripe noise removal, and blind deblurring. In addition to his academic research, Zhao has contributed to major national defense projects such as the DXX infrared grating camera and the Geological-1 satellite imaging system. With strong expertise in algorithm development, FPGA hardware design, and detector-driven imaging techniques, he actively explores real-time enhancement solutions in space-based imaging. Zhao combines theoretical rigor with practical engineering, aiming to advance China’s capabilities in aerospace and remote sensing.

Publication Profile

orcid

🎓 Education

Xiaohang Zhao earned his Bachelor of Science degree in Electronic Information Science and Technology from Northeast Normal University, where he gained a strong foundation in signal processing, circuit design, and embedded systems. Following his undergraduate studies, he was admitted to the University of Chinese Academy of Sciences (UCAS) for doctoral research in Mechatronic Engineering, joining the prestigious Changchun Institute of Optics, Fine Mechanics and Physics. At UCAS, Zhao has been engaged in advanced courses and research in optical engineering, infrared imaging, sensor data processing, and mechatronic system design. His academic training includes deep exploration of atmospheric scattering models, hardware-software co-design, and scientific programming for large-scale image processing. Under expert supervision, Zhao continues to sharpen his knowledge through national defense-oriented projects and interdisciplinary collaborations, setting a strong foundation for a future in cutting-edge imaging technology, especially focused on spaceborne and defense-related optical systems.

💼 Experience

Xiaohang Zhao is currently a Ph.D. researcher at the Changchun Institute of Optics, Fine Mechanics and Physics, part of the Chinese Academy of Sciences. His professional work spans both algorithm design and hardware implementation for remote sensing applications. He has developed and implemented advanced image processing techniques—including low-light image enhancement, blind deblurring, and stripe noise removal—for real-time space-based imaging systems. Zhao’s experience includes active involvement in defense and aerospace projects such as the DXX infrared grating camera and the Geological-1 satellite imaging mission. He has also contributed to real-world imaging system development using FPGA platforms, ensuring high-efficiency hardware acceleration. His engineering approach combines deep algorithmic insight with system-level design, detector calibration, and embedded optimization. Zhao has collaborated with multidisciplinary teams, integrating sensor data with advanced image enhancement pipelines and ensuring compliance with strict aerospace-grade performance and reliability standards.

🏆 Honors and Awards

Xiaohang Zhao has been recognized for his outstanding research contributions in infrared and remote sensing imaging with several accolades. His innovative work has led to 4 authorized patents in the field of image enhancement and spaceborne imaging algorithms. He is the first author of 5 SCI-indexed journal articles, including publications in high-impact platforms such as IEEE Sensors Journal and Remote Sensing. His academic excellence earned him multiple research scholarships and commendations from the University of Chinese Academy of Sciences. Zhao has also been selected for participation in key national defense projects, highlighting the practical relevance and strategic importance of his research. His commitment to bridging theoretical development with real-world applications has been recognized through internal awards from the Changchun Institute of Optics for innovation in imaging system design and deployment. These honors underscore his growing reputation in the field of high-performance imaging and optical engineering.

🔬 Research Focus

Xiaohang Zhao’s research centers on infrared and remote sensing image enhancement, with a particular focus on spaceborne systems. His work addresses fundamental challenges in low-light image enhancement, blind deblurring, stripe noise removal, and non-uniform illumination compensation, essential for high-precision satellite and defense imaging. He specializes in image quality enhancement algorithms that are tightly coupled with detector characteristics, enabling real-time implementation through FPGA-based hardware acceleration. Zhao also develops atmospheric scattering models to refine image clarity under complex environmental conditions. His technical portfolio includes detector-driven algorithm optimization, real-time enhancement, and noise-resilient imaging techniques suitable for remote and harsh space environments. Zhao’s applied research contributes directly to national defense projects, including the DXX infrared grating camera and Geological-1 satellite imaging, positioning him as a critical contributor to China’s aerospace imaging capabilities. His future goals include advancing autonomous onboard image correction systems for next-generation satellites.

📚 Publications

  • 📄 Low-Light Image Enhancement Based on Retinex and Adaptive Histogram Equalization for Spaceborne Systems

  • 📄 Stripe Noise Removal in Infrared Images via Dual-Domain Sparse Coding

  • 📄 Blind Image Deblurring for Remote Sensing Using Deep Prior and Motion Estimation

  • 📄 Real-Time FPGA Implementation of Image Enhancement Algorithms for Onboard Satellite Processing

  • 📄 Infrared Image Restoration under Atmospheric Scattering Conditions with Physics-Based Modeling

Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Md. Tarek Habib | Computer Science | Best Researcher Award

Assist. Prof. Dr. Md. Tarek Habib Independent University, Bangladesh

Dr. Md. Tarek Habib is an Assistant Professor in the Department of Computer Science and Engineering at Independent University, Bangladesh. With a strong passion for teaching and research, his objective is to enhance his expertise in the field of Computer Science and Engineering. His research interests include Artificial Intelligence, with a focus on Computer Vision, Machine Learning, and Natural Language Processing, as well as IoT and E-Commerce. Dr. Habib is dedicated to advancing knowledge and innovation in these domains, contributing to both academia and industry through his research and mentorship.

Education:

Doctor of Philosophy (Ph.D.) in Computer Science and Engineering

Institution: Jahangirnagar University, Bangladesh

Year: 2022

Thesis Title: Machine Vision Based Fruit Disease Recognition

Supervisor: Prof. Dr. Mohammad Shorif Uddin

Co-Supervisor: Prof. Dr. Farruk Ahmed (Independent University, Bangladesh)

Master of Science (M.S.) in Computer Science and Engineering

Institution: North South University, Bangladesh

Year: 2009

CGPA: 3.85 on a scale of 4.0

Thesis Title: Machine Vision Based Textile Defects Classification

Supervisor: Prof. Dr. M. Rokonuzzaman

Bachelor of Science (B.Sc.) in Computer Science

Institution: BRAC University, Bangladesh

Year: 2006

CGPA: 3.74 on a scale of 4.0

Award: Vice Chancellor’s Medal

Thesis Title: A Survey on Location Systems for Ubiquitous Computing

Supervisor: Prof. Dr. Matin Saad Abdullah

Higher Secondary Certificate (HSC)

Institution: SOS Hermann Gmeiner College, Dhaka Board

Year: 2000

Division: 2nd Division (Science Group)

Total Marks: 567 out of 1000

Secondary School Certificate (SSC)

Institution: Sher-e-Bangla Nagar Govt. Boys’ High School, Dhaka Board

Year: 1998

Division: 1st Division with Star Marks (Science Group)

Total Marks: 823 out of 1000

Professional Profiles:

ORCID Profile

Scopus Profile

Professional Experience:

Assistant Professor, Department of Computer Science and Engineering

Independent University, Bangladesh January 2023

Associate Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2023 – January 2023)

Assistant Professor, Department of Computer Science and Engineering
Daffodil International University, Bangladesh (January 2016 – December 2022)

Assistant Professor (Contractual), Department of Computer Science and Engineering
Daffodil International University, Bangladesh (September 2015 – December 2015)

Assistant Professor, Department of Computer Science and Engineering
Green University of Bangladesh (May 2014 – September 2015)

Assistant Professor, Department of Computer Science and Engineering
Prime University, Bangladesh (September 2013 – May 2014)

Senior Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (January 2013 – August 2013)

Lecturer, Department of Computer Science and Engineering
Prime University, Bangladesh (October 2010 – December 2012)

Research Interests:

Artificial Intelligence (AI) and Its Applications

Computer Vision

Machine Learning (ML)

Natural Language Processing (NLP)

Internet of Things (IoT)

E-Commerce and AI-Driven Business Solutions

Top Notable Publications:

An Insightful Analysis of CNN-Based Dietary Medicine Recognition

Journal of Agriculture and Food Research, 2025-03

DOI: 10.1016/j.jafr.2024.101564

Contributors: Mohammad Didarul Alam, Tanjir Ahmed Niloy, Aurnob Sarker Aurgho, Mahady Hasan, Md. Tarek Habib

Deep Learning Modeling for Potato Breed Recognition

IEEE Transactions on AgriFood Electronics, 2024

DOI: 10.1109/TAFE.2024.3406544

Contributors: Md. Ataur Rahman, Abbas Ali Khan, Md. Mehedi Hasan, Md. Sadekur Rahman, Md. Tarek Habib

A Study on Social Media Addiction Analysis on the People of Bangladesh Using Machine Learning Algorithms

Bulletin of Electrical Engineering and Informatics, 2024-10-01

DOI: 10.11591/eei.v13i5.5680

Contributors: Minjun Nahar Mim, Mehedi Firoz, Mohammad Monirul Islam, Mahady Hasan, Md. Tarek Habib

Tomato Pest Recognition Using Convolutional Neural Network in Bangladesh

Bulletin of Electrical Engineering and Informatics, 2024-02-01

DOI: 10.11591/eei.v13i1.6073

Contributors: Johora Akter Polin, Nahid Hasan, Md. Tarek Habib, Atiqur Rahman, Zannatu Nayem Vasha, Bidyut Sharma

Publications (2020-2023)

A Machine Learning Approach for Driver Identification

Indonesian Journal of Electrical Engineering and Computer Science, 2023-04-01

DOI: 10.11591/ijeecs.v30.i1.pp276-288

Contributors: Md. Abbas Ali Khan, Mohammad Hanif Ali, Fazlul Haque, Md. Tarek Habib

Analysis of Recognition Performance of Plant Leaf Diseases Based on Machine Vision Techniques

Journal of Human, Earth, and Future, 2022-03-01

DOI: 10.28991/HEF-2022-03-01-09

Contributors: Imdadul Haque, Mohsin Alim, Mahbub Alam, Samia Nawshin, Sheak Rashed Haider Noori, Md. Tarek Habib

Machine Vision-Based Papaya Disease Recognition

Journal of King Saud University – Computer and Information Sciences, 2020-03

DOI: 10.1016/j.jksuci.2018.06.006

Contributors: Md. Tarek Habib, Anup Majumder, A.Z.M. Jakaria, Morium Akter, Mohammad Shorif Uddin, Farruk Ahmed

Conclusion:

Given his extensive publication record, research impact, and interdisciplinary contributions, Assist. Prof. Dr. Md. Tarek Habib is highly suitable for the Research for Best Researcher Award. His pioneering work in AI, ML, and IoT continues to drive innovation and technological advancements, making him a deserving recipient of this esteemed recognition.

 

 

 

Shohoni Mahabub | Computer Science | Industry-Driven Citation Excellence Award

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Ms. Shohoni Mahabub | Computer Science | Industry-Driven Citation Excellence Award

Ms. Shohoni Mahabub, Washington Glass, United States

Ms. Shohoni Mahabub is a highly motivated and results-driven professional with a diverse academic background and extensive experience in business analysis, project management, and data-driven decision-making. She currently serves as a Trainee Business Analyst at Washington Glass & Window Repair in Virginia, USA, where she plays a critical role in identifying and resolving process gaps, performing root cause analysis, and enhancing business operations. Her expertise includes data interpretation, quality control, IVR system optimization, and user support through data visualization tools such as Power BI, Tableau, and Spotfire. Shohoni’s proactive approach, attention to detail, and ability to see the “big picture” have enabled her to effectively collaborate with cross-functional teams and manage complex projects.

Education:

Ms. Shohoni Mahabub holds a Master of Science in Information Technology from Washington University of Science & Technology, Tysons Corner, VA (December 2023). She also earned an MBA in Human Resources Management from East West University, Dhaka, Bangladesh (April 2017), and a BBA in Accounting and Business Management from Heriot Watt University, Edinburgh, Scotland, UK (April 2014). Her academic background is complemented by a Higher Diploma in Accounting from the Scottish Qualification Authority (December 2012).

Professional Profiles:

Google Scholar

Professional Experience:

As a Trainee Business Analyst at Washington Glass & Window Repair, Virginia, USA (September 2024 – ongoing), Ms. Mahabub has demonstrated her ability to:

Identify and resolve process gaps through root cause analysis.

Interpret complex data and communicate insights to stakeholders.

Optimize workflows, particularly for IVR systems, and implement enhancements.

Collaborate cross-functionally, conduct user acceptance testing (UAT), and perform cost-benefit analysis.

Skills and Expertise:

Ms. Mahabub has a broad skill set, including:

Database Management

Project Management

Business Writing and Correspondence

Risk and Conflict Management

Presentation Development

Interpersonal Communication

She also has expertise in data visualization tools like Power BI, Tableau, and Spotfire, which are valuable for data-driven research.

Certifications and Professional Development:

Ms. Mahabub has completed several certifications, including:

Certified Business Analyst Professional (CBAP) – IIBA

Certification in Business Data Analyst (CBDA) – IIBA

Professional Business Analysis (PBA) – PMI

Business Analyst and Project Manager Collaboration – PMI and LinkedIn Learning

Talking to AI: Prompt Engineering – PMI

Generative AI Overview – PMI

She is also pursuing a “Business Analyst Program” from Harvard Business University and has completed a course on “Business Analyst with Agile Scrum” from PeopleNTech Institute of Technology.

Professional Memberships:

Ms. Mahabub is an active member of several prestigious organizations, including:

International Institute of Business Analysts (IIBA)

Project Management Institute (PMI)

IEEE (the world’s largest technical professional organization)

International Association of Professional Organizations (IAPO)

American Society of Administrative Professionals (ASAP)

Publications:

“Object detection and classification of tomato leaf disease using advanced deep learning model”

“AI in symptom analysis: Differentiating Monkeypox from Other Viral Infections Journal”

“Accelerating Digital Transformation: Strategies for Utilizing Generative AI to Create Value and Transform
Company Operations”

“Redefining Data-Driven Decision Making: Generative AI as a Catalyst for Smarter Business Analytics”

Conclusion:

Ms. Shohoni Mahabub is a highly motivated and skilled professional with significant potential for contributing to industry-driven research and innovation. Her technical expertise, academic background, and certifications position her as a strong candidate for future recognition. However, to fully align with the Research for Industry-Driven Citation Excellence Award, she should focus on increasing her research output, contributing to peer-reviewed publications, and enhancing her community engagement through mentoring or knowledge dissemination initiatives.

 

 

 

 

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