Yinlei Cheng | Computer Vision | Best Researcher Award

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Dr. Yinlei Cheng | Computer Vision | Best Researcher Award

Beijing Institute Of Fashion Technology | China

Dr. Yinlei Cheng is a dedicated postgraduate researcher at the Beijing Institute of Fashion Technology, specializing in artificial intelligence and innovative design. With a strong academic foundation in engineering and computing, he has developed expertise in deep learning, computer vision, and intelligent image processing. His research journey is marked by active involvement in collaborative projects bridging academia and industry, where he has focused on real-world challenges such as intelligent fabric recognition and fault diagnosis systems. Driven by a passion for research and innovation, he continues to explore advanced computational methods that contribute to both theoretical understanding and practical applications.

Publication Profile

Scopus

Education Background

Dr. Yinlei Cheng completed his undergraduate engineering studies at Shandong Jiaotong University, where he established a strong base in technology and problem-solving. He is currently pursuing a master’s degree at the School of Liberal Arts and Sciences, Beijing Institute of Fashion Technology, advancing his academic career with a focus on artificial intelligence applications. His educational path highlights a consistent pursuit of excellence, blending technical knowledge with practical applications in computer vision and image processing. Through this background, he has been able to integrate academic learning with innovative research contributions, strengthening his expertise in both theory and practice.

Professional Experience

Dr. Yinlei Cheng has been actively engaged in research-driven projects with direct industry relevance, showcasing his ability to apply cutting-edge methods to solve complex problems. His work on the intelligent fabric piece grasping system demonstrated his skill in combining deep learning and machine vision for non-rigid object recognition and automation. He also contributed to developing a portable fault diagnosis software system designed to provide real-time monitoring and predictive analysis of industrial equipment. These experiences reflect his growing professional maturity and highlight his potential to bridge academic research with practical industry solutions, ensuring his contributions have both scientific and applied value.

Awards and Honors

While Dr. Yinlei Cheng is still at an early stage in his research career, he has already achieved recognition through his publication in a peer-reviewed international journal indexed in high-ranking databases. His academic contributions, particularly in advancing activation functions for convolutional neural networks, have been cited by other researchers, reflecting the growing impact of his work. His dedication to refining theoretical insights and combining them with rigorous experimental validation has positioned him as a promising researcher. Although formal awards may not yet fully represent his contributions, his publication record and involvement in impactful projects underline his academic excellence.

Research Focus

The central focus of Dr. Yinlei Cheng’s research lies in computer vision, deep learning, and image processing, with a particular interest in designing intelligent systems for real-world applications. His work explores innovative activation functions to enhance the performance of convolutional neural networks, contributing both theoretical advancements and practical improvements. He also applies these concepts to industrial applications, such as automation in flexible manufacturing and predictive fault detection systems. By balancing theoretical depth with practical deployment, his research adds value to both academia and industry. His ongoing efforts aim to extend these methodologies to more advanced architectures and transformative technologies.

Publication Notes

Title: A Periodic Mapping Activation Function: Mathematical Properties and Application in Convolutional Neural Networks
Published Year: 2025
Citation: 1

Conclusion

Dr. Yinlei Cheng’s academic journey reflects a balance of solid educational grounding, active participation in significant projects, and meaningful contributions to the field of artificial intelligence. His work demonstrates the ability to translate theoretical research into applied solutions that address complex industry challenges. With an expanding publication record and growing recognition, he shows strong potential to emerge as a leading researcher in computer vision and deep learning. His commitment to rigorous research, clarity in academic writing, and focus on future innovations position him as a deserving candidate for recognition in the Best Researcher Award category.

GuoXin Chen | Image Processing | Best Researcher Award

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Dr. GuoXin Chen | Image Processing | Best Researcher Award

Dr. GuoXin Chen | Zhejiang University | China

Guoxin Chen is a prominent Chinese geophysicist specializing in marine seismic exploration, currently serving as a researcher at the Ocean College of Zhejiang University. With a strong foundation in both mathematics and geophysics, he has developed innovative techniques in seismic waveform inversion, imaging, and artificial intelligence-driven data processing. He has held various academic roles in China and internationally, including at the University of California, Santa Cruz. In addition to his research, he is an editorial board member of several SCI-indexed journals and contributes as a reviewer for top-tier publications. His scholarly work is widely recognized in the geophysical research community.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Guoxin Chen completed his Ph.D. in Geophysics from Zhejiang University, one of China’s leading institutions in scientific research. His academic journey began with a Bachelor’s degree in Mathematics from Shandong University, Jinan, where he built a strong analytical foundation that later enriched his work in geophysics. His interdisciplinary academic background enabled him to approach seismic imaging and inversion with a unique combination of theoretical precision and practical problem-solving skills, contributing to significant advances in marine geophysical research methodologies.

Professional Experience

Guoxin Chen has accumulated extensive experience in geophysics through academic and research roles both in China and the United States. He currently works as a researcher at the Ocean College of Zhejiang University and previously served as an associate researcher and postdoctoral scholar in the same institution. Internationally, he has been affiliated with the Modeling & Imaging Lab at the University of California, Santa Cruz, holding roles from project assistant researcher to junior researcher. His professional appointments include serving as a distinguished expert with BGP, CNPC, and as a guest editor and board member for several prominent journals.

Awards and Honors

Guoxin Chen has been recognized for his contributions to exploration geophysics with multiple prestigious academic appointments and research grants. He serves as a part-time distinguished expert for the Bureau of Geophysical Prospecting under CNPC. He also holds editorial positions in high-impact SCI journals such as Water, Symmetry, Petroleum Science, and Journal of Earth Science. He has served as a principal investigator and core researcher in numerous national-level and provincial research projects, highlighting his leadership in scientific innovation and research development in geophysics and related fields.

Research Focus

Guoxin Chen’s research primarily focuses on marine seismic exploration, especially seismic wave full waveform inversion, reverse time migration imaging, and the application of AI in geophysical data processing. He aims to improve imaging accuracy and efficiency for complex geological structures, such as salt bodies and sub-seafloor sediments. His recent work integrates deep learning algorithms into conventional geophysical workflows, offering enhanced solutions for noise reduction, model building, and data interpretation. His work has significantly contributed to advancements in both academic geophysics and practical seismic exploration technologies.

Top Publications

Efficient Seismic Data Denoising via Deep Learning with Improved MCA-SCUNet
Published Year: 2024
Cited by: 14

Joint Model and Data-Driven Simultaneous Inversion of Velocity and Density
Published Year: 2024
Cited by: 12

Salt Structure Elastic Full Waveform Inversion Based on the Multi-scale Signed Envelope
Published Year: 2022
Cited by: 38

Application of Envelope in Salt Structure Velocity Building
Published Year: 2020
Cited by: 55

Multi-scale Direct Envelope Inversion: Algorithm and Methodology for Application to the Salt Structure Inversion
Published Year: 2019
Cited by: 42

Conclusion

Guoxin Chen stands as a distinguished figure in the field of exploration geophysics with a career marked by academic excellence, groundbreaking research, and international collaboration. His fusion of mathematical insight, geophysical expertise, and cutting-edge artificial intelligence places him at the forefront of seismic imaging research. Through numerous publications, editorial contributions, and funded projects, he continues to influence the direction of marine seismic data processing and inversion technologies. His work not only contributes to academic knowledge but also addresses real-world challenges in geophysical exploration and energy resource discovery.

 

Prof. Dr. Mohamed Maher Ben Ismail | Artificial Intelligence | Best Researcher Award

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Prof. Dr. Mohamed Maher Ben Ismail | Artificial Intelligence | Best Researcher Award

Prof. Dr. Mohamed Maher Ben Ismail, King Saud University, Saudi Arabia

Dr. Mohamed Maher Ben Ismail is a distinguished full professor in the Computer Science Department at the College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia . With a prolific academic and research background spanning over two decades, Dr. Ben Ismail is recognized for his contributions in artificial intelligence, image processing, and data mining. His work bridges theory and practical applications in machine learning and statistical modeling, making him a leading voice in his field 🌐📚.

Professional Profile

Google Scholar

Scopus

🎓 Education Background

Dr. Ben Ismail holds a Ph.D. in Computer Engineering and Computer Science from the University of Louisville, USA (2011) 🇺🇸, where his dissertation focused on image annotation and retrieval using multi-modal feature clustering. He also earned a Master’s in Automatic and Signal Processing and a Bachelor’s in Electrical Engineering from the National School of Engineering of Tunis, Tunisia 🇹🇳. His early academic journey was distinguished by excellence in mathematics, physics, and competitive engineering entrance exams 🧠📘.

🧑‍🏫 Professional Experience

Dr. Ben Ismail currently serves as a Full Professor at King Saud University (2021–present), following roles as Associate Professor (2017–2021) and Assistant Professor (2011–2017). Previously, he worked as a Design & Development Engineer at STMicroelectronics, Tunisia, and as a Graduate Research Assistant at the University of Louisville’s Multimedia Research Lab, where he pioneered work on CBIR systems and integrated machine learning approaches. His academic role includes supervising thesis work, lecturing across AI, ML, algorithm design, and image processing 💼👨‍🏫.

🏆 Awards and Honors

Throughout his career, Dr. Ben Ismail has received numerous accolades, including the Best Faculty Member Award (2017) at King Saud University, the Graduate Dean’s Citation Award (2011), and the IEEE Outstanding CECS Student Award (2011) 🥇. He is also a member of the Golden Key International Honor Society and received early recognition through his promotion at STMicroelectronics and various graduate assistantships and scholarships 🎖️.

🔬 Research Focus

Dr. Ben Ismail’s research interests lie in Artificial Intelligence, Machine Learning, Pattern Recognition, Image Processing, Temporal Data Mining, and Information Fusion 🤖🧠. His work emphasizes robust statistical modeling and intelligent systems design, often applied to domains like IoT security, brain tumor detection, real estate prediction, and hyperspectral imaging. His prolific publication record in top-tier journals and conferences highlights his continuous contributions to advanced computational techniques and interdisciplinary innovation 📊📈.

📌 Conclusion

With a solid educational foundation, impactful research contributions, and extensive teaching experience, Dr. Mohamed Maher Ben Ismail stands as a key figure in advancing AI-driven solutions in academia and industry. His dedication to excellence and innovation marks him as a thought leader and an inspirational academic voice in the global computer science community 🌟🧑‍🔬.

📚 Top Publications Notes

  1. YOLO-Act: Unified Spatiotemporal Detection of Human Actions Across Multi-Frame Sequences
    📅 Published in: Sensors, 2025
    🔍 Cited by: 12 articles (as of mid-2025)
    🧠 Highlights: Proposes a YOLO-based system for recognizing actions across video frames.

  2. MRI-Based Meningioma Firmness Classification Using an Adversarial Feature Learning Approach
    📅 Published in: Sensors, 2025
    🔍 Cited by: 9 articles
    🧠 Highlights: Enhances brain tumor classification using deep adversarial networks.

  3. RobEns: Robust Ensemble Adversarial Machine Learning Framework for Securing IoT Traffic
    📅 Published in: Sensors, 2024
    🔍 Cited by: 18 articles
    🔐 Highlights: Focuses on adversarial ML methods to enhance IoT network security.

  4. Skin Cancer Recognition Using Unified Deep Convolutional Neural Networks
    📅 Published in: Cancers, 2024
    🔍 Cited by: 25 articles
    🧬 Highlights: Applies CNNs to early skin cancer detection using medical images.

  5. A Deep Learning Approach for Brain Tumor Firmness Detection Based on Five YOLO Versions
    📅 Published in: Computation, 2024
    🔍 Cited by: 14 articles
    💡 Highlights: Compares YOLOv3 to YOLOv7 models for brain scan interpretation.

  6. Toward an Improved Machine Learning-based Intrusion Detection for IoT Traffic
    📅 Published in: Computers, 2023
    🔍 Cited by: 20 articles
    🔒 Highlights: Develops a secure ML framework to prevent intrusions in smart devices.

  7. Simultaneous Deep Learning-based Classification and Regression for Company Bankruptcy Prediction
    📅 Published in: Journal of Business & Economic Management, 2023
    🔍 Cited by: 8 articles
    💼 Highlights: Innovative DL model integrating financial classification with regression.

  8. Novel Dual-Constraints Based Semi-Supervised Deep Clustering Approach
    📅 Published in: Sensors, 2025
    🔍 Cited by: 6 articles
    📊 Highlights: Enhances clustering accuracy using semi-supervised constraints in DL.

  9. Better Safe than Never: A Survey on Adversarial Machine Learning Applications towards IoT Environment
    📅 Published in: Applied Sciences, 2023
    🔍 Cited by: 22 articles
    🔍 Highlights: Comprehensive survey exploring adversarial ML attacks and defense for IoT.

  10. Detecting Insults on Social Network Platforms Using a Deep Learning Transformer-Based Model
    📅 Published in: IGI Global Book Chapter, 2025
    🔍 Cited by: 11 articles
    🌐 Highlights: Uses transformer models to detect hate speech and insults online.

 

Mr. Ayush Roy | Computer Vision | Young Researcher Award

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Mr. Ayush Roy | Computer Vision | Young Researcher Award

PhD, University at Buffalo, United States

Ayush Roy is an emerging researcher and innovator in the field of Electrical Engineering with a deep interest in AI, computer vision, and biomedical image analysis. Currently pursuing his B.E. at Jadavpur University, he has demonstrated exceptional potential through interdisciplinary research, AI-driven solutions, and impactful contributions to both academia and real-world applications. With multiple international publications and recognitions, Ayush is a dynamic force in the intersection of deep learning, signal processing, and intelligent systems.

Publication Profile

Google Scholar

🎓 Education Background

Ayush Roy is a final-year undergraduate student at Jadavpur University, West Bengal, India, enrolled in the Bachelor of Engineering (Electrical) program with an SGPA of 8.1/10 (2020–2024). He completed his schooling from Bhartiya Vidya Bhavan, West Bengal under the CBSE board, scoring 90.6% in Class 12 and a perfect CGPA of 10 in Class 10.

💼 Professional Experience

Ayush’s research journey began at Jadavpur University, working under renowned professors in Audio Signal Processing, Reinforcement Learning, and Image Segmentation. As a research intern at the Indian Statistical Institute, he contributed to dataset development and text detection models. He furthered his research as an intern at the University of Malaya on transformer-based networks and at IISc Bangalore on CLIP for image quality assessment. His work integrates deep learning models like YOLO, Swin Transformer, UNet, and CLIP with novel architectures and real-world applications.

🏆 Awards and Honors

Ayush has earned several accolades such as the Most Innovative Solution award at Hack-a-Web by NIT Bhopal (2021), 3rd Prize at FrostHack, IIT Mandi (2022), Top 10 in Cloud Community Hackday by GDG Cloud, and became a Finalist in both the IEEE R10 Robotics Competition and 404 Resolved hackathon at IIT Delhi.

🔬 Research Focus

His primary research areas include computer vision, medical image segmentation, scene text detection, and real-time AI systems. He is especially focused on lightweight models, attention mechanisms, domain adaptation, and hybrid approaches combining deep learning and signal processing. He has created multiple datasets for benchmarking including those for drone license plate detection, underwater text, water meter digit recognition, and circuit component recognition.

📌 Conclusion

Ayush Roy stands as a committed and creative researcher, blending electrical engineering fundamentals with cutting-edge AI methodologies. His work not only adds value to academic literature but also paves the way for practical, socially impactful AI systems. With an impressive early-career portfolio, Ayush continues to show immense promise for future contributions to science and technology.

📚 Top Publication Notes 

AWGUNet: Attention-aided Wavelet Guided U-net for nuclei segmentation in histopathology images

Year: 2024

Journal/Conference: ISBI 2024

Cited By: 2 articles (Google Scholar)

A Wavelet Guided Attention Module for Skin Cancer Classification

Year: 2024

Journal/Conference: ISBI 2024

Cited By: 1 article (Google Scholar)

A New Lightweight Attention-based Model for Emotion Recognition Using Distorted Social Media Images

Year: 2023

Journal/Conference: ACPR 2023

Cited By: 3 articles

Fourier Feature-based CBAM and Vision Transformer for Text Detection in Drone Images

Year: 2023

Conference: ICDAR WML 2023

Cited By: 1 article

A Lightweight Script Independent Scene Text Style Transfer Network

Year: 2024

Journal: International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)

Cited By: 1 article

Identification and Classification of Human Mental Stress using Physiological Data

Year: 2022

Conference: IEEE CATCON 2022

Cited By: 4 articles

Adapting a Swin Transformer for License Plate Number and Text Detection in Drone Images

Year: 2023

Journal: Artificial Intelligence and Applications (AIA)

Cited By: 2 articles

An Attention-based Fusion of ResNet50 and InceptionV3 Model for Water Meter Digit Recognition

Year: 2023

Journal: Artificial Intelligence and Applications (AIA)

Cited By: 1 article

DAU-Net: Dual Attention-aided U-Net for Segmenting Tumor Region in Breast Ultrasound Images

Year: 2023

Journal: PLOS ONE

Cited By: 6 articles

 

 

Mr. Kostas Ordoumpozanis | Computer Vision | Best Researcher Award

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Mr. Kostas Ordoumpozanis | Computer Vision | Best Researcher Award

Phd Cand. Department of Cultural Technology and Communication, University of the Aegean Greece, Greece

Kostas Ordoumpozanis is a dynamic AI researcher, developer, and educator specializing in multi-agent AI systems 🤖. Currently a PhD candidate at the University of the Aegean, Greece, his expertise spans AI-driven automation, large language models (LLMs), retrieval-augmented generation (RAG), and AI-human collaboration. With a background in mechanical engineering and over a decade of experience in full-stack development, AR, and creative technology, he blends technical proficiency with artistic innovation. Kostas is also an entrepreneur, recognized for his startup ventures in AI and augmented reality, making significant contributions to AI-driven storytelling, gamification, and sustainable design 🌍.

Publication Profile

ORCID

🎓 Academic Background

Kostas holds a 5-year Mechanical Engineering degree from the University of Western Macedonia, Greece (2005) 🏗️. He pursued PhD research on hybrid ventilated PV facades at the same institution (2006-2021) and is currently completing an MPhil in Computer Science & AI at the International Hellenic University (2023-present) 🎓. His latest research focuses on AI multi-agent systems as part of his PhD at the University of the Aegean (2024-present), further cementing his expertise in AI agency and intelligent automation.

💼 Professional Experience

With a diverse career spanning multiple domains, Kostas worked as a mechanical engineer and sustainable design simulation expert (2006-2016) before transitioning into digital arts, photography, and cinematography (2013-2020) 🎥. His entrepreneurial journey includes founding a startup specializing in augmented reality (2016-2024) and serving as a skills educator (2008-2023) 📚. Since 2018, he has been a full-stack developer, focusing on AI applications, web technologies, and vector databases. Currently, he is an AI researcher and developer working on LLMs, AI agents, and human-machine collaboration 🤖.

🏆 Awards and Honors

Kostas has received numerous accolades, including recognition as a “Rising Start-Up Business” from the Evros Chamber, Greece (2023) 🚀. He secured first place in the EU Interreg Greece-Bulgaria Startup Contest (2023) and was a finalist in the Athens StartUp Awards (2018) and XR COSMOS Greece (2021). His innovative contributions earned him a patent recognition in Greece (2018) 🏅.

🔬 Research Focus

His research revolves around AI agentic systems, LLM optimization, RAG architectures, and AI-driven storytelling 🧠. He explores the intersection of generative AI, human-computer collaboration, and augmented reality for educational and creative applications. His work also extends to sustainable AI, assessing the carbon footprint of deep learning models and developing efficient AI architectures for various domains.

📝 Conclusion

Kostas Ordoumpozanis is a visionary AI researcher and innovator, merging technical expertise with creative problem-solving. His contributions to AI agents, storytelling, and sustainable AI showcase his commitment to pushing technological boundaries. With a strong academic foundation, industry experience, and entrepreneurial mindset, he continues to shape the future of AI-driven systems and human-machine interaction 🌍.

📚 Top Research Publications

Reviewing 6D Pose Estimation: Model Strengths, Limitations, and Application Fields (2025) – Applied Sciences
Cited by: Multiple AI research articles

Green AI: Assessing the Carbon Footprint of Fine-Tuning Pre-Trained Deep Learning Models in Medical Imaging (2024) – 3ICT Conference, Bahrain
Cited by: Research in sustainable AI and medical imaging

C-LINK Agent: Connecting Social Media Post Generation with Recommender Systems (2024) – SMAP 2024 Conference
Cited by: Works in AI-driven social media automation

A Second-Generation Agentic Framework for Generative AI-Driven Augmented Reality Educational Games” (2025) – EDUCON Conference
Cited by: Research in AI and AR-driven education

Energy, Comfort, and Indoor Air Quality in Nursery and Elementary School Buildings in the Cold Climatic Zone of Greece” (Published in Energy and Buildings)
Cited by: Sustainability and green architecture studies

Energy and Thermal Modeling of Building Façade Integrated Photovoltaics” (Published in Thermal Science)
Cited by: Research in sustainable energy and architecture

VINOD KUMAR VERMA | Computer Science | Best Researcher Award

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Assist Prof Dr. VINOD KUMAR VERMA | Computer Science | Best Researcher Award

Assistant Professor, Sant Longowal Institute of Engineering and Technology, Longowal, India

👨‍🏫 Dr. Vinod Kumar Verma was born in Kalka, Haryana, India. He is an esteemed Assistant Professor in the Department of Computer Science and Engineering at SLIET-Deemed to be University. With international teaching and research experience, he has contributed significantly to various academic and research institutions worldwide, including the UK, USA, Japan, Italy, Australia, France, and Greece. Dr. Verma has collaborated with prestigious universities such as the University of Surrey, England, and the University of Nottingham, Malaysia. He has published extensively in renowned international journals, making notable contributions to the fields of wireless sensor networks, IoT, big data, cloud computing, and more.

Profile

Scopus

🎓 Education

BTech in Computer Engineering from Kurukshetra University, 2005. MS Degree from BITS Pilani, Pilani, 2008. PhD in Computer Science and Engineering from Sant Longowal Institute of Engineering and Technology (SLIET), Longowal, India

💼 Experience

Dr. Verma has held various academic positions and has been involved in numerous international collaborations. His teaching and research engagements have taken him to countries such as the UK, USA, Japan, Italy, Australia, France, and Greece. He has worked with the University of Surrey, England, and visited the University of West Attica, Athens, Greece under the ERASMUS+ program. Dr. Verma is currently an Assistant Professor at SLIET-Deemed to be University.

🔍 Research Interests

Dr. Verma’s research interests are diverse and cutting-edge, including wireless sensor networks, the internet of things (IoT), big data, cloud computing, trust and reputation systems, simulation, distributed computing, cryptography, and software systems. His work has been published in various top-tier international journals, showcasing his significant contributions to these fields.

🏆 Awards

Dr. Verma has been recognized for his outstanding contributions to the field of computer science. He received the Session’s Best Paper Award at IMETI-CITSA-2014 in Orlando and the Best Paper Award at NCCN-11 in Longowal in 2011. He has also served on numerous organizing and program committees for international conferences, highlighting his influence and leadership in the academic community.

📚 Publications

Cooperative-centrality enabled investigations on edge-based trustworthy framework for cloud focused internet of things