Mr. Ayush Roy | Computer Vision | Young Researcher Award

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

 

 

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Dr. Aiai Wang | Machine Learning | Best Researcher Award

Doctoral student, University of Science and Technology Beijing, China

Ai-Ai Wang is a passionate and dedicated young researcher born in March 1998 in Langfang, Hebei Province, China. A proud member of the Communist Party of China (CPC), she is currently based at the University of Science and Technology Beijing (USTB), where she serves as the Secretary of the 16th Party Branch, 4 Zhaizhai. With a solid academic foundation in mining and civil engineering, Ai-Ai has excelled in both academic and research spheres, contributing significantly to digital and intelligent mining technologies. Her work emphasizes physical dynamics in tailings sand cementation and filling, showing strong potential for innovation in sustainable mining practices.

Publication Profile

Scopus

🎓Education Background:

Ai-Ai Wang completed her Bachelor of Science in Mining Engineering from North China University of Science and Technology in 2021. She further pursued her Master’s degree in Civil Engineering at the University of Science and Technology Beijing (2021.09–2024.06), affiliated with the School of Civil and Resource Engineering.

🛠️Professional Experience:

Alongside her academic journey, Ai-Ai has undertaken significant responsibilities, currently serving as Secretary of the Party Branch at USTB. Her leadership extends beyond administration into collaborative research projects, software development, and patent contributions under renowned mentors such as Prof. Cao Shuai. She has played vital roles in developing intelligent systems for mining operations, reinforcing her multidisciplinary strengths.

🏅Awards and Honors:

Ai-Ai Wang has been recognized extensively for her academic and research excellence. Notable accolades include the “Top Ten Academic Stars” at USTB (2023), a National Scholarship for Master’s Degree Students (2022), the prestigious Taishan Iron and Steel Scholarship (2023), and multiple First-Class Academic Scholarships from USTB. She was twice named an Outstanding Three-Good Graduate Student and honored by her school as an outstanding individual. Moreover, she has received scientific awards such as the First Prize from the China Gold Association and the Second Prize from the China Nonferrous Metals Industry for her impactful contributions to green and safe mining.

🔬Research Focus:

Ai-Ai Wang’s research is rooted in advanced techniques of tailings sand cementation, intelligent filling systems, and digital mining. She explores the structural stability of backfills, application of nanomaterials, and CT-based 3D modeling of internal structures. Her work blends civil engineering, environmental safety, and digital innovation, aiming to enhance sustainability and efficiency in modern mining. She also contributes to cutting-edge software systems and patented technologies for mining design and operation support.

📝Conclusion:

Ai-Ai Wang stands out as a promising engineer and researcher whose academic achievements, professional dedication, and innovative research in intelligent mining set a high standard for future civil and mining engineers. Her trajectory reflects not just technical mastery but a deep commitment to sustainable and smart engineering solutions in the mining industry.

📚Top Publications with Details

Effect of height to diameter ratio on dynamic characteristics of cemented tailings backfills with fiber reinforcement through impact loading – Construction and Building Materials, 2022
Cited by: 26 articles
Influence of types and contents of nano cellulose materials as reinforcement on stability performance of cementitious tailings backfill – Construction and Building Materials, 2022
Cited by: 20 articles
Quantitative analysis of pore characteristics of nanocellulose reinforced cementitious tailings fills using 3D reconstruction of CT images – Journal of Materials Research and Technology, 2023
Cited by: 12 articles

 

Mr. Alvaro Martinez Ballester | Computer vision | Best Researcher Award

Mr. Alvaro Martinez Ballester | Computer vision | Best Researcher Award

PhD researcher, Miguel Hernández University, Spain

Álvaro Martínez Ballester is a dedicated researcher in the fields of robotics, automation, and deep learning 🤖🎓. Currently working at Universidad Miguel Hernández de Elche as Research Personnel, he specializes in detecting and recognizing dynamic elements using 3D LiDAR and deep learning techniques. His work focuses on improving environmental mapping by eliminating moving objects, making maps more robust and reliable. With a strong academic background and hands-on experience, Álvaro is actively engaged in developing solutions that enhance the capabilities of mobile robotics and autonomous systems 🚀🔬.

Publication Profile

ORCID

🎓 Education

Álvaro holds a Bachelor’s degree in Electronic Engineering and Industrial Automation from Miguel Hernández University of Elche (2021) and a Master’s degree in Robotics from the same university (2022) 🎓🔍. His academic journey is marked by excellence, having achieved a perfect 10/10 score for both his Final Degree and Master’s projects. His research focused on EOG artifact removal in EEG signals and 3D LiDAR-based object detection using deep learning, demonstrating his strong analytical and technical skills 💡📊.

💼 Experience

With a solid foundation in research and industry applications, Álvaro has worked extensively with ROS modules, SLAM, and autonomous robotics 🤖. His previous roles at Universidad Miguel Hernández de Elche include Research Staff, Specialist Technician, and Intern, where he contributed to the development of mapping, control algorithms, and sensor integration for mobile robots 🚀. His expertise in deep learning for object detection and environmental mapping has been instrumental in advancing autonomous robotic navigation 🌍🤖.

🏆 Awards and Honors

Álvaro has demonstrated exceptional academic and research achievements, securing perfect scores (10/10) in his Bachelor’s and Master’s final projects 🏅📚. His dedication to scientific advancements in robotics and automation has positioned him as a promising researcher in the field. His research contributions are being recognized through his work on funded R&D projects and his involvement in cutting-edge LiDAR-based perception systems 🏆🔬.

🔬 Research Focus

Álvaro’s primary research revolves around deep learning for autonomous systems, LiDAR-based perception, and robotic mapping 🚀📡. He is particularly interested in developing advanced algorithms to filter out dynamic elements in real-time, ensuring more reliable environmental understanding for autonomous robots. His work integrates AI, robotics, and sensor fusion, paving the way for future advancements in self-driving technologies and intelligent automation 🤖💡.

🔍 Conclusion

Álvaro Martínez Ballester is a rising expert in robotics, automation, and AI-driven perception 🤖🚀. With a strong academic foundation, hands-on research experience, and innovative contributions to robotic vision and mapping, he is shaping the future of autonomous systems. His work not only advances robotic intelligence but also enhances real-world applications in autonomous navigation and environmental modeling 🌍🔬.

📚 Publication

A Method for the Calibration of a LiDAR and Fisheye Camera SystemApplied Sciences

2025-02-15 | journal-article