Yang zhang | Computer Vision | Best Researcher Award-duplicate-1

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Dr. Saikat Biswas | Operations Research and Statistical Optimization | Best Researcher Award

IIT Roorkee | India

Dr. Saikat Biswas is an Indian chemical engineer and academic whose research primarily focuses on computational fluid dynamics (CFD), multiphase flow, and microfluidics, with a special emphasis on droplet dynamics including breakup, splitting, and the transition from dripping to jetting in complex microchannel geometries. He earned his PhD in Chemical Engineering from the Indian Institute of Technology Guwahati (2016–2023), where his doctoral work investigated droplet breakup dynamics in confined microscale flows, and previously completed both his M.Tech and B.Tech in Chemical Engineering at the National Institute of Technology Agartala. Throughout his academic journey, he has published 14 documents, accumulating 41 citations and achieving an h-index of 3, reflecting his growing impact in the field. His contributions include both numerical and computational studies, such as two-dimensional and three-dimensional simulations of droplet splitting at T-junctions and multifurcating channels, investigations of flow-focusing geometries, and analyses of the role of viscosity ratio, surface tension, and channel design in influencing microfluidic droplet behaviour. Skilled in advanced tools such as ANSYS Fluent, COMSOL Multiphysics, OpenFOAM, and MATLAB, he integrates computational methods with engineering applications to address fundamental and applied challenges. Recognized as hard-working, adaptable, and collaborative, Biswas continues to contribute to the advancement of microfluidics and multiphase flow research.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

“Digital electronic based portable device for colorimetric quantification of ketones and glucose level in human urine”

“Droplet splitting in multifurcating microchannel: A three-dimensional numerical simulation study”

“3D simulation of dripping and jetting phenomena in a flow-focusing geometry”

“A computational study on transition mechanism of dripping to jetting flow in a flow focusing geometry”

“Influence of microchannel geometry on droplet breakup dynamics: A computational study”

Yang zhang | Computer Vision | Best Researcher Award

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Dr. Yang zhang | Computer Vision | Best Researcher Award

Yang Zhang is a Lecturer at the School of Computer Science and Engineering, Nanjing University of Science and Technology. She earned her PhD in Control Science and Engineering from Southeast University and was a visiting researcher at the Australian Artificial Intelligence Institute, University of Technology Sydney. Her research focuses on face image and video super-resolution, face recognition, illumination normalization, and three-dimensional face reconstruction. She has published extensively in top journals and conferences such as IEEE TPAMI, IEEE TIP, and CVPR. A recipient of national and institutional scholarships, her work is widely recognized and cited by leading universities and industry labs worldwide.

Dr. Yang zhang | Nanjing University of Science and Technology | China

Profiles

SCOPUS

GOOGLE SCHOLAR

Education

  • Yang Zhang received her doctoral degree in Control Science and Engineering from Southeast University in Nanjing, China. During her doctoral studies, she gained international exposure as a visiting student at the Australian Artificial Intelligence Institute, University of Technology Sydney, under the supervision of Professor Ivor W. Tsang. This academic journey provided her with a strong foundation in artificial intelligence, computer vision, and advanced image processing methods.

Experience

  • Yang Zhang is currently a Lecturer at the School of Computer Science and Engineering, Nanjing University of Science and Technology. She has previously worked on research collaborations at the University of Technology Sydney, where she deepened her expertise in artificial intelligence and machine learning. Her academic role has been complemented by her extensive publications in top journals and conferences, where her contributions have been recognized at the international level.

Awards and Recognition

  • Yang Zhang has been recognized for her academic excellence with prestigious scholarships. She received the China National Scholarship and the Nanjing Artificial Intelligence Project Scholarship, both awarded for her outstanding research and contributions to the field of computer vision. These awards highlight her dedication to innovation and her ability to contribute meaningfully to the global research community.

Skills and Expertise

  • Her skills lie at the intersection of artificial intelligence, computer vision, and image processing. She specializes in designing and implementing deep learning architectures for face image super-resolution, video super-resolution, and face recognition under challenging conditions. Yang Zhang is skilled in integrating prior knowledge into deep learning frameworks to achieve robust feature representation, visual quality enhancement, and structural fidelity. She also demonstrates strong expertise in handling issues such as illumination normalization, pose variation, and occlusion restoration.

Research Focus 

  • Yang Zhang’s research is centered on advancing face image super-resolution, face recognition, and three-dimensional face reconstruction under extreme conditions. She has developed innovative models for illumination removal, non-local style transfer super-resolution, pose correction, and progressive restoration. Her work bridges deep learning with traditional image processing to address real-world challenges. Her contributions have set benchmarks in the field and are widely recognized and cited by leading academic institutions and industry research labs globally.

Publications

  • Recursive Copy and Paste GAN: Face Hallucination From Shaded Thumbnails
    Authors: Y Zhang, IW Tsang, Y Luo, C Hu, X Lu, X Yu
    Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence

    Copy and Paste GAN: Face Hallucination From Shaded Thumbnails
    Authors: Y Zhang, IW Tsang, Y Luo, CH Hu, X Lu, X Yu
    Journal: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

    Face Hallucination With Finishing Touches
    Authors: Y Zhang, IW Tsang, J Li, P Liu, X Lu, X Yu
    Journal: IEEE Transactions on Image Processing

    IL-GAN: Illumination-invariant Representation Learning for Single Sample Face Recognition
    Authors: Y Zhang, C Hu, X Lu
    Journal: Journal of Visual Communication and Image Representation

    Face Illumination Recovery for the Deep Learning Feature Under Severe Illumination Variations
    Authors: CH Hu, J Yu, F Wu, Y Zhang, XY Jing, XB Lu, P Liu
    Journal: Pattern Recognition

Conclusion

  • Yang Zhang is an accomplished researcher and academic whose work in face recognition and image processing has had significant impact on both academia and industry. Her innovative methods have pushed the boundaries of face image analysis under challenging conditions, earning her recognition in top international venues. With a strong academic background, prestigious awards, and active membership in leading professional societies, she continues to shape the future of computer vision through groundbreaking research and collaboration.

Ciliang Shao | Computer Vision | Best Researcher Award

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Mr. Ciliang Shao | Computer Vision | Best Researcher Award 

Ciliang Shao is an undergraduate student of Computer Science and Technology at Sichuan University, Pittsburgh Institute. His research focuses on computer vision and pattern recognition, with contributions to projects on respiratory motion modeling, cross-modal MRI-TRUS registration, and three-dimensional scene generation. He has co-authored a publication, presented at academic conferences, and earned recognition on the Dean list. Through research projects and an internship at Zhejiang University, he has developed strong skills in deep learning, data processing, and medical imaging applications, reflecting his passion for innovation and commitment to advancing technology for real-world impact.

Mr. Ciliang Shao | Sichuan University | China

Profile

GOOGLE SCHOLAR

Education

  • Ciliang Shao is pursuing undergraduate studies in Computer Science and Technology at Sichuan University within the Pittsburgh Institute. His academic journey has been defined by a strong interest in computer vision and pattern recognition. During his studies, he has consistently demonstrated academic excellence, earning a place on the Dean list. His education has not only provided him with technical knowledge but has also nurtured his ability to engage in innovative research projects addressing real-world challenges

Experience

  • Ciliang Shao has gained valuable experience through participation in research projects and internships. He has contributed to studies on inter-subject lung respiratory motion modeling and cross-modal MRI-TRUS registration in prostate cancer, where he applied advanced frameworks such as E-CMCA and LSTM. In addition, he has worked on the generation of details for infinite three-dimensional scenes. His internship at Zhejiang University further strengthened his technical foundation and problem-solving abilities. These experiences have shaped his research outlook and deepened his commitment to advancing computer vision techniques.

Awards and Recognition

  • Recognition of his academic dedication came through inclusion in the Dean list, highlighting his consistent excellence and strong academic performance. His achievements in both coursework and research projects underscore his potential as a future researcher and innovator in his field.

Skills and Expertise

  • Ciliang Shao has developed strong skills in computer vision, pattern recognition, and deep learning techniques. He is proficient in designing and implementing frameworks for cross-modal data alignment and recognition. His ability to collaborate in group projects has enhanced his teamwork and communication skills, while his internship experience provided hands-on exposure to applying theoretical knowledge in practical settings. His research presentations and published work further reflect his ability to translate complex ideas into meaningful contributions.

Research Focus 

  • His research interests lie at the intersection of computer vision and pattern recognition. He focuses on developing innovative frameworks that enhance accuracy and efficiency in complex data processing tasks, particularly in medical imaging and healthcare applications. By exploring motion modeling and cross-modal data registration, his work aims to support more reliable diagnostic and treatment tools. He is also intrigued by the creative possibilities of generating detailed infinite three-dimensional scenes, expanding the scope of computer vision applications.

Publication

  • Inter-Subject Lung Respiratory Motion Modeling with Motion Artifacts Reduction
    Author: Ciliang Shao, Hejia Zhang, Jingjing He, Yang Ye, Kunpeng Wang
    Journal: Special session CIST

  • E-CMCA and LSTM-Enhanced Framework for Cross-Modal MRI-TRUS Registration in Prostate Cancer
    Author: Ciliang Shao, Ruijin Xue and Lixu Gu.
    Journal: Journal of Imaging (MDPI)

Conclusion

  • Ciliang Shao has demonstrated remarkable research potential through his contributions to computer vision and pattern recognition at an early stage of his academic journey. His work on medical imaging and three-dimensional scene generation reflects both innovation and practical impact. With strong academic achievements, research publications, and recognition such as the Dean list, he is highly suitable for the Best Researcher Award. Continued expansion of collaborations and deeper engagement with global research networks will further strengthen his academic trajectory and establish him as a future leader in his field.