CHENGJIE DAI | design | Best Researcher Award

Posted on 21/10/202421/10/2024 by 21b4bddf87157652317827146367558f

Dr.CHENGJIE DAI | design | Best Researcher Award

Dr, CHENGJIE DAI,Zhejiang University, China

Dr. Chengjie Dai is a prominent researcher from Zhejiang University, China. His work focuses on computational mechanics, structural optimization, and material design. With numerous publications in top-tier journals, Dr. Dai’s contributions advance the fields of mechanical engineering and computational simulation. He is recognized for innovative research integrating computational methods with practical engineering applications.

Summary:

Dr. Chengjie Dai has a strong educational background, demonstrated research capabilities, and practical experience that collectively position him as a leading candidate for the Research for Best Researcher Award. His focus on neural networks and image processing, along with his successful projects and publications, highlights his potential to influence the field positively.

Professional Profiles:

Scopus

🎓 Education :

Zhejiang University | School of Aeronautics and Astronautics | Ph.D. in Electronic Information
September 2020 – June 2025
Pursuing a Ph.D. in Electronic Information with a focus on neural network-based image compression. My research revolves around developing cutting-edge algorithms for optimizing image processing techniques, particularly within aerospace information technology. Under the guidance of Prof. Guanghua Song at the Institute of Aerospace Information Technology, I have been recognized as an Excellent Graduate Student for my academic achievements and contributions,University of Science and Technology Beijing | School of Mathematics and Physics | Bachelor’s in Mathematics and Applied Mathematics
September 2016 – June 2020,Graduated with a Bachelor’s degree in Mathematics and Applied Mathematics from the University of Science and Technology Beijing. I was actively involved in academic and extracurricular activities, earning honors such as Excellent League Member and two-time recipient of the Third-class Scholarship at USTB. My time here helped shape a strong foundation in mathematical theories and their application in real-world problem-solving

🏢 Experience:

Hikvision Digital Technology Co., Ltd. | Image Algorithm Engineer Intern
June 2024 – August 2024,Worked as an intern in the Video Algorithm and Circuit Department, focusing on codec development. I was involved in designing an H.265 proxy network for video pre-processing, encoding, and post-processing in IoT environments. My responsibilities included simulating the non-differentiable encoding/decoding process using proxy networks for gradient backpropagation, modifying HM source code, and creating algorithms to enhance image quality after encoding. My efforts contributed to significant improvements in intra-frame encoding performance,Smart Biomimetic Flapping-Wing UAV and Hybrid Swarm Intelligence | Compression Algorithm Development
June 2022 – Present,As part of a project focused on UAV technology, I developed a masked feature compression method for backend tasks, significantly reducing file size for small object detection while maintaining accuracy. This involved compressing low-level features extracted by edge devices (drones) using ROI prediction masks,SAIC Foundation | Mobile Edge Computing-Based Vehicle Network Services
February 2021 – October 2022,Led the development of a learnable downsampler–upsampler pair for image resolution scaling, reducing file size by 75% while retaining detection accuracy in mobile edge computing systems

🛠️Skills:

Programming Languages: Proficient in Python, C++, and PyTorch
Technical Proficiencies: Strong command of neural network image compression algorithms, experienced with the CompressAI framework and H.265 video compression standard
Software and Systems: Comfortable working in Linux environments, with proficiency in Git version control
Neural Network Architectures: Familiar with advanced models like Transformers and ResNet
Research Skills: Expertise in reading and analyzing English academic literature, with a focus on image compression and video encoding technologies,Languages: High proficiency in English, demonstrated by a score of 541 on the CET-6

Research Focus :

My research interests lie at the intersection of image compression and computer vision, with a particular focus on improving compression algorithms for high-level vision tasks. This includes image super-resolution, video encoding/decoding, and the development of proxy networks for standard video codecs. Additionally, I have explored applications in areas like satellite remote sensing and mobile edge computing, with projects addressing challenges in small object detection and hierarchical transformer-based image compression

🔬Awards:

Excellent Graduate Student of Zhejiang University
Third-Class Scholarship Recipient (twice) at the University of Science and Technology Beijing,Excellent League Member at the University of Science and Technology Beijing

Conclusion:

In conclusion, Dr. Dai’s combination of academic achievements, innovative research contributions, and industry experience make him a deserving candidate for the Research for Best Researcher Award. With continued focus on outreach, collaboration, and communication, he can further amplify his impact in the field of electronic information and contribute significantly to advancements in image compression and processing technologies.

Publications :

Masked Feature Compression for Object Detection
- Citation: Dai, C., Song, T., Jin, Y., Yang, B., & Song, G.
- Year: 2024
- Journal: Mathematics, 12(12), 1848

ChatLsc: Agents for Live Streaming Commerce
- Citation: Dai, C., Fang, K., Hua, P., & Chan, W.K.
- Year: 2024
- Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Computer Aided Design In Mechanical Engineering and Lecture Notes in Bioinformatics), 14735 LNAI, pp. 360–372

Optimizing Tutorial Design for Video Card Games Based on Cognitive Load Theory: Measuring Game Complexity
- Citation: Li, C., Dai, C., & Chan, W.K.
- Year: 2024
- Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Computer Aided Design In Mechanical Engineering and Lecture Notes in Bioinformatics), 14730 LNCS, pp. 55–67

Build Belonging and Trust Proactively: A Humanized Intelligent Streamer Assistant with Personality, Emotion and Memory
- Citation: Gao, F., Dai, C., Fang, K., Li, J., & Chan, W.K.V.
- Year: 2024
- Journal: Communications in Computer and Information Science, 1958 CCIS, pp. 140–147

Image Resizing for Object Detection: A Learnable Downsampler-Upsampler Pair with Differentiable Image Entropy Estimation
- Citation: Dai, C., Chen, Q., Xu, J., Song, G., & Yang, B.
- Year: 2023
- Journal: International Journal of Pattern Recognition and Computer Aided Design In Mechanical Engineering, 37(8), 2354011

Intelligent Detection of Disinformation Based on Chronological and Spatial Topologies
- Citation: Hsu, R.-H., Chen, B.-J., & Dai, C.-J.
- Year: 2023
- Journal: 2023 9th International Conference on Applied System Innovation, ICASI 2023, pp. 258–260

Benjamin Allaert| vision | Best Researcher Award

Posted on 05/09/202405/09/2024 by 21b4bddf87157652317827146367558f

Assoc Prof Dr . Benjamin Allaert| vision | Best Researcher Award

Assoc Prof Dr. Benjamin Allaert,Institue Mines-Télécom Nord Europe.France

Assoc. Prof. Dr. Benjamin Allaert is a prominent researcher and academic affiliated with the Institut Mines-Télécom Nord Europe in France. He specializes in fields related to engineering and technology, contributing significantly to advancements in these areas. Dr. Allaert is known for his extensive research work, publications, and active participation in academic communities. His expertise and leadership have positioned him as a key figure within the institute, where he continues to mentor students and collaborate on cutting-edge research projects.

Summary:

Dr. Benjamin Allaert is an outstanding candidate for the Best Researcher Award, with his comprehensive academic background, multidisciplinary expertise, and proven leadership. His work on deep learning, facial expression recognition, and innovative contributions to medical imaging tools reflect his dedication to advancing human-computer interaction and computer vision. His achievements, including prestigious awards, patents, and publications in highly respected journals, position him as a top contender for the award.

Professional Profiles:

Orcid

🎓 Education :

Ph.D. in Computer Vision, Affective Computing, and Machine Learning (2014-2018) Benjamin Allaert earned his Ph.D. from the University of Lille, France, where he specialized in computer vision and affective computing. His doctoral research focused on analyzing human emotions through facial expressions, particularly micro and macro expressions in complex environments. His work aimed to improve facial expression recognition using machine learning algorithms, even in challenging real-world conditions involving varying head poses.,B.Sc. & M.Sc. in Computer Vision, Image, Vision, and Interaction (2011-2014) Before pursuing his Ph.D., Allaert completed both his Bachelor’s and Master’s degrees in Computer Vision with a focus on Image, Vision, and Interaction. These programs laid the foundation for his expertise in image processing and human-computer interaction, which he later applied to his research in affective computing.,Associate Degree in IT Management (2009-2011) Allaert holds an Associate Degree in IT Management, where he developed skills in system administration, database management, and networking. This background equipped him with essential technical knowledge that he later leveraged in his research and professional roles.,High School Specialization in Electrotechnics (2008-2009) His early interest in technology began in high school with a specialization in electrotechnics, where he gained a fundamental understanding of electrical systems and engineering principles.

🏢 Experience:

Associate Professor, IMT Nord Europe, France (Since 2021) Currently, Benjamin Allaert serves as an Associate Professor at IMT Nord Europe. His research is focused on computer vision and artificial intelligence, specifically analyzing human behavior and interactions with AI-driven systems. His work aims to enhance human-machine interaction and bridge gaps in user experiences through innovative AI solutions.,Lead Data Scientist, GENFIT, France (2019-2021) As Lead Data Scientist at GENFIT, Allaert led an R&D team developing diagnostic tools based on deep learning. His work primarily involved medical image processing, helping healthcare professionals diagnose conditions using automated systems. His contributions played a key role in advancing AI-driven medical diagnostics.,Research Engineer, CRIStAL, FOX Team, France (2018-2019) Allaert worked as a research engineer on the ITEA3 PAPUD European project at the CRIStAL lab. His research focused on affective computing, using image processing and deep learning techniques to analyze emotional states, including frustration, contributing to advancements in emotion recognition technologies.,Ph.D. Researcher, CRIStAL, FOX Team, France (2014-2018) During his Ph.D. research, Allaert developed novel methods for recognizing facial expressions in uncontrolled environments, such as varying head poses and partial occlusions. His work provided significant insights into the complexities of emotion recognition in real-world scenarios.,Master’s Intern, CRIStAL, FOX Team, France (2014) As part of his Master’s program, Allaert analyzed head, arm, and shoulder movements to study their impact on interaction systems, showcasing his interest in human-computer interaction.,R&D Project Intern, INRIA LILLE, SHACRA Team, France (2013) Allaert developed an augmented reality-based educational application for medical simulations during his internship at INRIA Lille, demonstrating his ability to apply cutting-edge technology to practical educational contexts.,Mobile Software Developer, Speechi, France (2012) In his early career, Allaert developed a mobile voting app aimed at enhancing classroom interactions, further showcasing his ability to create user-centered technological solutions.

🛠️Skills:

Allaert possesses a wide range of technical skills, including proficiency in programming languages such as C/C++, C#, Java, and Python,along with web languages like HTML5, PHP, and JavaScript. He is highly experienced with deep learning frameworks such as Keras, TensorFlow, and PyTorch. His expertise also extends to operating systems (DOS, UNIX, Android) and platforms such as Qualisys QTM, Unreal Engine, and Unity.

🔬Awards:

IoT Student Challenge Winner (2019),Allaert was awarded three prizes, including the laureate prize, incubation prize, and the favorite prize of the Hauts-de-France region, for his outstanding work in the Internet of Things (IoT) domain. These awards recognized his innovative contributions to IoT technologies.,Best “Young Researcher” Paper Prize, CORESA (2016),His research on computer vision and affective computing earned him the prestigious Best “Young Researcher” Paper Prize at the CORESA conference, highlighting his early contributions to facial expression recognition technologies.

Research Focus:

Benjamin Allaert’s research primarily revolves around the intersection of computer vision, affective computing, and human-computer interaction. He focuses on improving facial expression recognition in real-world scenarios, particularly under challenging conditions such as partial occlusion and varying head poses. Through deep learning and advanced image processing, his work enhances the understanding of human emotions and behavior, contributing to sectors like healthcare and user interaction technologies.

Conclusion:

Dr. Allaert’s strong academic profile, impactful research, and leadership skills make him a highly suitable candidate for the Best Researcher Award. While expanding his international collaboration and exploring new avenues of research could further elevate his contributions, his existing body of work already reflects excellence and innovation in his field.

Publications :

Face Analysis Under Uncontrolled Conditions: From Face Detection to Expression Recognition (2022), John Wiley & Sons

Dynamic Facial Expression Recognition Under Partial Occlusion with Optical Flow Reconstruction (2021), IEEE Transactions on Image Processing

Impact of Facial Landmark Localization on Facial Expression Recognition (2021), IEEE Transactions on Affective Computing

Patent Application: Semi-supervised Approach for Automatic Cell Annotation (2021), WO2022090205A1