Sara Sadeghi | Structure | Best Researcher Award

Mrs Sara Sadeghi | Structure | Best Researcher Award

PhD Candidate,Isfahan University of Art,Iran

Sara Sadeghi is a highly accomplished researcher with a strong academic background, significant contributions to architectural engineering, and practical industry experience. She has demonstrated her ability to use innovative methodologies and techniques in her research, which has been recognized by high-impact publications. Her active involvement in teaching and industry projects further strengthens her professional profile.

Publication Profile
scopus

Education :

Sara Sadeghi is currently pursuing a Ph.D. in Architectural Engineering at the Art University of Isfahan, where she has maintained a high GPA of 3.92 (18.88/20) since 2020. Prior to this, she earned a Master’s degree in Architectural Engineering from the Iran University of Science and Technology (IUST) in 2017, graduating with a GPA of 3.75 (17.20/20). She completed her Bachelor’s degree in Architectural Engineering at Ferdowsi University in Mashhad, where she graduated with a GPA of 3.87 (17.52/20).

EXPERIENCE:

Sara has a diverse set of academic and professional experiences. Since 2022, she has served as an Instructor and Teaching Assistant (TA) at Ferdowsi University of Mashhad, where she teaches both undergraduate and graduate-level courses in Architectural Design and Traffic-Oriented Design. Additionally, she has worked as an instructor at the Art University of Isfahan in 2021, teaching “Architectural Theories” to graduate students. Her professional design experience includes working at Ziba Saze Toos Gam Co as an Architectural Designer, contributing to the Kooh Noor and Dornika Residential Towers in Mashhad. She has also served as R&D Manager at Royan Hooshmand science-based company, focusing on precast construction systems.

Research Focus:

Sara’s research is concentrated on architectural structural performance, with a particular focus on the qualitative and quantitative assessment of structures through advanced methods such as fuzzy logic and multi-criteria decision-making. Her ongoing Ph.D. thesis, supervised by Dr. Mahmoudi, explores the qualitative measurement models of structural performance in architecture. Her published works have delved into the integration of aesthetics and functionality in structural design, particularly in the context of Iranian architecture.

Awards and Recognition:

Sara has received multiple prestigious scholarships throughout her academic career, including full scholarships from Art University of Isfahan, Iran University of Science and Technology, and Ferdowsi University. She was also awarded the Top Student Prize at Ferdowsi University, which granted her membership in the “Talented Students’ Community.” Additionally, Sara received the straight admission to the Master’s program at Iran University of Science and Technology due to her outstanding academic performance.

Skills:

Sara possesses a robust skill set in both architectural design and computational tools. Her technical skills include proficiency in software such as Machine Learning, Revit, Python, MATLAB, Civil 3D, Rhinoceros, GIS, Grasshopper, and Design Builder. These tools enable her to conduct advanced architectural analyses and design innovative, sustainable structures. She has also gained expertise in Python programming, 3D modeling, and design computing.

Publication 

  • Sadeghi, S., Mahmoudi, M., Kamel Nia, H., & Hoseinpour Jajarm, M. (2025). “Quantitative Assessment Model for Spatial and Functional Performances of Structures Using Fuzzy Logic, Case Studies: Spaceframe Structures”. Journal of Structures. Elsevier. IF: 3.9. Q1. (Accepted and published).
  • Sadeghi, S., Mahmoudi, M., Kamel Nia, H., & Hoseinpour Jajarm, M. (2024). “Assessment of Qualitative Performances of Structures in Architecture, Case Studies: Space Frame Structures in Tehran, Iran”. The Institution of Engineers (India), Springer. Q2. https://doi.org/10.1007/s40030-024-00858-6 (Accepted and published).
  • Sadeghi, S., Mahmoudi Kamelabad, M., & Kamel Nia, H. (2024). “Assessing Structural Performance: A Combined Qualitative and Quantitative Approaches Using Multi-Criteria Decision-Making Method”. The Institution of Engineers (India), Springer. Q2. https://doi.org/10.1007/s40030-024-00862-w. (Accepted and published).
  • Sadeghi, S., Ekhlassi, A., & Nowrouzian, S. (2018). “Analysis of Aesthetics Role in Iranian Structural Architecture, Case Study: Tajol-Molk Dome”. SN Applied Sciences Journal, Springer. JCR, Q2, IF: 2.8, 1:570.
  • Sadeghi, S., Ekhlassi, A., & Kamelnia, H. (2018). “Investigation of Aesthetics Styles in Iranian Architectural Styles”. International Conference of Civil, Architecture and Urban Management, Tehran University, Iran. (Accepted and published).
  • Sadeghi, S., Ekhlassi, A., & Kamelnia, H. (2017). “Study of Architectural Aesthetics Role in Iranian Houses, Case Study: Historic Houses of Mashhad”. Journal of Researches in Islamic Architecture, No 21. (Accepted and published).
  • Sadeghi, S., Ekhlassi, A., & Kamelnia, H. (2016). “Analysis of Architectural Aesthetic Principles”. National Conference in Architecture and Civil, Khaje Nasir University, Tehran, Iran. (Accepted and published).
CONCLUSION:

Sara Sadeghi is an outstanding candidate for the Best Researcher Award due to her exceptional academic achievements, impressive publication record, and commitment to advancing the field of architectural engineering. With continuous professional development, a focus on enhancing her academic writing, and further international collaborations, Sara is poised to make even more substantial contributions to architectural research. Her dedication, innovation, and leadership in the field make her an exemplary candidate for this prestigious award.

CHENGJIE DAI | design | Best Researcher Award

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