Samira Azizi | Engineering | Best Researcher Award

Ms. Samira Azizi | Engineering | Best Researcher Award

Ph.D candidate at Politecnico di Milano, Italy.

Samira Azizi ๐ŸŽ“ is a Ph.D. candidate at Politecnico di Milano ๐Ÿ‡ฎ๐Ÿ‡น, specializing in smart structural control and vision-based structural health monitoring (SHM) ๐Ÿ—๏ธ๐Ÿ“น. Her work focuses on enhancing earthquake resilience through real-time damage detection and adaptive stiffness systems ๐ŸŒโš™๏ธ. She has contributed significantly to full-field motion estimation using video data and advanced optimization techniques such as particle swarm algorithms ๐Ÿง ๐Ÿ“ˆ. As a dedicated researcher, Samira serves on editorial boards ๐Ÿ“š, reviews for prestigious journals โœ๏ธ, and engages in innovative, non-contact SHM technologies. Her passion lies in bridging advanced engineering with intelligent monitoring solutions ๐ŸŒ๐Ÿ’ก.

Professional Profile:

Scopus

ORCID

Suitability For Best Researcher Award:

Samira Azizi is highly suitable for the Best Researcher Award based on her cutting-edge research, interdisciplinary innovation, and global academic engagement. Her work bridges structural engineering, artificial intelligence, and computer vision, with a clear focus on non-contact, vision-based structural health monitoring (SHM) โ€” a domain crucial for infrastructure safety in earthquake-prone regions. Her leadership as a peer reviewer and editorial board member, combined with impactful publications and innovative methodologies, demonstrate excellence and commitment to advancing civil engineering research.

๐Ÿ”น Education & Experience

๐ŸŽ“ Education:

  • Ph.D. Candidate in Structural Engineering โ€“ Politecnico di Milano, Italy ๐Ÿ‡ฎ๐Ÿ‡น

  • Research background in system identification, control systems, and structural health monitoring ๐Ÿ—๏ธ

๐Ÿ’ผ Experience:

  • Short-term research contract (ongoing) at Politecnico di Milano ๐Ÿ”ฌ

  • Peer reviewer for journals including PLOS ONE, Engineering Structures, and Experimental Mechanics ๐Ÿ“ฐ

  • Editorial board member of Frontiers in Built Environment ๐Ÿ“–

  • Published multiple high-impact research papers in SCI/Scopus-indexed journals ๐Ÿ“‘

๐Ÿ”น Professional Development

Samira Azizi has demonstrated exceptional professional growth through collaborative research projects and technical expertise in system dynamics and SHM technologies ๐Ÿ”๐Ÿค. Her editorial roles and frequent peer reviewing across top journals reflect her critical thinking and in-depth knowledge ๐Ÿ“˜๐Ÿ”ฌ. She continues to refine her research acumen by actively engaging in advanced image processing and video-based structural analysis ๐Ÿ“น๐Ÿง . With a focus on non-contact, intelligent monitoring frameworks, she is also pursuing a research contract at Politecnico di Milano, enhancing her academic trajectory ๐Ÿš€. Samiraโ€™s constant pursuit of innovation and precision defines her as a rising star in engineering research ๐ŸŒŸ๐Ÿ“.

๐Ÿ”น Research Focus Area

Samiraโ€™s research centers on vision-based structural identification and control systems ๐ŸŽฅ๐Ÿ—๏ธ. Her innovative work bridges civil engineering with artificial intelligence and image processing ๐Ÿค–๐Ÿ“ธ, aiming to improve structural integrity assessment without physical sensors. She develops non-contact, video-based motion estimation frameworks that track both macro and subpixel movements, ideal for real-time damage detection โšก๐Ÿ”ง. By integrating tools like particle swarm optimization and complexity pursuit, her studies push forward the field of output-only modal analysis ๐ŸŒ€๐Ÿ“‰. Her goal is to create sustainable, smart monitoring systems for resilient infrastructure in seismically active regions ๐ŸŒ๐Ÿ› ๏ธ.

๐Ÿ”น Awards & Honors

๐Ÿ† Awards & Recognitions:

  • โœจ Selected editorial board member โ€“ Frontiers in Built Environment

  • ๐Ÿ… Reviewer for reputed journals: PLOS ONE, Engineering Structures, Experimental Mechanics, etc.

  • ๐Ÿ“ Multiple peer-reviewed journal publications in top-tier SCI/Scopus outlets

  • ๐ŸŽ“ Invited speaker and contributor at international conferences (e.g., ECSA-10)

  • ๐ŸŒ Recognized for developing innovative semi-active stiffness control systems and full-field video measurement techniques

Publication Top Notes

Article Title:

Structural Identification Using Digital Image Correlation Technology

Authors:
  • Samira S. Azizi

  • Kaveh K. Karami

  • Stefano S. Mariani

Published in:

Engineering Proceedings, 2023
Access: Open Access (Link currently disabled)

Abstract Summary

This paper explores the application of Digital Image Correlation (DIC) technology for structural identification in engineering systems. DIC is a non-contact optical method used to measure deformation, displacement, and strain by tracking speckle patterns on the surface of materials. The study focuses on the implementation of DIC to assess the structural response under various loading conditions. Through experimental validation and comparative analysis, the authors demonstrate the effectiveness of DIC in enhancing the accuracy and reliability of structural health monitoring techniques.

๐Ÿ Conclusion:

Samira Azizi exemplifies the qualities of a Best Researcher Award recipient. Her interdisciplinary approach, scientific rigor, and global academic engagement place her at the forefront of innovation in structural engineering. She is not only shaping the future of smart infrastructure but also elevating the standards of academic research and collaboration. Awarding her this recognition would honor a truly transformative contributor to engineering science.

Yumeng Su | Engineering | Best Researcher Award

Mr. Yumeng Su | Engineering | Best Researcher Award

Mr. Yumeng Su at Shanghai Jian Qiao University, China.

Su Yumeng ๐ŸŽ“, a top-ranking computer science undergraduate at Shanghai Jian Qiao University ๐Ÿ‡จ๐Ÿ‡ณ, excels in AI ๐Ÿค–, robotics ๐Ÿš, and embedded systems ๐Ÿง . With hands-on experience in drone development, ROS, and deep learning ๐Ÿ’ก, he has published impactful research and led award-winning teams ๐Ÿ†. His technical expertise spans Python, MATLAB, LaTeX, and advanced hardware platforms like Jetson Nano and STM32 ๐Ÿ’ป. Beyond academics, heโ€™s a dynamic leader and athlete ๐Ÿ€๐Ÿšดโ€โ™‚๏ธ, known for his resilience and innovation in intelligent systems and smart hardware applications ๐Ÿ”. Suโ€™s work bridges theoretical AI with real-world applications ๐ŸŒ.

Publication Top Notes

ORCID

Suitability for Best Researcher Award โ€“ Su Yumeng

Su Yumeng is a highly promising and exceptionally driven early-career researcher whose blend of technical excellence, innovation, and leadership places him as a top contender for the Best Researcher Award. As an undergraduate, his hands-on contributions to AI, robotics, and embedded systems are not only commendable but groundbreaking, particularly for his academic level. He demonstrates a rare ability to translate theory into impactful real-world applications, bridging research with innovation in autonomous systems, drone technology, and intelligent hardware solutions.

๐Ÿ”น Education & Experience

  • ๐ŸŽ“ B.Sc. in Computer Science & Technology, Shanghai Jian Qiao University (2021โ€“Present)

  • ๐Ÿ“ Focus: AI, Robotics, Embedded Systems, and Smart Hardware

  • ๐Ÿ“š Completed key courses with top grades (AI, Python, Robotics, Microcontroller Principles, etc.)

  • ๐Ÿš€ ROS training at East China Normal University (Basic & Advanced UAV/Vehicle Tracking)

  • ๐Ÿ›  Internship at Superdimension Technology Space: Autonomous drone development

  • ๐Ÿงช Project collaboration with FAST-Lab at Zhejiang University on UAVs

๐Ÿ”น Professional Development

Su Yumeng continually advances his professional skills through academic projects ๐Ÿงช, interdisciplinary competitions ๐Ÿ†, and real-world UAV applications ๐Ÿš. He has mastered the integration of AI models like YOLO with edge computing platforms such as Jetson Nano and Raspberry Pi ๐Ÿ’ป. His leadership in innovation competitions reflects his capacity to guide teams and deliver impactful solutions ๐ŸŽฏ. Suโ€™s deep involvement in research and drone design demonstrates his ability to convert academic concepts into cutting-edge technology ๐Ÿ’ก. With practical ROS experience and sensor fusion expertise, he remains at the forefront of smart automation and robotics ๐ŸŒ.

๐Ÿ”น Research Focus Category

Su Yumengโ€™s research focuses on Artificial Intelligence in Embedded and Autonomous Systems ๐Ÿค–, especially in smart robotics and deep learning applications for environmental perception and control ๐ŸŒ. His work bridges physics-informed neural networks (PINNs) with real-time sensor fusion for drones and robotics ๐Ÿค. He explores practical challenges like crack detection in infrastructure using UAVs ๐Ÿ› ๏ธ, baby posture recognition on embedded platforms ๐Ÿผ, and SLAM-based navigation for wheeled robots ๐Ÿš—. His interdisciplinary approach merges hardware innovation with AI, yielding scalable, intelligent, and responsive systems suitable for civil engineering, healthcare, and autonomous mobility fields ๐Ÿš€.

๐Ÿ”น Awards & Honors

  • ๐Ÿฅ‡ National Second Prize, 17th National College Student Computer Design Competition (2024)

  • ๐Ÿฅ‰ National Bronze & Shanghai Gold, China Innovation Competition (2024)

  • ๐Ÿฅ‡ Shanghai Gold Award, Career Planning Competition (2024)

  • ๐Ÿ… First Prize, Shanghai College Student Computer Application Competition (2024)

  • ๐Ÿฅˆ Shanghai Second Prize, Ti Cup Electronic Design Contest (2023)

  • ๐Ÿฅ‰ Bronze Award, “Challenge Cup” Entrepreneurship Plan Competition

  • ๐Ÿฅ‰ Shanghai Third Prize, China Robot & AI Competition (2024)

  • ๐ŸŽ– National Motivational Scholarship ร—3

  • ๐ŸŽ“ President โ€œQing Yunโ€ Scholarship

  • ๐ŸŽ— School Special Scholarship

Publication Top Notes

  • “The Feasibility Assessment Study of Bridge Crack Width Recognition in Images Based on Special Inspection UAV”
    Cited by: 13 | Year: 2020 โ€‹

  • “Intelligent Crack Detection and Quantification in the Concrete Bridge: A Deep Learning-Assisted Image Processing Approach”
    Cited by: 20 | Year: 2022

Conclusion

Su Yumengโ€™s combination of academic excellence, deep technical knowledge, hands-on innovation, and research impact clearly distinguishes him as an ideal recipient of the Best Researcher Award. His contributions as an undergraduate are extraordinary and reflect the potential of a future global leader in AI and robotics research.