Samira Azizi | Engineering | Best Researcher Award

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Ms. Samira Azizi | Engineering | Best Researcher Award

Ph.D candidate at Politecnico di Milano, Italy.

Samira Azizi 🎓 is a Ph.D. candidate at Politecnico di Milano 🇮🇹, specializing in smart structural control and vision-based structural health monitoring (SHM) 🏗️📹. Her work focuses on enhancing earthquake resilience through real-time damage detection and adaptive stiffness systems 🌐⚙️. She has contributed significantly to full-field motion estimation using video data and advanced optimization techniques such as particle swarm algorithms 🧠📈. As a dedicated researcher, Samira serves on editorial boards 📚, reviews for prestigious journals ✍️, and engages in innovative, non-contact SHM technologies. Her passion lies in bridging advanced engineering with intelligent monitoring solutions 🌍💡.

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) — 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.

🔹 Education & Experience

🎓 Education:

  • Ph.D. Candidate in Structural Engineering – Politecnico di Milano, Italy 🇮🇹

  • Research background in system identification, control systems, and structural health monitoring 🏗️

💼 Experience:

  • Short-term research contract (ongoing) at Politecnico di Milano 🔬

  • Peer reviewer for journals including PLOS ONE, Engineering Structures, and Experimental Mechanics 📰

  • Editorial board member of Frontiers in Built Environment 📖

  • Published multiple high-impact research papers in SCI/Scopus-indexed journals 📑

🔹 Professional Development

Samira Azizi has demonstrated exceptional professional growth through collaborative research projects and technical expertise in system dynamics and SHM technologies 🔍🤝. Her editorial roles and frequent peer reviewing across top journals reflect her critical thinking and in-depth knowledge 📘🔬. She continues to refine her research acumen by actively engaging in advanced image processing and video-based structural analysis 📹🧠. With a focus on non-contact, intelligent monitoring frameworks, she is also pursuing a research contract at Politecnico di Milano, enhancing her academic trajectory 🚀. Samira’s constant pursuit of innovation and precision defines her as a rising star in engineering research 🌟📐.

🔹 Research Focus Area

Samira’s research centers on vision-based structural identification and control systems 🎥🏗️. Her innovative work bridges civil engineering with artificial intelligence and image processing 🤖📸, 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 ⚡🔧. By integrating tools like particle swarm optimization and complexity pursuit, her studies push forward the field of output-only modal analysis 🌀📉. Her goal is to create sustainable, smart monitoring systems for resilient infrastructure in seismically active regions 🌍🛠️.

🔹 Awards & Honors

🏆 Awards & Recognitions:

  • ✨ Selected editorial board member – Frontiers in Built Environment

  • 🏅 Reviewer for reputed journals: PLOS ONE, Engineering Structures, Experimental Mechanics, etc.

  • 📝 Multiple peer-reviewed journal publications in top-tier SCI/Scopus outlets

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

  • 🌐 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.

🏁 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.

JUN WON HO | Computer Engineering | Best Researcher Award

Posted on by phenomenological Research

Dr. JUN WON HO | Computer Engineering | Best Researcher Award

Research Fellow at Incheon National University, South Korea.

Dr. Jun Won-Ho 🎓 is a dedicated Research Fellow at Incheon National University, South Korea 🇰🇷. He earned his Ph.D. in Computer Engineering in February 2023 🧠, focusing on sleep pattern analysis in an unconscious, non-intrusive state 🛏️. His innovations aim to revolutionize sleep health through biosensor-based technologies 💡. With peer-reviewed publications in SCI-indexed journals 📚 and a patent on body weight estimation while lying in bed 🧾, Dr. Jun is making sleep monitoring accessible and home-based. His work bridges healthcare and engineering, offering practical solutions for sleep apnea detection 🩺 using biosensors and ambient signals 🌐.

Professional Profile:

ORCID

Suitability for Best Researcher Award – Dr. Jun Won-Ho

Dr. Jun Won-Ho is highly suitable for the Best Researcher Award due to his pioneering research at the intersection of biomedical engineering and computer science. Despite being an early-career researcher, he has demonstrated remarkable innovation and scientific productivity, especially in the field of non-intrusive sleep health monitoring. His Ph.D. and postdoctoral work have resulted in SCI-indexed journal publications, a granted patent, and the development of AI-based, contact-free technologies to address global health concerns like sleep apnea—showing both originality and real-world impact.

🎓 Education and Experience

  • 🎓 Ph.D. in Computer Engineering – Incheon National University (2023)

  • 🧪 Research Fellow – Incheon National University (Current)

  • 📄 Published in SCI-indexed journals – Including Sensors

  • 🛏️ Doctoral Research – Focused on unobtrusive sleep pattern analysis

  • 🔬 Ongoing Research – Development of self-screening technology for sleep apnea

  • 🧾 Patent Holder – System for estimating body weight while lying on a bed

🚀 Professional Development

Dr. Jun Won-Ho has significantly contributed to the field of sleep science and biomedical engineering 🧠. His journey began with a strong academic foundation in computer engineering 🎓, which he has transformed into impactful research focused on real-world health challenges 🩺. He has authored articles in SCI-indexed journals 📚 and currently works on a cutting-edge sleep apnea screening solution using biosensors and environmental data 🌙📊. His patented invention 🧾 and active engagement in non-contact health monitoring technologies reflect his innovative mindset and commitment to improving global health accessibility 🌍💡.

🧬 Research Focus Category

Dr. Jun Won-Ho’s research falls under the category of Biomedical Engineering and Sleep Science 🧠🛌. He is especially focused on unobtrusive health monitoring, developing systems that use biosensors, physiological signals, and environmental data to analyze sleep patterns and detect sleep disorders like apnea 😴🩺. His goal is to eliminate the need for intrusive clinical testing such as polysomnography 🧪 and instead offer home-based, AI-powered health solutions 🌐📲. His patented work on weight estimation during sleep complements his broader mission of advancing digital health technologies for continuous, contact-free care 🧾💡.

🏅 Awards and Honors

  • 🧾 Patent Granted – System for Estimating Body Weight While Lying on a Bed (KR 10-2556030)

  • 📄 SCI-Indexed Publications – Published 2 articles in renowned journals like Sensors

  • 📌 Ph.D. Achievement – Doctorate completed with impactful research in 2023

  • 🏆 Nominated for Best Researcher Award – For contributions to biomedical sleep technology

  • 🧠 Research Innovation Recognition – Development of non-contact sleep apnea screening system

Publication Top Notes

1. Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow

  • Published: April 30, 2025

  • Journal: Bioengineering

  • DOI: 10.3390/bioengineering12050480

  • Summary: This study introduces a novel method for detecting sleep posture by analyzing humidity fluctuations using sensors embedded in a pillow. The system monitors changes caused by respiration and perspiration, offering a non-invasive approach to sleep posture detection.

2. Sleep Pattern Analysis in Unconstrained and Unconscious State

  • Published: November 29, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22239296

  • Citation Count: 6

  • Summary: This research analyzes sleep patterns in individuals without physical constraints or active awareness. Utilizing various sensors, the study collects physiological and environmental data to classify sleep stages, providing insights into natural sleep behaviors.MDPI

3. Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes

  • Published: July 19, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22145388

  • Citation Count: 12

  • Summary: This paper presents a reconfigurable module for multi-sensor data fusion, applied to unmanned storage boxes. By integrating data from various sensors, the system enhances reliability and security in automated storage environments.

Conclusion

Dr. Jun Won-Ho exemplifies the qualities of a Best Researcher Award recipient through his innovative mindset, impactful biomedical applications, and commitment to global health technology advancement. His work is not only academically rigorous but also practically transformative, making essential health monitoring more accessible, affordable, and patient-friendly. He stands out as a rising star in biomedical engineering, well-deserving of this prestigious recognition.