Sara Sadeghi | Structure | Best Researcher Award

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Mrs. Sara Sadeghi | Structure | Best Researcher Award

Isfahan University of Art | Iran

PUBLICATION PROFILE

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👩‍🎓 Education

Mrs. Sara Sadeghi is currently a Ph.D. Candidate in Architectural Engineering at the Art University of Isfahan, with a stellar GPA of 3.92/4.00. She completed her Master’s in Architectural Engineering from Iran University of Science and Technology (IUST), where she graduated with a GPA of 3.75/4.00. Additionally, she earned her Bachelor’s in Architectural Engineering from Ferdowsi University of Mashhad, with an impressive GPA of 3.87/4.00.

🏆 Awards & Achievements

Sara has received several prestigious scholarships throughout her academic journey, including full scholarships from Art University of Isfahan and Iran University of Science and Technology. Notably, she was granted straight admission into the Master’s program at IUST and received the top student prize at Ferdowsi University, earning her a spot in the “Talented Students’ Community.”

📑 Licensure & Certification

Sara became a certified Professional Engineer (P.E.) for Design and Construction Supervision in Khorasan Razavi, Iran, in 2021. This licensure showcases her professional capabilities and commitment to the architectural engineering field.

📚 Publications & Presentations

Sara has made significant contributions to architectural engineering research with multiple publications. Some of her notable works include:

  • “Quantitative Assessment Model for Spatial and Functional Performances of Structures Using Fuzzy Logic” (2025)

  • “Assessment of Qualitative Performances of Structures in Architecture” (2024)

  • “Analysis of Aesthetics Role in Iranian Structural Architecture” (2018).
    Her research spans structural performance, aesthetics in architecture, and the application of fuzzy logic.

💼 Professional Experience

Sara’s professional journey is as impressive as her academic one. She currently serves as an instructor and teaching assistant at Ferdowsi University of Mashhad and Art University of Isfahan, where she teaches architectural design and theory courses. She has also worked as an architectural designer for Ziba Saze Toos Gam Co. in Mashhad and as an R&D Manager at Royan Hooshmand science-based company, where she contributed to the development of precast construction methods.

📊 Research & Projects

Sara is deeply involved in research, particularly in the “Numerical Analysis of Structural Performances” at Art University of Isfahan. She has also contributed to architectural design and development projects, such as her master’s thesis on “Cultural Center Design” and her bachelor’s thesis on “Villa Design with the Approach of Green Architecture.”

💡 Trainings & Workshops

Sara continuously enhances her skills through specialized training programs and workshops. She completed courses in Python Programming, 3D Modeling with Rhino and Python, and Renewable Energy and Green Building Entrepreneurship. She also attended workshops in Parametric Architecture and Sustainable Architecture.

📚 Top Notes Publications 

An analysis of structural aesthetics in architecture case study: Taj-Ol-Molk Dome, Jāmeh Mosque of Isfahan, Iran

    • Authors: S Sadeqi, A Ekhlassi, S Norouzian-Maleki

    • Journal: SN Applied Sciences

    • Year: 2019

Analysis of Architectural Aesthetics Role in Iranian Houses; Case Study: Mashhad Historical Houses

    • Authors: S Sadeghi, A Ekhlassi, H Kamelnia

    • Journal: JOURNAL OF RESEARCHES IN ISLAMIC ARCHITECTURE

    • Year: 2019

Quantitative assessment model for spatial and functional performances of structures using fuzzy logic, case studies: Spaceframe structures

    • Authors: S Sadeghi, M Mahmoudi Kamelabad, H Kamelnia, M Hoseinpour Jajarm

    • Journal: Structures

    • Year: 2025

Assessing Structural Performance: A Combined Qualitative and Quantitative Approaches Using Multi‑Criteria Decision‑Making Method

    • Authors: S Sadeghi, M Mahmoudi Kamelabad, H Kamelnia

    • Journal: The Institution of Engineers (India)

    • Year: 2024

Assessment of Qualitative Performances of Structures in Architecture, Case Studies: Space Frame Structures in Tehran, Iran

    • Authors: S Sadeghi, M Mahmoudi Kamelabad, H Kamelnia, M Hoseinpour Jajarm

    • Journal: The Institution of Engineers (India)

    • Year: 2024

Yongzhi Qu | Scientific Machine Learning | Excellence in Innovation

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Dr. Yongzhi Qu | Scientific Machine Learning | Excellence in Innovation

University of Utah | United States

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Biography of Dr. Yongzhi Qu

🏅 Assistant Professor at University of Utah | Ph.D. in Industrial Engineering & Operations Research

Dr. Yongzhi Qu is an accomplished assistant professor at the University of Utah in the Department of Mechanical Engineering, specializing in AI-powered systems, data-driven dynamics, autonomous manufacturing, and digital twins. He earned his Ph.D. from the University of Illinois at Chicago in 2014, with a focus on Industrial Engineering & Operations Research. His research spans several fields, including machine learning, system modeling, and control for mechanical and structural systems.

📚 Education

  • Ph.D. in Industrial Engineering & Operations Research – University of Illinois at Chicago (2014)
  • M.S. in Measurement & Testing Technology – Wuhan University of Technology (2011)
  • B.Sc. in Measurement & Control Instrumentation and Technology – Wuhan University of Technology (2008)

💼 Professional Experience

  • Assistant Professor (07/2023 – Present)
    Department of Mechanical Engineering, University of Utah
  • Assistant Professor (08/2019 – 06/2023)
    Department of Mechanical & Industrial Engineering, University of Minnesota Duluth
  • Assistant/Associate Professor (01/2015 – 07/2019)
    Department of Mechanical Engineering, Wuhan University of Technology
  • Application Engineer (12/2013 – 12/2014)
    The DEI Group, Millersville, Maryland, US

🧠 Research Interests ON Scientific Machine Learning

Dr. Qu’s research focuses on scientific machine learning, AI-powered system modeling, estimation, and control for dynamic systems, with applications in autonomous manufacturing and digital twins. His recent work explores the intersection of machine learning, physics, and mathematics to model and control complex systems.

🏆 Research Grants

  • A Neural Differential Machine Learning Framework with Nonlinear Physics
    National Institute of Standards and Technology (NIST), $121,015 (2023-2026)
  • Real-time System Identification for Machining Spindles
    NIST, $159,950 (2020-2022)
  • Learning Real-time Dynamics of a Rotor System
    University of Minnesota, $44,501 (2020-2021)

🏅 Academic Awards

  • Best Academic Paper Award (IEEE International Conference on Prognostics and Health Management, 2013)
  • Best Student Paper Award (Society for Machinery Failure Prevention Technology Conference, 2014)
  • Best Paper Award (Prognostics and System Health Monitoring Conference, 2018)

📢 Invited Talks

  • Machine Learning for Dynamic System Modeling, Seagate (2022)
  • Keynote on Deep Learning in PHM, Annual Conference of PHM Society (2019)
  • FBG Sensing for Machinery Health Monitoring, Northeastern University, China (2016)

🎓 Teaching

  • Machine Learning for System Dynamics and Control, University of Minnesota Duluth
  • Six Sigma and Quality Control, University of Minnesota Duluth
  • Control Engineering, Wuhan University of Technology

🤝 Professional Service

  • Organizing Chair, Data Challenge, 15th Annual Conference of PHM Society (2023)
  • Panelist, Doctoral Symposium, 14th Annual Conference of PHM Society (2022)
  • Symposium Chair, ASME Manufacturing Science and Engineering Conference (2022, 2023)

📚 TOP NOTES PUBLICATIONS 

State space neural network with nonlinear physics for mechanical system modeling
    • Authors: Reese Eischens, Tao Li, Gregory W. Vogl, Yi Cai, Yongzhi Qu
    • Journal: Reliability Engineering & System Safety
    • Year: 2025
    • DOI: 10.1016/j.ress.2025.110946
Graph neural network architecture search for rotating machinery fault diagnosis based on reinforcement learning
    • Authors: Jialin Li, Xuan Cao, Renxiang Chen, Xia Zhang, Xianzhen Huang, Yongzhi Qu
    • Journal: Mechanical Systems and Signal Processing
    • Year: 2023
    • DOI: 10.1016/j.ymssp.2023.110701
Development of Deep Residual Neural Networks for Gear Pitting Fault Diagnosis Using Bayesian Optimization
    • Authors: Jialin Li, Renxiang Chen, Xianzhen Huang, Yongzhi Qu
    • Journal: IEEE Transactions on Instrumentation and Measurement
    • Year: 2022
    • DOI: 10.1109/TIM.2022.3219476
A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network
    • Authors: Jialin Li, Xueyi Li, David He, Yongzhi Qu
    • Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    • Year: 2020
    • DOI: 10.1177/1748006X19867776
Gear pitting fault diagnosis using disentangled features from unsupervised deep learning
    • Authors: Yongzhi Qu, Yue Zhang, Miao He, David He, Chen Jiao, Zude Zhou
    • Journal: Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
    • Year: 2019
    • DOI: 10.1177/1748006X18822447

 

Kuntao Ye | Signal Processing Algorithm | Best Researcher Award

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Dr. Kuntao Ye | Signal Processing Algorithm | Best Researcher Award

Jiangxi Univ. of Sci. and Tech. | China

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Dr. Kuntao Ye⚡🌍

INTRODUCTION 🌟

Dr. Kuntao Ye is an esteemed academic with a distinguished career in the fields of Electrical Engineering and Physics. As a professor at Jiangxi University of Science and Technology in China, Dr. Ye continues to contribute significantly to higher education, teaching, and research. His extensive academic background and professional experience in both academia and industry have earned him recognition globally. His work encompasses optical sensing, MEMS technology, signal processing, and more, making him a prominent figure in the research community.

EARLY ACADEMIC PURSUITS 📚

Dr. Ye’s academic journey began in China, where he obtained his B.S. and M.S. degrees from Nankai University, specializing in condensed matter physics and optics. His passion for research in photonics and optics led him to pursue a Ph.D. in Electrical Engineering from the University of Cincinnati, where he developed pioneering techniques for integrating optical nanoprobes with CMOS photodetection circuitry.

PROFESSIONAL ENDEAVORS 💼

Dr. Ye has had a wide-ranging career that includes roles as a postdoctoral fellow, product engineer, CTO, and visiting scholar. He has held important teaching positions, including as an associate professor at Jiangxi University of Science and Technology, where he imparts his expertise in signal processing, optoelectronics, and more. His time as a CTO at IntelliSense Corporation, as well as his academic visits to prestigious institutions such as McMaster University and the University of Nevada, have further enriched his professional portfolio.

CONTRIBUTIONS AND RESEARCH FOCUS ON Signal Processing Algorithm 🔬

Dr. Ye’s research spans a diverse array of topics including MEMS technology, optoelectronics, hyperspectral imaging, and signal processing. He has led several major research projects funded by the National Natural Science Foundation of China and other prestigious entities. His work on MEMS-based Fourier transform spectrometers, multi-parameter identification for turbid media, and advancements in image compression and sensing algorithms have earned him a reputation for groundbreaking contributions in these fields.

IMPACT AND INFLUENCE 🌍

Dr. Ye’s research has had a significant impact on various industries, particularly in the fields of optical sensing and MEMS technology. His patented inventions, including novel driving circuits for MEMS micromirrors and infrared-visible light image fusion methods, have been recognized both domestically and internationally. His research findings have been published in leading journals and conferences, further solidifying his position as an influential academic and researcher.

ACADEMIC CITATIONS AND PUBLICATIONS 📑

Dr. Ye has authored over 30 research papers and holds numerous patents. His work has been published in highly respected journals such as the IEEE Access and the Journal of Circuits, Systems, and Computers. His research continues to be cited by scholars and practitioners, particularly in the fields of image processing, hyperspectral sensing, and MEMS technology. His papers on advanced algorithms for image compression and detection techniques have been widely recognized for their innovative approaches.

HONORS & AWARDS 🏆

Throughout his career, Dr. Ye has received several accolades for his teaching and research achievements. These include the Outstanding Supervisor of Excellent Master’s Theses Award, Excellent Instructor Award at the National University Physics Experiment Competition, and recognition for his work in the Physics Innovation Contest. He has also been honored with the Advanced Worker of Science Popularization award by the Association of Science and Technology in Ganzhou City.

LEGACY AND FUTURE CONTRIBUTIONS  🔮

Dr. Ye’s legacy lies in his continuous pursuit of innovation and excellence in both teaching and research. His future contributions are expected to further advance technology in areas such as hyperspectral imaging, optoelectronic devices, and signal processing. With a strong foundation in both fundamental research and applied technology, Dr. Ye is poised to remain a key figure in the academic and research community for years to come.

FINAL NOTE ✨

Dr. Kuntao Ye’s work as a researcher and educator has left an indelible mark on the academic and professional world. His contributions to optics, MEMS technology, and signal processing have advanced the fields significantly. As an educator, he has shaped the minds of countless students, preparing them for careers in science and technology.

TOP NOTES PUBLICATIONS 📚

  • Multi-Scale Channel Distillation Network for Image Compressive Sensing

    • Authors: Tianyu Zhang, Kuntao Ye, Yue Zhang, Rui Lu
    • Journal: IEEE Access
    • Year: 2025

  • Differential Self-Feedback Dilated Convolution Network With Dual-Tree Channel Attention Mechanism for Hyperspectral Image Classification

    • Authors: Zhiqiang Xiao, Kuntao Ye, Guolong Cui
    • Journal: IEEE Transactions on Instrumentation and Measurement
    • Year: 2024

  • A Statistical Model-Based Approach for Reproducing Intermittent Faults in Electrical Connectors under Varying Vibration Loading Conditions

    • Authors: Xinglong Zhou, Kuntao Ye, Sheng Li, Songhua Liu
    • Journal: Journal of Circuits, Systems and Computers
    • Year: 2024

  • An Improved Beetle Swarm Antennae Search Algorithm Based on Multiple Operators

    • Authors: Kuntao Ye, Leilei Shu, Zhiqiang Xiao, Wen Li
    • Journal: Soft Computing
    • Year: 2024

 

Sana Jahangir | Computational modeling | Women Researcher Award

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Ms. Sana Jahangir | Computational modeling | Women Researcher Award

University of Eastern Finland | Finland

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Ms. Sana Jahangir ⚡🌍

👩‍🔬 INTRODUCTION

Sana Jahangir is a rising expert in computational modeling and biomechanics, currently pursuing a Ph.D. at the University of Eastern Finland, where her research focuses on knee joint mechanics and imaging-based computational modeling. She is passionate about the intersection of biomechanics and computer science, applying cutting-edge technologies to enhance the treatment of musculoskeletal conditions, particularly osteoarthritis. Her academic and professional work bridges the gap between engineering, medicine, and biomechanics, with an emphasis on simulation, modeling, and medical imaging.

🎓 EARLY ACADEMIC PURSUITS

Sana Jahangir’s academic journey began with a B.S. in Electrical Engineering from COMSATS University, Pakistan (2013-2017), where she majored in electronics and focused on signals and image segmentation. This foundation led to an M.S. in Biomedical Engineering from National University of Sciences and Technology (NUST), Pakistan (2017-2019), where she specialized in computational biomechanics and the design of prosthetic implants. Her academic excellence and CGPA of 3.6/4.0 earned her recognition, and she received awards for her research, particularly in finite element modeling and the design of 3-D bio-printable prosthetic implants.

💼 PROFESSIONAL ENDEAVORS

Currently, Sana serves as a Project Researcher at the University of Eastern Finland (2020-present), working on the ERA PerMed project, focusing on X-ray-based diagnostic tools for personalized treatment in patients with osteoarthritis. She has been involved in collaborative research with institutions in Sweden and Denmark and has played an integral role in computational framework testing, simulation of knee joint mechanics, and data analysis. Prior to this, Sana worked as a Research Assistant at NUST, Pakistan, contributing to projects on cardiac stent design, 3D bioprintable prosthetics, and biomechanical simulations. Her involvement in these projects helped contribute to the development of medical devices and healthcare solutions.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS ON Computational modeling

Sana’s research focuses on computational biomechanics, with a primary emphasis on knee joint mechanics. Her Ph.D. thesis explores radiograph-informed model generation and the sensitivity of cartilage mechanics to selected model parameters. She has made significant contributions to finite element modeling and biomechanical simulations of osteoarthritis and foot osteomyelitis. Her work on image-based computational models aims to improve diagnostic tools and personalize treatment plans for joint-related diseases, providing a more cost-effective and efficient solution to healthcare challenges.

🌍 IMPACT AND INFLUENCE

Sana’s work is pushing boundaries in the field of computational biomechanics. Through her involvement in several international collaborations, she is contributing to innovative treatments for knee injuries and osteoarthritis. Her research on the sensitivity of knee joint mechanics and musculoskeletal modeling has had a significant impact on the development of more accurate and personalized treatment strategies. Furthermore, her research findings are starting to influence both the academic and medical communities, particularly in improving the understanding of musculoskeletal mechanics and advancing treatment methodologies.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

Sana has authored multiple notable publications, including articles in prestigious journals such as Journal of Biomechanics and Annals of Biomedical Engineering. Her work on the sensitivity of knee joint mechanics and finite element modeling has garnered significant attention from the global academic community. Some of her highlighted papers include:

  1. “Sensitivity of simulated knee joint mechanics to selected human and bovine fibril-reinforced poroelastic material properties” – Journal of Biomechanics, 2023
  2. “Rapid X-ray-based 3-D finite element modeling of medial knee joint cartilage biomechanics during walking” – Annals of Biomedical Engineering, 2022
    Her work has also been presented at prominent international conferences such as the Orthopaedic Research Society Annual Meeting and the International Society of Biomechanics Congress.

🏅 HONORS & AWARDS

Sana’s academic journey has been decorated with several prestigious awards and grants, including:

  • UEF LUMETO program doctoral scholarship
  • Finnish Cultural Foundation grant (€26,000)
  • Third position in the Master’s in Biomedical Engineering batch at NUST
  • Best undergraduate thesis award
  • Best paper writing and presentation award at University of Helsinki
  • Selection for the ERA PerMed project as a Ph.D. candidate out of 26 applicants.

🌟 LEGACY AND FUTURE CONTRIBUTIONS HIGHLIGHT

Sana’s work promises to leave a lasting impact on the biomedical engineering field. As she progresses through her Ph.D. and beyond, her innovations in personalized treatment plans, biomechanical simulations, and image-based modeling will undoubtedly contribute to the development of more efficient and cost-effective solutions for musculoskeletal conditions. Her future work is expected to enhance medical diagnostics, prosthetic design, and joint health treatments, solidifying her legacy as a leading figure in the field of computational biomechanics.

📜 FINAL NOTE

Sana Jahangir is a dedicated researcher whose work in computational biomechanics is shaping the future of personalized healthcare. Her research in finite element modeling, musculoskeletal mechanics, and medical imaging has far-reaching implications for improving treatment strategies for knee injuries and musculoskeletal diseases. With her strong academic background and practical research experience, Sana is well-positioned to continue making significant contributions to the field of biomedical engineering.

 📚 TOP NOTES PUBLICATIONS

Effect of UNCERTAINTIES IN MUSCULOSKELETAL MODELING INPUTS on Sensitivity of Knee Joint Finite Element Simulations

  • Authors: Sana Jahangir, Will Bosch, Amir Esrafilian, Mika E. Mononen, Petri Tanska, Lauri Stenroth, Marius Henriksen, Tine Alkjaer, Rami K. Korhonen
    Journal: Medical Engineering & Physics
    Year: 2025
    DOI: 10.1016/j.medengphy.2025.104313 🦵💻

Sensitivity of Simulated Knee Joint Mechanics to Selected Human and Bovine Fibril-Reinforced Poroelastic Material Properties

  • Authors: Sana Jahangir, Amir Esrafilian, Mohammadhossein Ebrahimi, Lauri Stenroth, Tine Alkjær, Marius Henriksen, Martin Englund, Mika E. Mononen, Rami K. Korhonen, Petri Tanska
    Journal: Journal of Biomechanics
    Year: 2023
    DOI: 10.1016/j.jbiomech.2023.111800 🦵🦴

Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking
Correction to: Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking

  • Authors: Sana Jahangir, Ali Mohammadi, Mika E. Mononen, Jukka Hirvasniemi, Juha-Sampo Suomalainen, Simo Saarakkala, Rami K. Korhonen, Petri Tanska
    Journal: Annals of Biomedical Engineering
    Year: 2022
    DOI: 10.1007/s10439-022-02957-6 🦵🩻