Bojiang Yin | Engineering | Best Researcher Award

Published on by Forensic Scientist

Mr. Bojiang Yin | Engineering | Best Researcher Award

School of Petrochemical Engineering, Lanzhou University of Technology | China

Mr. Bojiang Yin’s research primarily focuses on the fundamental and applied aspects of special valve design and process systems, with an emphasis on structural parameter optimization, reliability engineering, and multi-physics coupling dynamics. His work addresses critical challenges in extreme operating environments, such as ultra-low temperature liquid hydrogen systems, by developing innovative sealing structures and evaluating their performance using advanced computational approaches. He has employed techniques including thermo-mechanical coupling, sensitivity analysis, high-precision RBF surrogate modeling, and NSGA-II optimization to achieve reliable bidirectional sealing under cryogenic conditions. Bojiang has published in high-impact journals like Scientific Reports, contributing to the scientific understanding of valve mechanics and optimization methodologies. He has collaborated with the National Natural Science Foundation of China, the Double First-Class Key Program of Gansu Province, and other regional technology programs, bridging academic research with practical industry applications. His contributions extend to consultancy projects, product development, and providing references for the design of advanced butterfly valves, positioning him as an emerging researcher in valve innovation and cryogenic system reliability.

Profile: ORCID

Featured Publications

Li, S., Yin, B., Wei, C., Li, W., & Yang, L. (2025). Structural analysis and multi-objective optimization of sealing structure for cryogenic liquid hydrogen triple-offset butterfly valve. Scientific Reports, 15, Article 20095. https://doi.org/10.1038/s41598-025-20095-6

Amin Reza Kalantari Khalil Abad | Engineering | Best Researcher Award

Published on by Forensic Scientist

Dr. Amin Reza Kalantari Khalil Abad | Engineering | Best Researcher Award

Iran University of Science and Technology | Iran

Dr. Amin Reza Kalantari Khalil Abad is a distinguished researcher and Lecturer in Industrial Engineering at Iran University of Science and Technology, Tehran, specializing in system optimization and sustainable supply chain design. He earned his Ph.D. in Industrial Engineering from Iran University of Science and Technology (2024), focusing on designing resilient horticultural supply chains under pest disruption, and holds an M.Sc. in Industrial Engineering (System Optimization) from Kharazmi University and a B.Sc. from Meybod University, Iran. His research expertise spans decision-making, operations research, mathematical modeling, and optimization, with emphasis on sustainable, resilient, and circular supply chain networks under uncertainty. Dr. Amin Reza Kalantari Khalil Abad has extensive teaching experience as a lecturer and teaching assistant in logistics, supply chain management, operations research, and software applications including GAMS and MiniTab. He has published six high-impact journal articles, including in the Journal of Environmental Management (2025), Journal of Industrial Information Integration (2025), Computers & Chemical Engineering (2024, 2023), Journal of Cleaner Production (2024), and Applied Soft Computing (2023). His work has been cited 57 times by 51 documents, achieving an h-index of 5 according to Scopus. Recognized as Top Ph.D. Student in Education (2021–2022) and Research (2023–2024), he also serves as a reviewer for leading journals and international conferences. Through his innovative research integrating optimization techniques, sustainable development, and supply chain resiliency, Dr. Amin Reza Kalantari Khalil Abad has significantly contributed to advancing both academic knowledge and practical applications, making him a highly deserving candidate for the Best Researcher Award.

Profile: Scopus | Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

  • Alizadeh, M., Kalantari Khalil Abad, A. R., Jahani, H., & Makui, A. (2023). Prevention of post-pandemic crises: A green sustainable and reliable healthcare supply chain network design for emergency medical products. Journal of Cleaner Production, 139702. https://doi.org/10.1016/j.jclepro.2023.139702

  • Kalantari Khalil Abad, A. R., Barzinpour, F., & Pishvaee, M. S. (2023). Toward circular economy for pomegranate fruit supply chain under dynamic uncertainty: A case study. Computers & Chemical Engineering, 178, 108362. https://doi.org/10.1016/j.compchemeng.2023.108362

  • Kalantari Khalil Abad, A. R., & Pasandideh, S. H. R. (2022). Green closed-loop supply chain network design with stochastic demand: A novel accelerated Benders decomposition method. Scientia Iranica, 29(5), 2578–2592. https://doi.org/10.24200/sci.2022.55657

  • Kalantari Khalil Abad, A. R., Barzinpour, F., & Pishvaee, M. S. (2023). Green and reliable medical device supply chain network design under deep dynamic uncertainty: A novel approach in the context of COVID-19 outbreak. Applied Soft Computing, 110964. https://doi.org/10.1016/j.asoc.2023.110964

  • Kalantari Khalil Abad, A. R., & Pasandideh, S. H. R. (2021). Green closed-loop supply chain network design: A novel bi-objective chance-constraint approach. RAIRO-Operations Research, 55(2), 811–840. https://doi.org/10.1051/ro/2021035

Xinxin Wang | Engineering | Best Researcher Award

Published on by Forensic Scientist

Mr. Xinxin Wang | Engineering | Best Researcher Award

North China Electric Power University | China

Xinxin Wang is a driven and innovative PhD candidate at North China Electric Power University, whose work bridges advanced theoretical research with practical engineering solutions. With a strong foundation in machinery and power engineering, he has developed expertise in the design, analysis, and optimization of underground tunneling equipment, particularly Tunnel Boring Machines (TBMs). His career reflects a deep commitment to solving complex challenges in rock mechanics and engineering, supported by collaborative efforts with leading experts in China and abroad. His predictive models and design methods have significantly advanced tunneling efficiency, making him a promising leader in his field.

Professional Profile

Scopus

ORCID

Education

Xinxin Wang earned a Master’s degree in Machinery and Engineering from Inner Mongolia University of Science and Technology, followed by doctoral studies in Power Machinery and Engineering at North China Electric Power University. Selected for the prestigious National “Excellent Engineer Program,” he broadened his academic exposure through a joint doctoral program as a visiting scholar at the University of Pisa, Italy. This international engagement allowed him to integrate advanced European engineering practices with domestic innovation, enriching his academic and professional capabilities in tunneling technology and rock-breaking mechanics.

Experience

Xinxin Wang has actively participated in multiple national-level research projects, including those funded by the National Natural Science Foundation of China and the National High Technology Research and Development Program. His contributions extend to the development of proprietary software for calculating rock-breaking forces in TBM disc cutters and the creation of new cutterhead designs capable of handling varied geological conditions. He works closely with industry and academic partners to ensure his research outcomes are implemented in real-world projects, thus enhancing the efficiency, reliability, and cost-effectiveness of large-scale underground excavation.

Research Interest

His research focuses on intelligent control systems and energy efficiency analysis for advanced underground construction equipment, particularly TBMs. He is deeply engaged in studying the collaborative rock-breaking mechanism of disc cutters, developing predictive models for cutter forces and cutterhead torque, and designing innovative solutions to optimize performance in diverse geological settings. Additionally, his expertise spans rock mechanics, structural analysis, and the integration of advanced computational modeling techniques into engineering practice.

Awards

Xinxin Wang has received recognition for his scholarly achievements through competitive doctoral scholarships and honors for academic excellence. His innovative contributions to TBM rock-breaking mechanics, cutterhead design, and excavation efficiency have been widely acknowledged in professional circles. These recognitions underscore his potential to make sustained and transformative contributions to the tunneling and underground engineering sector, making him a strong candidate for the Best Researcher Award.

Publications

Title: Investigation into the Rock-Breaking Forces of TBM Disc Cutters with Diverse Edge Shapes
Journal: Rock Mechanics and Rock Engineering
Published on: 2025

Title: Study on the Rock-Breaking Forces of TBM Disc Cutters with Uneven Wear
Journal: Chinese Journal of Theoretical and Applied Mechanics
Published on: 2025

Title: Study on Fatigue Characteristics of High-Pressure Vessel with Multiple Cracks in Stages
Journal: Mechanical Design and Manufacturing
Published on: 2024

Title: Allowable Limit of Crack Defect Zone Evaluation under Expected Life of Ultra-high Pressure Vessel Head
Journal: Thermal Processing Technology
Published on: 2024

Conclusion

By combining theoretical innovation with real-world engineering solutions, Xinxin Wang has made impactful contributions to the science and technology of tunnel boring and underground excavation. His research has not only improved operational efficiency but has also reduced construction costs and enhanced safety in challenging environments. With proven academic excellence, international collaboration experience, and a strong record of published work, he exemplifies the qualities of a dedicated and forward-thinking researcher worthy of the Best Researcher Award.

Suganya | Engineering | Best Researcher Award

Published on by Forensic Scientist

Dr. Suganya | Engineering | Best Researcher Award

Assistant Professor | SRM Institute of Science and Technology | India

Y. Suganya, M.E., (Ph.D.), is a dedicated academic professional with over 14 years of teaching experience in Computer Science and Engineering. Her research focuses on machine learning and deep learning techniques for ovarian cyst classification and prediction. She has contributed significantly to academia through publications, conference presentations, and departmental leadership.

Professional profile👤

Google Scholar

Strengths for the Awards✨

  • Research Excellence: Y. Suganya has a strong research background, with a focus on machine learning and deep learning applications in medical imaging, particularly ovarian cyst classification. Her Ph.D. work aligns well with contemporary research trends in AI-driven healthcare.
  • Publication Record: She has published extensively in reputable journals and conferences, including Springer and IEEE Xplore, with multiple papers indexed in Scopus. These publications demonstrate the depth and quality of her research.
  • Teaching and Mentorship: Nearly 15 years of teaching experience, with a proven track record of producing 100% results in several semesters, indicates her commitment to education and mentorship.
  • Leadership and Service: She has taken on significant responsibilities such as coordinating accreditation processes (NBA), acting as Chief Superintendent for examinations, and serving as a journal reviewer. These roles highlight her leadership skills and service to the academic community.
  • Technical Proficiency: Proficiency in programming languages like Python, C, C++, and Java supports her research in machine learning and data analysis, making her technically well-equipped.

🎓 Education

  • Ph.D. (Computer Science and Engineering)
    • Annamalai University, Tamil Nadu, India
    • Thesis: “Classification and Prediction of Ovarian Cysts Using Machine Learning and Deep Learning Techniques” (Thesis Submitted: October 16, 2023)
  • Master of Engineering (Computer Science and Engineering)
    • MIET College of Engineering (Affiliated to Anna University), Tamil Nadu, India (June 2011) – CGPA: 8.22 (First Class)
  • Bachelor of Engineering (Computer Science and Engineering)
    • Royal College of Engineering (Affiliated to Anna University), Tamil Nadu, India (April 2005) – Percentage: 66.6% (First Class)

💼 Experience

  • Assistant Professor
    • Mookambigai College of Engineering, Tamil Nadu, India (June 24, 2011 – Present)
  • Lecturer
    • Idhaya College of Engineering for Women, Tamil Nadu, India (January 2, 2006 – April 15, 2007)

🔬 Research Interests On Engineering

  • Machine Learning and Deep Learning
  • Medical Image Processing
  • Ovarian Cyst Classification and Prediction
  • Artificial Intelligence in Healthcare

🏆 Awards

  • Annual Membership in ACM Professional Membership (ID: 5666897)
  • Reviewer for Journal Manuscript (Signal, Image, and Video Processing – Springer Nature) – November 8, 2024
  • Chief Superintendent for Theory Examination (Nov/Dec 2023), Anna University
  • Coordinated NBA Accreditation Work for the Computer Science Department

📝 Publications

  • Title: A diagnosis of ovarian cyst using deep learning neural network with XGBoost algorithm
    Authors: Y Suganya, S Ganesan, P Valarmathi, T Suresh
    Year: 2023
    Citations: 17

  • Title: Ultrasound ovary cyst image classification with deep learning neural network with Support vector machine
    Authors: Y Suganya, S Ganesan, P Valarmathi
    Year: 2022
    Citations: 11

  • Title: Classification of medical x-ray images for automated annotation
    Authors: S Ganesan, TS Subashini
    Year: 2014
    Citations: 10

  • Title: Novel approach of internet of things (IoT) based smart ambulance system for patient’s health monitoring
    Authors: A Bekkanti, R Aishwarya, Y Suganya, P Valarmathi, S Ganesan, …
    Year: 2021
    Citations: 7

  • Title: Classification of X-rays using statistical moments and SVM
    Authors: S Ganesan, TS Subashini, K Jayalakshmi
    Year: 2014
    Citations: 7

  • Title: An approach toward the efficient indexing and retrieval on medical X-ray images
    Authors: S Ganesan, TS Subashini
    Year: 2013
    Citations: 7

  • Title: A content based approach to medical X-Ray image retrieval using texture features
    Authors: S Ganesan, TS Subashini
    Year: 2014
    Citations: 6

  • Title: A Comparative Study on Consumer Courts in Tamil Nadu & Kerala States-A Statistical Survey Report
    Authors: BY Krishna, Y Suganya
    Year: 2011
    Citations: 5

  • Title: Fuzzy based detection and swarm based authenticated routing in MANET
    Authors: K Shanthi, T Jebarajan, P Sampath, W AMITABH, D RAMYA, …
    Year: 2014
    Citations: 3

  • Title: Comparative analysis of ovarian images classification for identification of cyst using ensemble method machine learning approach
    Authors: Y Suganya, S Ganesan, P Valarmathi
    Year: 2022
    Citations: 2

📊 Conclusion

Y. Suganya is a passionate educator and researcher who has made remarkable contributions to machine learning and medical image processing, specifically focusing on ovarian cyst classification and prediction. With a wealth of teaching experience, active participation in departmental responsibilities, and numerous research publications, she continues to inspire and shape the future of computer science students.

Zejie Yu | Engineering | Best Researcher Award

Published on by Forensic Scientist

Prof. Dr. Zejie Yu | Engineering | Best Researcher Award

Zhejiang University | China

Zejie Yu is a tenure-track professor at Zhejiang University in Hangzhou, China. With a strong foundation in optical and electronics engineering, he has contributed significantly to the fields of integrated photonics, nonlinear optics, and microwave photonics. His career began with his undergraduate studies at Zhejiang University, followed by a Ph.D. and postdoctoral research at The Chinese University of Hong Kong. He currently holds a prominent role in advancing photonic technologies and has made notable contributions to research in photonic chips and optical modulators.

Profile

Google Scholar

Orcid

Scopus

Strengths for the Awards

  • Academic and Professional Background:
    • Zejie Yu holds a B.S. in Optical Engineering and a Ph.D. in Electronics Engineering, with a strong track record of postdoctoral research and current tenure-track professorship at Zhejiang University. His expertise spans integrated photonics, nonlinear optics, and microwave photonics, which are highly relevant to contemporary technological advancements.
  • Research Output:
    • His extensive publication list, featuring high-quality papers in top-tier journals like Advanced Science, Nanophotonics, Laser & Photonics Reviews, and ACS Photonics, showcases his active and innovative contributions to the field of photonics.
    • His work often addresses cutting-edge technologies, such as electro-optic modulators, supercontinuum generation, and high-bandwidth integrated photonics.
  • Professional Engagement:
    • Zejie Yu’s roles as a TPC member for conferences like ACP 2020 and 2021, as well as his position as a guest editor for JOSA B and Chinese Optics Letters, illustrate his leadership in advancing the field.
    • He has been invited to give talks at major international conferences, signifying his recognition and influence among peers.
  • Research Funding:
    • His involvement in prestigious research projects funded by the National Natural Science Foundation of China and other significant national programs highlights his ability to secure funding for innovative and impactful research.

Education🎓

Zejie Yu’s academic journey began with a Bachelor of Science in Optical Engineering from Zhejiang University, China, in 2015. His focus on advanced engineering education led him to the prestigious Chinese University of Hong Kong, where he earned his Ph.D. in Electronics Engineering in 2019. He continued his research there as a postdoctoral fellow before joining Zhejiang University as a faculty member in 2020.

Experience📈

After completing his Ph.D., Zejie Yu worked as a postdoctoral researcher at The Chinese University of Hong Kong, where he honed his expertise in photonics and optics. In 2020, he transitioned to Zhejiang University as a tenure-track professor, where he continues to lead significant research projects. He also actively contributes to the scientific community as a young editor for Chinese Optics Letters and as a guest editor for JOSA B.

Research Interest On Engineering🔬

Zejie Yu’s primary research interests include integrated photonics, nonlinear optics, and microwave photonics. His work focuses on developing advanced photonic devices, including high-performance optical modulators, photonic chips, and the application of lithium niobate in integrated photonics. His ongoing projects aim to push the boundaries of photonic technologies for future communication and computing applications.

Award🏆

Zejie Yu’s innovative contributions to photonics have earned him recognition in the scientific community. His research has been featured in top-tier journals and presented at various international conferences. While specific awards are not mentioned, his contributions to the field have undoubtedly positioned him as a leading figure in photonics research.

Publication📚

  • Photonic integrated circuits with bound states in the continuum
    • Authors: Z Yu, X Xi, J Ma, HK Tsang, CL Zou, X Sun
    • Year: 2019
    • Citations: 179
  • Genetic-algorithm-optimized wideband on-chip polarization rotator with an ultrasmall footprint
    • Authors: Z Yu, H Cui, X Sun
    • Year: 2017
    • Citations: 139
  • Acousto-optic modulation of photonic bound state in the continuum
    • Authors: Z Yu, X Sun
    • Year: 2020
    • Citations: 133
  • High-dimensional communication on etchless lithium niobate platform with photonic bound states in the continuum
    • Authors: Z Yu, Y Tong, HK Tsang, X Sun
    • Year: 2020
    • Citations: 128
  • Ultralow‐loss silicon photonics beyond the singlemode regime
    • Authors: L Zhang, S Hong, Y Wang, H Yan, Y Xie, T Chen, M Zhang, Z Yu, Y Shi, …
    • Year: 2022
    • Citations: 89
  • Genetically optimized on-chip wideband ultracompact reflectors and Fabry–Perot cavities
    • Authors: Z Yu, H Cui, X Sun
    • Year: 2017
    • Citations: 89
  • Inverse-designed low-loss and wideband polarization-insensitive silicon waveguide crossing
    • Authors: Z Yu, A Feng, X Xi, X Sun
    • Year: 2018
    • Citations: 60
  • Gigahertz acousto-optic modulation and frequency shifting on etchless lithium niobate integrated platform
    • Authors: Z Yu, X Sun
    • Year: 2021
    • Citations: 57
  • Ultranarrow-band metagrating absorbers for sensing and modulation
    • Authors: A Feng, Z Yu, X Sun
    • Year: 2018
    • Citations: 56
  • Compact electro-optic modulator on lithium niobate
    • Authors: B Pan, H Cao, Y Huang, Z Wang, K Chen, H Li, Z Yu, D Dai
    • Year: 2022
    • Citations: 55

Conclusion🔮

Zejie Yu’s academic and professional trajectory exemplifies a commitment to advancing the field of integrated photonics. His impressive educational background, extensive research, and leadership in numerous professional activities reflect his significant contributions to photonics. His continued success as a tenure-track professor at Zhejiang University promises further innovation and breakthroughs in the field of photonic engineering.