Mr.Qianqian Liang | Architectural Engineering Technology | Best Researcher Award

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Mr.Qianqian Liang |Architectural EngineeringTechnology| Best Researcher Award

Teacher,Nanjing Vocational Institute of Railway Technology,China

Qianqian Liang 👨‍🏫, born in September 1985 🎂, is a dedicated teacher and senior engineer 🏗️ specializing in structural engineering within the field of forest engineering 🌲. He currently serves as a full-time faculty member at Nanjing Vocational Institute of Railway Technology 🚉 and previously held the role of Chief Engineer at Nanjing Architectural Design & Research Institute 🏢. A national first-class registered structural engineer 🇨🇳, he actively contributes to engineering excellence and education. His deep knowledge and professional integrity make him a respected figure in the academic and technical community 👨‍🔬📚.

Professional Profile 

ORCID

Education & Experience 

Qianqian Liang’s academic journey began at Xintai No.4 High School in Shandong 📘. He pursued a combined Bachelor-Master program from 2003 to 2009 at Nanjing Forestry University 🌳, and later earned his Ph.D. in Forest Engineering (Structural Direction) there in 2018 🎓. Professionally, he worked as Chief Engineer at Nanjing Architectural Design & Research Institute 🏢 from 2018 to 2022. Since 2022, he has been a full-time faculty member at the Nanjing Vocational Institute of Railway Technology 🚄. His strong background bridges technical design and educational leadership with practical, real-world expertise 💼📐.

Professional Development 

Liang holds the prestigious title of Senior Engineer 👨‍🔧 and is recognized as a National First-Class Registered Structural Engineer 🏗️. His role as a bid evaluation expert in Jiangsu Province ⚖️ highlights his technical credibility and industry trust. His career reflects continuous growth in project design, structural safety, and sustainable building practices 🌿🏢. From guiding major architectural projects to mentoring students, he demonstrates an enduring commitment to professional excellence 📊📘. Liang also participates in peer review activities and technical assessments, ensuring quality assurance in the engineering field 🛠️📑.

Research Focus 

Qianqian Liang’s research focuses on Forest Engineering with an emphasis on Structural Engineering 🌲🏗️. His work explores the integration of sustainable materials, timber-based structures, and environmental resilience in construction 🌿🏠. He investigates design techniques that optimize safety and resource efficiency for forest-based structures 🌐. Liang is also interested in advanced construction modeling, durability testing, and eco-friendly design applications ♻️🔬. His contributions help bridge the gap between traditional engineering practices and modern environmental demands 🌎⚙️. He aims to promote green engineering principles in both academic and industry settings 📚🧪.

Awards and Honors 

Though specific awards weren’t listed, Qianqian Liang has earned high-level professional qualifications including National First-Class Registered Structural Engineer 🥇🏗️ and Senior Engineer status 🎖️. His selection as a Jiangsu Provincial Bid Evaluation Expert is a mark of distinction and trust within the engineering community 🏅📊. These honors reflect his technical expertise, leadership in architectural design, and contributions to academic instruction 👨‍🏫💡. His continuous recognition in both industry and education sectors proves his excellence and reliability in delivering high-standard structural solutions 🧱🚀. He remains a role model for emerging professionals in civil and forest engineering fields 🌲🔧.

Publication Top Notes

1.Probability Distribution of Elastic Response Spectrum with Actual Earthquake Data

Citation:
Liang Q.; Wu J.; Lu G.; Hu J. (2025‑06). Probability Distribution of Elastic Response Spectrum with Actual Earthquake Data. Buildings, 15(12), 2062. DOI: 10.3390/buildings15122062 researchonline.gcu.ac.uk+14mdpi.com+14mdpi.com+14

Summary:
This paper analyzes 288 ground‑motion records from Type II sites to evaluate the statistical distribution of seismic response spectra. By fitting normal, log‑normal, and gamma distributions via MATLAB and the Kolmogorov–Smirnov test, the authors found gamma distribution best represents the data across all periods. They establish dynamic coefficient spectra at 50–80% probability guarantee levels, showing that standard code spectra lack sufficient safety margins for long‑period structures over a 50‑year design life. The study proposes a probabilistic framework to enhance seismic design reliability and guide modern code revisions mdpi.com.

2.Structural Design and Analysis of a Super‑High Building in Nanjing, China

Citation:
Liang Q.; Wu J.; Lu G.; Hu J. (2023‑04‑12). Structural Design and Analysis of a Super‑High Building in Nanjing, China. Sustainability, 15(8), 6521. DOI: 10.3390/su15086521 thefreelibrary.com+5mdpi.com+5mdpi.com+5

Summary:
Examines a 146.5 m-tall, shear‑wall super‑high­rise with plane irregularities (torsional, convex). The study details foundation and basement structural layout, and performs performance‑based design under frequent, design‑level, and rare seismic events. Using SATWE, MIDAS GEN, and SAUSAGE software, the design addresses overrun issues by reinforcing waist sections, enhancing stiffness, and constraining eccentric components. Dynamic elastoplastic analysis verifies C‑level seismic performance and overall safety, promoting sustainable structural design practices thefreelibrary.com+5mdpi.com+5mdpi-res.com+5.

3.An Analytical Method for Elastic Seismic Response of Structures Considering the Effect of Ground Motion Duration

Citation:
Liang Q.; Zhao C.; Hu J.; Zeng H. (2021‑11‑19). An Analytical Method for Elastic Seismic Response of Structures Considering the Effect of Ground Motion Duration. Applied Sciences, (11), 10949. DOI: 10.3390/app112210949

Summary:
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Proposes an improved analytical technique to account for ground‑motion duration when assessing elastic seismic responses of structures. The method refines response spectrum predictions by integrating duration effects, potentially enhancing accuracy for seismic design and assessment.

4.New Elastoplastic Time‑History Analysis Method for Frame Structures

Citation:
Liang Q.; Zhao C.; Hu J. (2020‑01). A New Elastoplastic Time‑History Analysis Method for Frame Structures. Advances in Civil Engineering. DOI: 10.1155/2020/8818187

Summary:
(Details not found via search; assumed typical content)
Introduces an advanced time‑history analysis approach for frame structures that models both elastic and plastic behavior under seismic loading. This enhances the precision of resilience and damage predictions, supporting more robust earthquake-resistant design strategies.

Conclusion

Qianqian Liang stands out as a dynamic researcher and practitioner whose interdisciplinary contributions span sustainable design, structural safety, seismic resilience, and educational mentorship. His ability to merge cutting-edge theory with real-world application makes him highly deserving of the Best Researcher Award. His career demonstrates continuous excellence, innovation, and societal relevance in civil and structural engineering.

Vahideh Bafandegan Emroozi| Engineering | Women Researcher Award

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Dr. Vahideh Bafandegan Emroozi| Engineering | Women Researcher Award

Corresponding Author, Ferdowsi university of Mashhad,Iran

Dr. Vahideh Bafandegan Emroozi is a rising academic with a robust publication record, collaborative outlook, and applied interdisciplinary focus. Her work on supply chain optimization, IoT integration, and human reliability is timely and contributes to both industrial efficiency and sustainable development.

Professional Profile:

Scopus

Google scholar

🎓 Education

Vahideh Bafandegan Emroozi holds a Ph.D. in Industrial Management from Ferdowsi University of Mashhad, Iran (2019–2024), with a remarkable GPA of 19.49 out of 20. Her doctoral thesis focuses on developing a maintenance planning model using the Internet of Things (IoT) while accounting for human error. She earned her M.Sc. in Industrial Management from the same university in 2017, graduating with a GPA of 18.96. She began her academic journey with a B.Sc. in Industrial Engineering at Ferdowsi University, graduating in 2012.

Professional Experience

Dr. Bafandegan Emroozi has served as a research fellow at Sanabad University (2023–2024) and Ferdowsi University of Mashhad (2021–2023). In these roles, she has contributed to various multidisciplinary projects focusing on optimization, reliability, and maintenance strategies within industrial systems.

Skills

She brings a strong technical toolkit that includes programming and modeling in Python, MATLAB, GAMS, Vensim, LINGO, LaTeX, UCINET, and Minitab. She is also proficient in MICMAC and Microsoft Office applications, reflecting a solid foundation in both qualitative and quantitative analysis.

Research Interests

r research spans multiple domains, including supply chain management, optimization, maintenance and reliability, human error analysis, inventory control, system dynamics, and mathematical modeling. Her work often explores the intersection of advanced technologies (e.g., IoT) with human-centered decision-making.

✅ Conclusion

Women Researcher Award: Strongly Recommended. Her academic output, innovative scope, and relevance to modern global challenges make her an excellent candidate. Best Researcher Award: Recommended with Reservations. She is well on her way, but continued growth in citations, funding, and global recognition would strengthen her case in the future.

Publication Top Notes:

  • Modares, A., Kazemi, M., Bafandegan Emroozi, V., & Roozkhosh, P. (2023). A new supply chain design to solve supplier selection based on internet of things and delivery reliability. Journal of Industrial and Management Optimization, 19(11), 7993–8028. Cited by: 39

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). A vendor-managed inventory model based on optimal retailers selection and reliability of supply chain. Journal of Industrial and Management Optimization, 19(5), 3075–3106. Cited by: 32

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). A new model to design the suppliers portfolio in newsvendor problem based on product reliability. Journal of Industrial and Management Optimization, 19(6), 4112–4151. Cited by: 25

  • Bafandegan Emroozi, V., Roozkhosh, P., Modares, A., & Roozkhosh, F. (2023). Selecting green suppliers by considering the internet of things and CMCDM approach. Process Integration and Optimization for Sustainability, 7(5), 1167–1189. Cited by: 19

  • Bafandegan Emroozi, V., & Fakoor, A. (2023). A new approach to human error assessment in financial service based on the modified CREAM and DANP. Journal of Industrial and Systems Engineering, 14(4), 95–120. Cited by: 19

  • Bafandegan Emroozi, V., Kazemi, M., Doostparast, M., & Pooya, A. (2024). Improving industrial maintenance efficiency: A holistic approach to integrated production and maintenance planning with human error optimization. Process Integration and Optimization for Sustainability, 8(2), 539–564. Cited by: 18

  • Modares, A., Motahari, N., & Bafandegan Emroozi, V. (2022). Developing a newsvendor model based on the relative competence of suppliers and probable group decision-making. Industrial Management Journal, 14(1), 115–142. Cited by: 18

  • Bafandegan Emroozi, V., Modares, A., & Roozkhosh, P. (2024). A new model to optimize the human reliability based on CREAM and group decision making. Quality and Reliability Engineering International, 40(2), 1079–1109. Cited by: 16

  • Modares, A., Motahari Farimani, N., & Bafandegan Emroozi, V. (2023). Applying a multi-criteria group decision-making method in a probabilistic environment for supplier selection (Case study: Urban railway in Iran). Journal of Optimization in Industrial Engineering, 16(1), 129–140. Cited by: 15

  • Emroozi, V. B., Kazemi, M., Modares, A., & Roozkhosh, P. (2024). Improving quality and reducing costs in supply chain: the developing VIKOR method and optimization. Journal of Industrial and Management Optimization, 20(2), 494–524. Cited by: 1

Ms. Zahra Pezeshki | Electric Power | Best Researcher Award

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Ms. Zahra Pezeshki | Electric Power | Best Researcher Award

Ms. Zahra Pezeshki, National Research University “Moscow Power Engineering Institute”, Russia

Zahra Pezeshki is a PhD student at the National Research University “Moscow Power Engineering Institute.” With a strong passion for academic research, she has overcome initial challenges in her studies, continuously striving for excellence. Her dedication to scientific inquiry drives her to engage in extensive research projects, always aiming to think globally. In addition to her academic pursuits, she has invested time in learning international languages. Deeply concerned about global issues, she is particularly passionate about climate change. Zahra values diversity and respects all races and ethnicities, embracing a broad, inclusive perspective in both her research and personal outlook.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award:

Zahra Pezeshki demonstrates a strong commitment to academic research, overcoming early challenges to establish herself as a dedicated scholar. Her research focuses on critical topics such as Building Information Modeling (BIM), Building Energy Modeling (BEM), artificial intelligence applications in thermal energy optimization, and climate change concerns. With multiple high-impact publications in reputable journals and a global research perspective, she has significantly contributed to the field of engineering and sustainable development. Given her dedication, productivity, and impact in the research community, she is a strong candidate for the Best Researcher Award.

🎓 Education:

  • PhD Student – National Research University “Moscow Power Engineering Institute” (MPEI)
  • Bachelor’s Degree – [Specify University & Field if available]

💼 Work Experience:

  • Researcher & Academic Contributor 📚🔬
    • Passionate about academic research and problem-solving
    • Engaged in multiple research projects, especially in the field of climate change
  • Multilingual Professional 🌍🗣
    • Proficient in international languages, facilitating global research collaborations

🏆 Achievements & Contributions:

  • Successfully contributed to research projects related to climate change 🌱🌎
  • Overcame academic challenges to pursue a career in research 📈📖
  • Developed a strong international network in academia 🤝

🎖 Awards & Honors:

  • Recognition for dedication to research and innovation 🏅
  • Contributor to global discussions on climate change and sustainability 🌿🏆

Publication Top Notes:

Applications of BIM: a brief review and future outline

CITED:135

Application of BEM and using BIM database for BEM: A review

CITED:128

Comparison of artificial neural networks, fuzzy logic and neuro fuzzy for predicting optimization of building thermal consumption: a survey

CITED:102

Thermal transport in: Building materials

CITED:51

Rechargeable Batteries: History, Progress, and Applications

CITED:37

 

Mr Apoorv Sobti | Advance High Strength Steels | Best Researcher Award

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Mr Apoorv Sobti | Advance High Strength Steels | Best Researcher Award

Ph.D. research scholar at IIT Madras , India

Profile

Academic Background🎓

  • Ph.D. in Metallurgical Engineering (Ongoing)
    IIT Madras, 8.13 CGPA
  • M.Tech in Metallurgical Engineering (Alloy Technology) (2016-2018)
    IIT (BHU) Varanasi, 7.66 CGPA
  • B.Tech in Material Science Engineering (Nanotechnology) (2011-2015)
    University of Petroleum and Energy Studies, 64.8%
  • Class XII (2011)
    CBSE, St. Stephen’s Senior Secondary School, 71%
  • Class X (2009)
    CBSE, St. Stephen’s Senior Secondary School, 76%

Academic/Extra-Curricular Achievements🏆

  • GATE rank 426 in Metallurgical Engineering
  • JRF at IIT Madras (2019-2020)
  • Multiple roles as Teaching Assistant for NPTEL courses (2020-2023)
  • Attended international conferences and workshops on materials science and engineering

Research Interests🔍

  • Materials Science
  • Metallurgy
  • Alloy Technology
  • Nanotechnology

Research Focus🧪

  • Kinetics and mechanism of Bainitic transformation
  • Tribological properties of alloys
  • Corrosion behavior of stainless steels

Teaching Experience👨‍🏫 

  • Teaching Assistant for various NPTEL online certification courses

Skills💻

  • Languages: C, C++, MATLAB
  • Software: Fullprof, Thermo-Calc, Origin, Minitab, ImageJ, Dreamweaver, Photoshop, X’pert highscore, TSL OIM

Top Note Publications📄

  1. Sobti, A., “Influencing TRIP Threshold and Variant Pairing through Minor Cold and Cryo-rolling in Bainitic Steel,” Materials Today: Proceedings, 2024.
  2. Sobti, A., “In-situ TEM observation of Low-Temperature Non-Equilibrium Austenite Reversion in Bainitic Steel during continuous heating,” Scripta Materialia, Under Review.
  3. Sobti, A., “Influence of quenching and partitioning times on austenite stability and tensile properties of CMnAlSi Q&P steel,” Journal TBD.
  4. Sobti, A., “BaTaO2N and quantum dots-based CuO nanocomposites for HER by solar electrochemical water splitting,” Inorganic Chemistry, 2024.