Xifeng Xie | Engineering | Best Researcher Award

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Prof. Xifeng Xie | Engineering | Best Researcher Award

Professor of Electrical Engineering at Southwest Jiaotong University, China

Prof. Xifeng Xie is a Professor at the School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China. He holds B.S. and M.S. degrees in Electrical Engineering from the same university and is currently pursuing a Ph.D. in Energy and Power Engineering. Since 2006, he has been actively engaged in academia and industry, with a professorship at Guangxi Vocational College of Water Resources and Electric Power since 2019. His research focuses on battery chargers, power electronic converters, and reactive power compensators. He has published 8 SCI/Scopus-indexed journal articles, authored 2 books, holds 7 patents, and has led several funded research and industry projects. Prof. Xie’s innovations—such as an isolated resonant voltage balancing circuit—have significantly improved system efficiency and reduced operational costs. He is also a reviewer for Hongshui River Magazine and a member of the Chinese Society for Electrical Engineering.

Profile:

🏛️ Institution & Designation:

Professor, School of Electrical Engineering
Southwest Jiaotong University, Chengdu, China

🎓 Academic Background:

Prof. Xie earned his B.S. and M.S. in Electrical Engineering from Southwest Jiaotong University in 2002 and 2006. He is currently pursuing a Ph.D. in Energy and Power Engineering at the same institution.

👨‍🏫 Professional Journey:

Since 2006, he has served at Guangxi Vocational College of Water Resources and Electric Power and became a full professor in 2019.

⚡ Research Areas:

His research focuses on:

  • 🔋 Battery chargers

  • 🔌 Power electronic converters

  • ⚙️ Reactive power compensators

🧠 Key Contributions:

He has developed an isolated resonant voltage balancing circuit and dead-time compensation strategy, leading to:

  • 🔽 Current unbalance reduced to 2.6%

  • ⚡ Power factor improved to 0.997

  • 🚀 Efficiency increased to 98.2%

  • 💰 Reduced component count and system costs

📊 Research & Innovation:

  • 🧪 Research Projects: 3 completed/ongoing

  • 🏭 Industry Projects: 5

  • 📖 Books Published: 2 (ISBN)

  • 🧾 Patents: 7 (published/under process)

  • 📚 Journals (SCI/Scopus): 8

  • ✍️ Editorial Role: Reviewer, Hongshui River Magazine

🌐 Collaborations & Memberships:

  • 🤝 Collaborator with the National Natural Science Foundation of China

  • 🎓 Distinguished Scholar Program of Guangxi Higher Education Institutions

  • 🔧 Member, Chinese Society for Electrical Engineering

Publication Top Notes:

  1. The Constant Power Transmission Control for Suppressing DC-Link Voltage Ripple Effect of Single-Phase AC–DC–AC Converter
    IEEE Transactions on Power Electronics, August 2025.
    DOI: 10.1109/TPEL.2025.3556470
    Authors: Minyang Zou, Linghui Meng, Jianglin Nie, Jiajin Li, Linzhe Li, Xiao Lv, Cheng Zhang, Xifeng Xie, Zeliang Shu

  2. Predictive Control Method with Conduction Mode Detection to Suppress Input Current Distortion of Three-Level Power Factor Correction
    IET Electric Power Applications, November 2024.
    DOI: 10.1049/elp2.12491
    Authors: Xifeng Xie, Zeliang Shu, Rongxin Chen, Jianghong Yin, Chunxiang Ling

 

Ms. HAFSA ANAM | Engineering | Best Researcher Award

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Ms. HAFSA ANAM | Engineering | Best Researcher Award

Macquarie University, Australia

Author Profile

Scopus

Orcid

Education 🎓

Hafsa completed her B.Sc. in Telecommunication Engineering in 2015 with a CGPA of 3.78/4.00, and later earned her M.Sc. in Telecommunication Engineering in 2017 with a CGPA of 3.79/4.00, both from the University of Engineering and Technology (UET), Taxila, Pakistan. Currently, she is pursuing her Ph.D. at Macquarie University, working on smart RFID sensor systems for IoT applications.

Professional Experience 💼

As part of her doctoral journey, Hafsa has worked as a Teaching Associate at Macquarie University, actively supporting undergraduate courses. Her role involved lectures, lab sessions, and student mentoring, enabling her to blend cutting-edge research with academic leadership. She also collaborates with interdisciplinary teams to design real-world applicable sensor systems.

Technical Skills 🛠️

Her core strengths lie in chipless RFID design, electromagnetic modeling, wireless communication systems, and flexible sensor fabrication. She is skilled in tools and techniques for antenna design, EM simulations, and printable electronics, with a focus on green, passive, and cost-effective RFID systems.

Teaching Experience👨‍🏫

Hafsa has contributed to several B.Sc. units as a Teaching Associate at Macquarie University. She has assisted in course delivery, lab experiments, and student project supervision, helping to bridge practical RFID development with academic theory.

Awards & Honors 🏅

Hafsa has been recognized with the Post Graduate Research Fund (PGRF) from Macquarie University in 2024 and is the recipient of a fully-funded Ph.D. scholarship (2022–present). Her research excellence earned her the Best Poster Presentation Award at the HDR Conference at Macquarie University in 2022, marking her as an emerging scholar in the RFID research community.

Research Interests 🔍

Her research is centered on chipless RFID tags, wireless communication, electromagnetics, and the Internet of Things (IoT). She is especially interested in developing multifunctional, battery-free RFID sensors that are capable of monitoring environmental parameters, with applications in recycling, smart infrastructure, retail, and industrial systems.

Publications Top Notes: 📝

Dual Sided Data Dense 25-bit Chipless RFID Tag

Authors: Hafsa Anam, Syed Muzahir Abbas, Subhas Mukhopadhyay, Iain Collings

Publication Year: 2023

Publication Type: Conference Paper

RFID Enabled Humidity Sensing and Traceability

Authors: Hafsa Anam, Syed Muzahir Abbas, Iain Collings, Subhas Mukhopadhyay

Publication Year: 2023

High-density Compact Chipless RFID Tag for Item-level Tagging

Authors: Ayesha Habib, Hafsa Anam, Yasar Amin, Hannu Tenhunen

Publication Year: 2018

 Internet-of-things Based Smart Tracking

Author: Hafsa Anam

Publication Year: 2017

Miniaturized Humidity and Temperature Sensing RFID Enabled Tags

Authors: Javeria Anum Satti, Ayesha Habib, Hafsa Anam, Sumra Zeb, Yasar Amin, Jonathan Loo, Hannu Tenhunen

Publication Year: 2018

Journal: International Journal of RF and Microwave Computer-Aided Engineering

Papdo Tchasse | Engineering | Elite Academic Visionary Award

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Mr. Papdo Tchasse | Engineering | Elite Academic Visionary Award

Institute of Forming Technology, University of Stuttgart Germany

Hans Dimitri Papdo Tchasse, born on July 14, 1996 in Cameroon 🇨🇲, is a dynamic scientific researcher in the field of forming technology, digitalization, and artificial intelligence. Currently based in Germany 🇩🇪, he works as a Research Associate at the Institute for Metal Forming Technology, University of Stuttgart. With a strong background in mechatronics and AI-driven manufacturing, he bridges academic research and industrial innovation to optimize forming processes and predictive control systems in manufacturing.

Profile

Scopus

Orcid

🎓 Education

Hans pursued his Bachelor’s and Master’s degrees in Mechatronics from Friedrich-Alexander University Erlangen-Nuremberg (FAU) between 2016 and 2022. His Master’s thesis, graded 1.3, focused on predicting process quality using machine learning, while his Bachelor’s thesis (graded 1.7) involved autonomous collision avoidance systems for aerial robots. He also completed intensive German language training at Karlsruhe Institute of Technology (DSH 3) and the Goethe Institute Yaoundé (B1 certificate) to facilitate his academic career in Germany. 📘🔧

💼 Professional Experience

Since July 2022, Hans has been working at the University of Stuttgart, where he leads several AI-driven research projects in forming technology and supervises students. His work emphasizes process simulation, sensor technology, and digital automation. Previously, at Siemens AG – Digital Industries, he contributed to the development of HMI interfaces, PLC programming, and machine learning applications for quality optimization. His blend of industrial and academic experience uniquely positions him to innovate in the manufacturing sector. 🏭💡

🔬 Research Interests

Hans is passionate about advancing digital manufacturing, with research focused on:

  • Metal forming and shear cutting
  • Sensor-based process monitoring
  • Artificial Intelligence in manufacturing
  • Deep learning for quality prediction
  • Human-centered smart factories His projects aim to make production more adaptive, efficient, and intelligent, promoting sustainability and digital transformation in the automotive and metal industries. 🤖📊

🏆 Awards & Nominations

Hans is a promising young innovator being nominated for this award due to his cutting-edge contributions in intelligent forming technologies and real-world application of AI in mechanical engineering. His interdisciplinary expertise, leadership in research, and publications in reputable conferences make him a strong candidate for distinction. 🌟👏

📚 Publications Top Notes: 

Hans has authored several high-impact publications in international conferences and journals, reflecting his interdisciplinary expertise.
Here’s a list of selected publications:

Detection of Defective Deep Drawn Sheet Metal Parts by Using Machine Learning Methods for Image Classification – WGP 2023 📅 (Cited by: 4)

Temperature Prediction of Multi-Stage Cold Forging Processes Using Deep Learning – SENAFOR 2024 (upcoming) 📅

Development of an Intelligent Metal Forming Robot and Application to Multi-Stage Cold Forging – Submitted 📤

Supervised Learning Methods for the Monitoring and Prediction of the Part Quality of Multi-Stage Cold Forging Processes – ICFG 2024 (accepted) 📅

Material Characterization for Sheet Metal Forming Processes Using Deep Learning Methods for Time Series Processing – TMS 2025 (upcoming) 📅

Simulative Design of a Model-Driven Control Strategy for Deep Drawing Processes and Numerical Validation Using Deep Learning – WGP 2024 (accepted) 📅

Monitoring and Prediction of the Process Energy in Multi-Stage Cold Forging Using Recurrent and Self-Attention Based Neural Networks – Submitted 🧠

Yusuf Alper KAPLAN | Engineering | Best Researcher Award

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Prof. Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Osmaniye Korkut Ata Unv. Turkey

Dr. Yusuf Alper Kaplan is a Professor of Energy Systems Engineering at Osmaniye Korkut Ata University in Turkey. He has a distinguished career in renewable energy, specializing in solar and wind energy modeling, estimation, and system performance. With over two decades of experience, Dr. Kaplan has contributed to advancing energy systems through innovative methodologies and predictive models.

Profile

Google scholar

Education 🎓

  • Bachelor’s in Electrical and Electronics Engineering, Gaziantep University, 2002
  • Master’s in Electrical and Electronics Engineering, Çukurova University, 2008
  • Ph.D. in Electrical and Electronics Engineering, Anadolu University, 2014

Professional Experience 💼

  • Lecturer (2004-2009) at Çukurova University
  • Research Assistant (2010-2014) at Anadolu University
  • Assistant Professor (2014-2018), Associate Professor (2018-2023), and Professor (2023-present) at Osmaniye Korkut Ata University
  • Head of Department of Energy Systems Engineering (2019-2020)
  • Director of the Continuing Education Centre (2020-present)

Research Interests 🔬

Dr. Kaplan’s research focuses on renewable energy, especially solar and wind energy systems. His work involves developing statistical and computational models for solar radiation forecasting, wind energy assessment, and performance optimization of renewable energy sources in varying environmental conditions.

Awards and Recognitions 🏆

Dr. Kaplan has been honored for his contributions to renewable energy and academic excellence. His achievements include national and international recognitions for advancements in energy system performance modeling and contributions to sustainable energy solutions.

Publications Top Notes: 📚

Kaplan, Y. A. (2024). Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 136, 109034. (Cited by 15)

Kaplan, A. G., & Kaplan, Y. A. (2024). Using of the Weibull distribution in developing global solar radiation forecasting models. Environmental Progress & Sustainable Energy. (Cited by 10)

Kaplan, Y. A. (2023). Development of backpropagation algorithm for estimating solar radiation: A case study in Turkey. Revue Roumaine des Sciences Techniques, 68(3), 313-316. (Cited by 8)