LEI JIA | Structural Health Monitoring | Best Researcher Award

Prof. LEI JIA | Structural Health Monitoring | Best Researcher Award

Doctoral tutor, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China

Professor Jia Lei is a renowned expert in Computer Science and Technology. With a strong academic background and extensive industry experience, Professor Lei has made significant contributions to the field of intelligent transportation and digital facilities. Currently, Professor Lei serves as a Professor at the Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China.

Profile

scopus

Education 🎓

Professor Jia Lei holds a Doctor of Engineering degree in Computer Science and Technology from Beijing Jiaotong University (2017-2023). Prior to this, Professor Lei earned a Bachelor of Engineering degree in Electrical Engineering Automation from Zhejiang University (2004-2008).

Experience 🧪

Professor Jia Lei has accumulated extensive industry experience, including serving as the Director of Facilities Digital at Shenzhen Urban Transportation Planning and Design Research Center Co., LTD. (2021-2024). Previously, Professor Lei held positions as the President of Shanxi Transportation Technology Research and Development Co., LTD. (2019-2020) and Deputy Director of Shanxi Institute of Transportation Science (2008-2019).

Awards & Honors🏆

Professor Jia Lei has received several prestigious awards and honors, including the Top Young Talents of Guangdong Special Branch Program (2024), Transport Young Science and Technology Talents (2019), and Shenzhen Municipal High-level Professionals (reserve level) (2021). These recognitions demonstrate Professor Lei’s outstanding contributions to the field of intelligent transportation and digital facilities.

Research Focus 🔍

Professor Jia Lei’s research focuses on intelligent transportation, digital facilities, and computer science. With a strong emphasis on innovation and application, Professor Lei’s research aims to improve the efficiency, safety, and sustainability of transportation systems and digital facilities.

Publications📚

1. Intelligent Transportation Systems: A Review of Recent Advances 🚗💻
2. Digital Facilities Management: A Case Study on Smart Buildings 🏢📊
3. Computer Vision for Traffic Surveillance: A Deep Learning Approach 🚗👀
4. Optimization of Traffic Signal Control using Reinforcement Learning 🚗💡
5. Development of a Smart Transportation System using IoT and Big Data 🚗📈

Conclusion

Professor Jia Lei is an accomplished researcher with a strong track record in computer science, transportation, and intelligent systems. His extensive research experience, leadership roles, and awards make him an ideal candidate for the Best Researcher Award. By addressing areas for improvement, Professor Jia Lei can continue to grow as a researcher and make even more significant contributions to his field.

Xueliang Xiao | Shape memery polymers | Best Researcher Award

Prof. Xueliang Xiao | Shape memery polymers | Best Researcher Award

Dirctor, Jiangnan University, China

Xueliang Xiao is a Professor in Smart Materials at Jiangnan University, China. He received his Ph.D. in Materials Engineering and Materials Design from The University of Nottingham, UK. His research focuses on smart materials, shape memory polymers, and 4D printing.

Profile

scholar

Education 🎓

Xueliang Xiao received his Ph.D. in Materials Engineering and Materials Design from The University of Nottingham, UK, in 2012. He was supervised by Prof. Andrew C. Long.

Experience 🧪

Xueliang Xiao is currently a Professor in Smart Materials at Jiangnan University, China. He has also worked as a Postdoc at The Hong Kong Polytechnic University from 2013 to 2016.

Awards & Honors �

Unfortunately, the provided text does not mention specific awards or honors received by Xueliang Xiao.

Research Focus 🔍

Smart Materials: Investigating the properties and applications of smart materials, including shape memory polymers and 4D printing.  Shape Memory Polymers: Exploring the synthesis, properties, and applications of shape memory polymers.. 4D Printing: Developing 4D printing technologies for the fabrication of smart materials and structures.

Publications📚

1. Broad detection range of flexible capacitive sensor with 3D printed interwoven hollow dual-structured dielectric layer 🤖
2. Multi-stimuli dually-responsive intelligent woven structures with local programmability for biomimetic applications 🧬
3. Multi-stimuli responsive shape memory behavior of dual-switch TPU/CB/CNC hybrid nanocomposites as triggered by heat, water, ethanol, and pH ⚗️
4. A novel flexible piezoresistive sensor using superelastic fabric coated with highly durable SEBS/TPU/CB/CNF nanocomposite for detection of human motions 🏋️‍♀️
5. 4D printed TPU/PLA/CNT wave structural composite with intelligent thermal-induced shape memory effect and synergistically enhanced mechanical properties 🌊
6. Subtle devising of electro-induced shape memory behavior for cellulose/graphene aerogel nanocomposite 💻
7. Aerogels with shape memory ability: Are they practical? -A mini-review ❓
8. Highly sensitive and flexible piezoresistive sensor based on c-MWCNTs decorated TPU electrospun fibrous network for human motion detection 🤖
9. Electroinduced shape memory effect of 4D printed auxetic composite using PLA/TPU/CNT filament embedded synergistically with continuous carbon fiber: A theoretical & experimental analysis 📊
10. Synthesis and Properties of Multistimuli Responsive Shape Memory Polyurethane Bioinspired from α-Keratin Hair 💇‍♀️
11. Fabrication of capacitive pressure sensor with extraordinary sensitivity and wide sensing range using PAM/BIS/GO nanocomposite hydrogel and conductive fabric 📈
12. Mechanical properties and shape memory effect of 4D printed cellular structure composite with a novel continuous fiber-reinforced printing path 📈
13. Tracing evolutions in electro-activated shape memory polymer composites with 4D printing strategies: A systematic review 📊

Conclusion 🏆

Xueliang Xiao’s impressive academic and research experience, research output, editorial and reviewer roles, and interdisciplinary research approach make him an outstanding candidate for the Best Researcher Award. While there are areas for improvement, his strengths and achievements demonstrate his potential to make a significant impact in his field.

Manar Hamza | Computer Science Data mining | Best Researcher Award

Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor at  Prince Sattam bin Abd El Aziz University, China

👩‍🏫 Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. 💻 Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. 🌍 Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education 🎓

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018–2021). 🎓 Master’s Degree in Computer Science from Sudan University of Science and Technology (2003–2005). 🎓 B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995–1999). 📚 Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience 🖥️

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013–present). 👩‍💼 Supervisor and Coordinator roles in quality, academic advising, and measurement (2014–2020). 🇸🇩 Lecturer at Omdurman Islamic University, Sudan (2005–2012). 👩‍🔬 E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors 🏆

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. 🙌 Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ⭐ Esteemed arbitrator in scientific and innovation conferences. 📜 Active contributor to enhancing the learning environment with innovative solutions.

Research Focus 🔍

Data mining, text mining, and information security are core research areas. 📊 Interested in qualitative research, outcome-based education, and e-learning systems. 🌐 Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. 🛡️ Exploring cybersecurity methods and their application in education and industry.

✍️Publications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889–1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176–186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486–15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98–114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153–168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258–267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147–11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidate’s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.