Pengyue Li | Technology Transforming | Best Researcher Award

Ms. Pengyue Li | Technology Transforming | Best Researcher Award

Student of Zhengzhou University, China

Summary:

Ms. Pengyue Li, born on September 20, 1997, is a dedicated researcher from China currently pursuing her Master’s degree at Zhengzhou University, expected to complete in June 2024. She earned her Bachelor’s degree from East China University of Technology in 2020. Ms. Li has distinguished herself academically with university-level scholarships and has actively contributed to research through published papers in both Chinese and international journals. Her research expertise spans Python programming, text mining, and semantic analysis. She is proficient in using advanced algorithms and tools such as k-means, UMAP, and SVM, and has experience with system dynamics simulation models. Ms. Li’s work reflects a strong foundation in both theoretical and practical aspects of her field, highlighting her potential as an emerging researcher.

 

Profile:

Education:

Ms. Pengyue Li has a solid educational foundation in her field. She completed her Bachelor’s degree at East China University of Technology from September 2016 to June 2020. Currently, she is pursuing a Master’s degree at Zhengzhou University, which she commenced in September 2021 and is expected to complete in June 2024. Her academic journey reflects a continuous commitment to advancing her knowledge and skills in her area of study.

Professional Experience:

Ms. Pengyue Li has been actively engaged in research and academic projects throughout her academic career. She has contributed to various scientific research projects at the provincial and school levels, showcasing her involvement in practical research applications. Her work includes participation in writing and implementing research projects, reflecting her commitment to advancing knowledge in her field. Additionally, Ms. Li has authored and co-authored several academic papers, including a notable publication in the journal Heliyon on intelligent manufacturing technology and sustainability. Her experience also includes proficiency in Python programming and text mining techniques, further underscoring her technical and analytical skills.

Research Interests:

Ms. Pengyue Li’s research interests lie at the intersection of data analysis, industrial production, and text mining. She is particularly focused on utilizing Python and various analytical tools to explore and solve complex problems. Her expertise includes the use of algorithms such as k-means, UMAP, KNN, and SVM for data clustering and classification, as well as web scraping for data collection. Ms. Li is proficient in semantic analysis and text mining techniques, including word frequency statistics, TF-IDF, topic modeling, and sentiment analysis, which she applies to patent and trademark text data. Additionally, she has a keen interest in industrial production processes, encompassing production planning, control, and system engineering. Ms. Li also employs system dynamics simulation models to address related industrial challenges. Her research endeavors aim to leverage advanced data analytics and simulation techniques to enhance efficiency and innovation in industrial production and text mining applications.

Certificates:

  • ETS TOEIC: 740
  • CET-6: 508
  • CET-4: 528

These certificates show her proficiency in English, which is valuable for international research collaboration and publication.

Awards:

Ms. Li has received university-level scholarships from both East China University of Technology and Zhengzhou University, highlighting her academic excellence.

Conclusion:

Ms. Pengyue Li has shown notable achievements for her career stage, including academic publications, active participation in research projects, and proficiency in relevant technical skills. However, for the Research for Best Researcher Award, which typically honors individuals with extensive and impactful research contributions over a longer period, Ms. Li might not yet be the strongest candidate compared to more experienced researchers. Her current accomplishments are promising, and with continued research output and professional development, she could become a more competitive candidate for such awards in the future.

Publication Tob Noted:

Title: Toward Industry 5.0: Challenges and Enablers of Intelligent Manufacturing Technology Implementation under the Perspective of Sustainability

Authors:

  • Liu, S.
  • Li, P.
  • Wang, J.
  • Liu, P.

Journal: Heliyon, 2024

Volume and Issue: 10(15)

Article ID: e35162

Amber Hayat | Biometrics Security | Women Researcher Award

Mrs. Amber Hayat | Biometrics Security | Women Researcher Award

PhD student of IIT Delhi, India

Mrs. Amber Hayat appears to be a strong candidate for the Research for Women Researcher Award based on her extensive contributions and achievements in the fields of biometrics, security, machine learning, deep learning, and the Internet of Things (IoT). Here are some key points that highlight her suitability:

Profile:

Research Contributions

Diverse Research Topics:

Amber’s work encompasses a variety of topics within the realm of information technology, specifically focusing on biometrics and security. Her research on template protection in biometrics is particularly noteworthy and relevant to current security challenges.

Awards and Fellowships:

She has received several accolades, such as the IEEE Travel Grant and the TEQIP II Fellowship for her M.Tech studies, demonstrating recognition from the academic community for her work and potential.

Professional Experience

Academic Positions:

Amber has held multiple academic positions, including as an Assistant Professor at various institutions. Her experience at the University of Petroleum & Energy Studies (UPES) and her roles in curriculum development, project mentorship, and organizing academic events showcase her dedication to teaching and research.

Project Involvement:

She has led and participated in several impactful projects, such as fingerprint template protection, online signature template protection, and real-time monitoring of water bodies using IoT. These projects reflect her ability to apply research to practical and socially relevant problems.

Teaching and Mentorship

Teaching Assistantships:

Amber has served as a teaching assistant at IIT Delhi, contributing to courses on biometrics security, cryptography, algorithms, and data structures, indicating her engagement in educating the next generation of researchers and engineers.

Mentorship:

Her mentorship roles, including guiding undergraduate projects and leading teams in hackathons, highlight her commitment to nurturing young talent and fostering innovation.

Additional Contributions

Organizing Committees and Talks:

Amber has been actively involved in organizing conferences and workshops, such as the IEEE International Conference on Next Generation Computing Technologies. She has also delivered expert talks on topics like IoT and fog computing, further establishing her as a knowledgeable and influential figure in her field.

Memberships and Community Involvement:

As an IEEE and ACM member, she stays connected with the broader research community, contributing to the advancement of her fields of interest.

Conclusion

Mrs. Amber Hayat’s extensive research contributions, professional experience, teaching and mentorship roles, and active involvement in academic and professional communities make her a highly suitable candidate for the Research for Women Researcher Award. Her work not only advances scientific knowledge but also addresses real-world problems, benefiting both academia and society.

Publication Tob Noted:

Intelligent System for Skin Disease Prediction Using Machine Learning

  • Authors: AA Elngar, R Kumar, A Hayat, P Churi
  • Journal: Journal of Physics: Conference Series
  • Volume: 1998, Issue: 1
  • Article: 012037
  • Year: 2021
  • Citations: 29

Green-IoT (G-IoT) Architectures and Their Applications in the Smart City

  • Authors: M Goel, A Hayat, A Husain, S Dalal
  • Book Chapter: Green Internet of Things for Smart Cities
  • Pages: 47-59
  • Year: 2021
  • Citations: 17

FinTem: A Secure and Non-invertible Technique for Fingerprint Template Protection

  • Authors: A Hayat, SS Ali, AK Bhateja, N Werghi
  • Journal: Computers & Security
  • Volume: 142
  • Article: 103876