Jingting Liu | Engineering | Best Researcher Award

Assoc. Prof. Dr. Jingting Liu | Engineering | Best Researcher Award

Shandong University | China

Dr. Jingting Liu is an Associate Professor in the Process Equipment and Control Engineering Department at Shandong University. She holds a Ph.D. in Chemical Process Machinery from Zhejiang University and a B.S. in Process Equipment and Control Engineering from China University of Petroleum. Her work focuses on fluid dynamics, vibration, and acoustics, with a particular interest in bubble dynamics.

Professional profile👤

Scopus

Strengths for the Awards✨

  • Research Excellence: Jingting Liu has led multiple research projects, notably funded by prestigious institutions like the National Natural Science Foundation of China and various provincial foundations, highlighting her capacity to secure competitive funding.

  • Publication Record: She has published extensively in high-impact journals, including the Chemical Engineering Journal and Physics of Fluids, showcasing the significance and quality of her research.

  • Innovative Contributions: Her focus on bubble dynamics and acoustics has practical applications in fluid machinery and noise reduction, demonstrating innovation and relevance to real-world challenges.

  • Interdisciplinary Impact: Her work integrates fluid dynamics, vibration, and acoustics, broadening the impact across multiple fields.

  • Leadership and Mentorship: As an associate professor, she not only contributes to research but also teaches and mentors students, nurturing the next generation of researchers.

  • Editorial Roles: Serving as a guest editor reflects her recognition and trust within the scientific community.

Education 🎓

  • Ph.D. in Chemical Process Machinery, Zhejiang University
  • B.S. in Process Equipment and Control Engineering, China University of Petroleum

Experience đź’Ľ

Jingting Liu has been serving as an Associate Professor at Shandong University, where she teaches courses in fluid mechanics and fluid machinery. She has led multiple research projects, delving into underwater bubble dynamics and acoustic phenomena. Her contributions extend to both academia and industry, where she provides solutions to reduce noise in fluid machinery.

Research Interests On Engineering🔬

Her primary research interests include fluid machinery, vibration and acoustics, bubble dynamics, and bubble acoustics. She explores the intricate mechanisms behind bubble formation and acoustic emissions, aiming to improve fluid machinery performance and noise reduction.

Awards 🏆

  • Best Researcher Award (Nomination)

Publications đź“–

  • Title: Dynamics of bubbles detached from non-circular orifices: Confinement effect of orifice boundary
    Authors: Jingting Liu*, Haoyang Qi, Yongxing Song, Songying Chen, Dazhuan Wu
    Year: 2024

  • Title: Experimental study on asymmetric bubbles rising in water: Morphology and acoustic signature
    Authors: Jingting Liu*, Shanhao Cong, Yongxing Song, Dazhuan Wu, Songying Chen
    Year: 2022

  • Title: Flow structure and acoustics of underwater imperfectly expanded supersonic gas jets
    Authors: Jingting Liu*, Shanhao Cong, Yongxing Song, Songying Chen, Dazhuan Wu
    Year: 2022

  • Title: Numerical simulations and experimental validation on passive acoustic emissions during bubble formation
    Authors: Jingting Liu, Wu Wang, Ning Chu, Dazhuan Wu, Weiwei Xu
    Year: 2018
    Citations: DOI: 10.1016/j.apacoust.2017.09.005

  • Title: Numerical simulations of bubble formation and acoustic characteristics from a submerged orifice: The effects of nozzle wall configurations
    Authors: Jingting Liu, Ning Chu, Shijie Qin, Dazhuan Wu
    Year: 2017
    Citations: DOI: 10.1016/j.cherd.2017.05.002

  • Title: Acoustic analysis on jet-bubble formation based on 3D numerical simulations
    Authors: Liu Jingting, Chu Ning, Qin Shijie, Wu Dazhuan
    Year: 2016
    Citations: INTER-NOISE 2016 – 45th International Congress and Exposition on Noise Control Engineering

  • Title: Acoustic emission measurement of submerged jet-bubble: Laboratory and computational fluid dynamics (CFD)
    Authors: Liu Jingting, Qin Shijie, Ning Chu, Wu Dazhuan
    Year: 2016

  • Title: Three-dimensional numerical simulation of air exhausted from submerged nozzles
    Authors: Liu Jingting, Qin Shijie, Miao Tiancheng, et al.
    Year: 2015

Conclusion 🔝

Jingting Liu has significantly contributed to understanding fluid dynamics and acoustics, with a special focus on bubble dynamics and noise reduction in fluid machinery. Her research not only advances academic knowledge but also provides practical solutions for industrial applications. She continues to inspire the next generation of engineers through her teaching and groundbreaking research.

Suganya | Engineering | Best Researcher Award

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)

đź’Ľ 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.