Jinxia Zhang | Defect detection | Best Researcher Award

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Assoc Prof Dr. Jinxia Zhang | Defect detection | Best Researcher Award

Ā Associate Professor at Southeast University, China

Assoc Prof Dr. Jinxia Zhang is an Associate Professor at Southeast University, Nanjing, China, specializing in saliency detection, visual attention, computer vision, and deep learning. With a Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology, he has extensive experience in artificial intelligence research. His journey includes time as a visiting scholar at Harvard Medical School and numerous prestigious research projects funded by national foundations. Assoc Prof Dr. Jinxia Zhang leads key AI initiatives, driving innovations in multimodal understanding, defect analysis, and object detection. His academic and professional contributions have positioned him as a prominent researcher in visual computing and AI.

Publication Profile

scholar

Education šŸŽ“

Assoc Prof Dr. Jinxia ZhangĀ  earned his M.Sc. and Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology in 2015. His doctoral research laid a foundation for his interest in artificial intelligence, particularly in areas like visual attention and computer vision. Prior to his postgraduate work, he completed his B.Sc. in Computer Science and Technology at the same institution in 2009, where he developed a solid understanding of computational theories and applications. His education has provided him with both theoretical knowledge and practical skills that are central to his current research on AI and deep learning.Assoc Prof Dr. Jinxia ZhangĀ  is currently an Associate Professor at Southeast University, Nanjing, a role he has held since 2019. From 2016 to 2019, he served as a Lecturer at the same university, where he significantly contributed to AI teaching and research. His early career included a prestigious stint as a Visiting Scholar at Harvard Medical School, USA, between 2012 and 2014, where he collaborated on cutting-edge AI-driven healthcare projects. His international exposure and academic roles have enriched his teaching and research, particularly in computer vision and AI, making him a key figure in the field.

Awards and HonorsĀ  šŸ†

Assoc Prof Dr. Jinxia ZhangĀ  has received numerous accolades for his research excellence and contributions to the field of AI. He was awarded the National Natural Science Foundation of China grant in 2018 for his project on salient object detection. In 2017, he secured the Jiangsu Natural Science Foundation Grant for his innovative research on visual cognitive characteristics. Additionally, his work in defect diagnosis for photovoltaic modules was recognized as part of the National Key Research and Development Plan. These prestigious awards underscore his pioneering contributions in artificial intelligence and computer vision research.

Research FocusĀ  šŸ”¬

Assoc Prof Dr. Jinxia Zhang ‘s research focuses on the intersection of visual attention, saliency detection, and deep learning within artificial intelligence. He leads projects on multimodal understanding and e-commerce applications, and is a Principal Investigator for research into AI-based fruit and vegetable recognition. His earlier work in defect diagnosis for photovoltaic modules and salient object detection in complex scenes has been supported by prominent grants. His innovative approach combines perceptual grouping and visual attention to develop cutting-edge solutions in computer vision, making significant advancements in how machines perceive and interact with visual data.

Conclusion

The candidate demonstrates an impressive body of work across several domains of artificial intelligence, particularly in salient object detection, visual cognition, and multimodal learning. Their academic achievements, project leadership, and dedication to advancing AI make them a strong contender for the Best Researcher Award. By continuing to broaden their industry collaborations and expanding the scope of their research impact, they can become a globally recognized leader in AI and computer vision.

PublicationĀ  Top Notes

  • Towards the Quantitative Evaluation of Visual Attention Models (2015)
    • Citation: 75
    • Journal: Vision Research
    • Key Contributors: Z. Bylinskii, E.M. DeGennaro, R. Rajalingham, H. Ruda, J. Zhang, J.K. Tsotsos
    • Highlights: Focuses on quantitative approaches to evaluate visual attention models, essential for improving saliency detection.
  • A Novel Graph-Based Optimization Framework for Salient Object Detection (2017)
    • Citation: 63
    • Journal: Pattern Recognition
    • Key Contributors: J. Zhang, K.A. Ehinger, H. Wei, K. Zhang, J. Yang
    • Highlights: Presents a new graph-based optimization method for enhancing the accuracy of salient object detection.
  • Salient Object Detection by Fusing Local and Global Contexts (2020)
    • Citation: 60
    • Journal: IEEE Transactions on Multimedia
    • Key Contributors: Q. Ren, S. Lu, J. Zhang, R. Hu
    • Highlights: This paper integrates both local and global visual contexts to refine salient object detection in multimedia applications.
  • Inter-Hour Direct Normal Irradiance Forecast with Multiple Data Types and Time-Series (2019)
    • Citation: 36
    • Journal: Journal of Modern Power Systems and Clean Energy
    • Key Contributors: T. Zhu, H. Zhou, H. Wei, X. Zhao, K. Zhang, J. Zhang
    • Highlights: Introduces a time-series forecasting model for direct normal irradiance, benefiting renewable energy systems.
  • Winter is Coming: How Humans Forage in a Temporally Structured Environment (2015)
    • Citation: 35
    • Journal: Journal of Vision
    • Key Contributors: D. Fougnie, S.M. Cormiea, J. Zhang, G.A. Alvarez, J.M. Wolfe
    • Highlights: Examines human visual foraging behavior in dynamically changing environments.
  • Domain Adaptation for Epileptic EEG Classification Using Adversarial Learning and Riemannian Manifold (2022)
    • Citation: 25
    • Journal: Biomedical Signal Processing and Control
    • Key Contributors: P. Peng, L. Xie, K. Zhang, J. Zhang, L. Yang, H. Wei
    • Highlights: This paper explores domain adaptation techniques to improve epileptic EEG classification through adversarial learning.
  • A Lightweight Network for Photovoltaic Cell Defect Detection in Electroluminescence Images (2024)
    • Citation: 23
    • Journal: Applied Energy
    • Key Contributors: J. Zhang, X. Chen, H. Wei, K. Zhang
    • Highlights: Develops a lightweight neural network for detecting defects in photovoltaic cells using knowledge distillation.
  • Salient Object Detection via Deformed Smoothness Constraint (2018)
    • Citation: 21
    • Journal: IEEE International Conference on Image Processing (ICIP)
    • Key Contributors: X. Wu, X. Ma, J. Zhang, A. Wang, Z. Jin
    • Highlights: Proposes a deformed smoothness constraint approach for improving salient object detection.
  • Character Recognition via a Compact Convolutional Neural Network (2017)
    • Citation: 20
    • Conference: International Conference on Digital Image Computing
    • Key Contributors: H. Zhao, Y. Hu, J. Zhang
    • Highlights: Develops a compact CNN for robust character recognition in natural scene images.
  • A Prior-Based Graph for Salient Object Detection (2014)
    • Citation: 23
    • Conference: IEEE International Conference on Image Processing (ICIP)
    • Key Contributors: J. Zhang, K.A. Ehinger, J. Ding, J. Yang
    • Highlights: Uses a prior-based graph model to enhance the performance of salient object detection algorithms.

Bernd Bachert | Korrosionsschutz | Best Researcher Award

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Dr.Ā  DHBW Mosbach, Germany

With a robust academic background in Mechanical Engineering, including a Doctorate from Darmstadt University of Technology, this individual has amassed extensive experience in academia and industry. They have served as a professor, dean, and director across various institutions, playing a pivotal role in developing and accrediting numerous engineering study programs. Their expertise extends to fluid mechanics, thermodynamics, and materials science. They also lead research in mechanical engineering and renewable energy, contributing significantly to education and innovation. As CEO of IRATEC GmbH, they combine academic rigor with practical industry insights, making them a highly accomplished professional in their field.

Professional Profiles:

Scopus

Education šŸŽ“

February 1982 – June 1987: Secondary School NeckargemĆ¼nd Qualification: GCSE August 1987 – February 1991: Training at Eltro GmbH, Heidelberg
Qualification: Precision Mechanic August 1991 – June 1992: Johannes-Gutenberg-Schule, Heidelberg Qualification: Technical Diploma (Fachhochschulreife) September 1992 – January 1997: University of Applied Sciences Mannheim, Faculty of Mechanical Engineering Qualification: Graduate Engineer in Mechanical Engineering (FH) October 1997 – April 2000: Darmstadt University of Technology, Faculty of Mechanical Engineering Qualification: Graduate Engineer in Mechanical Engineering June 2000 – December 2003: Doctoral Thesis at Darmstadt University of Technology, Faculty of Mechanical Engineering Qualification: Doctor of Mechanical Engineering (Dr.-Ing.)

Work Experience šŸ’¼

February 1991 – August 1991: Wolfgang Bortz Zerspanungstechnik GmbH Function: Programming of CNC Machines January 1997 – June 1999: Assistant Professor at BFZ NĆ¼rnberg January 1997 – December 1997: KDK Kalibrierdienst Kopp GmbH (Calibration Service) Function: Handling of problems in quality assurance and quality management October 1997 – April 2000: Assistant Professor at Abendakademie Mannheim and DaimlerChrysler Training Center Mannheim Lecture: Fluid Mechanics

Evaluation of the Candidate for the Best Researcher Award

Strengths:

  1. Extensive Academic Background:
    • The candidate has a solid educational foundation in mechanical engineering, with qualifications ranging from a Technical Diploma to a Doctorate in Mechanical Engineering (Dr.-Ing.). This extensive academic background supports their credibility and expertise in the field.
  2. Diverse Work Experience:
    • The candidate has a wealth of experience across various roles, including positions as an assistant professor, director, professor, and head of departments. Their roles have spanned multiple institutions and responsibilities, indicating a strong capacity for leadership and innovation in both academia and industry.
  3. Leadership and Management Skills:
    • The candidate has held significant leadership positions, such as Director of the Heidelberg Institute for Applied Research and Development, Professor and Dean at SRH University, and Head of Mechanical Engineering at DHBW Mosbach. These roles highlight their ability to lead and manage academic and research initiatives effectively.
  4. Contributions to Education:
    • The candidate has been instrumental in developing and accrediting various study programs, including Bachelor’s and Master’s degrees in Mechanical Engineering and Industrial Engineering. Their work in creating didactical training and education programs for national and international partners showcases their dedication to advancing education in engineering.
  5. Research Contributions:
    • The candidate has engaged in several research projects in areas such as Mechanical Engineering, Water Power Engineering, and Dual Education. Their authorship of various scientific publications further underscores their contributions to research and knowledge dissemination.
  6. International Experience and Collaboration:
    • As the Head of the International Office at DHBW Mosbach, the candidate has demonstrated a commitment to fostering international collaborations and expanding the global reach of their institution.
  7. Industry Engagement:
    • The candidate’s part-time role as CEO of IRATEC GmbH, coupled with their experience in consulting and renewable energy engineering, illustrates a strong connection between their academic work and practical, real-world applications.

Areas for Improvement:

  1. Focused Research Output:
    • While the candidate has a broad range of experience, a more focused research output in a specific area of mechanical engineering might strengthen their candidacy for a Best Researcher Award. Concentrating on one niche could lead to more impactful publications and a stronger reputation in that domain.
  2. Innovation and Patents:
    • The candidate’s profile could be further enhanced by showcasing any patents or innovative technologies they may have developed. Highlighting these achievements would emphasize their contributions to the advancement of mechanical engineering.
  3. Recent Research Activity:
    • Emphasizing more recent and cutting-edge research activities would demonstrate continued relevance and engagement with current trends in mechanical engineering. If recent high-impact publications or projects are not prominent, focusing on these could be beneficial.

 

āœļøPublications Top Note :

Time-dependent measurements of cavitation damage
Authors: Osterman, A., Bachert, B., Sirok, B., Dular, M.
Journal: Wear, 2009, 266(9-10), pp. 945ā€“951
Citations: 29

Comparison of different methods for the evaluation of cavitation damaged surfaces
Authors: Bachert, B., Ludwig, G., Stoffel, B., Baumgarten, S.
Conference: Proceedings of the American Society of Mechanical Engineers Fluids Engineering Division Summer Conference, 2005, 2, pp. 553ā€“560, FEDSM2005-77368
Citations: 1

Comparison of different methods for the evaluation of cavitation damaged surfaces
Authors: Bachert, B., Stoffel, B., Ludwig, G., Baumgarten, S.
Conference: Proceedings of 2005 ASME Fluids Engineering Division Summer Meeting, FEDSM2005, 2005, pp. 2111ā€“2118
Citations: 7

Relationship between cavitation structures and cavitation damage
Authors: Dular, M., Bachert, B., Stoffel, B., Å irok, B.
Journal: Wear, 2004, 257(11), pp. 1176ā€“1184
Citations: 249

Experimental investigations concerning erosive aggressiveness of cavitation at different test configurations
Authors: Bachert, B., Dular, M., Baumgarten, S., Ludwig, G., Stoffel, B.
Conference: Proceedings of the ASME Heat Transfer/Fluids Engineering Summer Conference 2004, HT/FED 2004, 3, pp. 733ā€“743, HT-FED04-56597
Citations: 5

Experimental investigations concerning influences on cavitation inception at an axial test pump
Authors: Bachert, B., Brunn, B., Stoffel, B.
Conference: Proceedings of the ASME/JSME Joint Fluids Engineering Conference, 2003, 2 A, pp. 249ā€“256
Citations: 5

The influence of cavitation structures on the erosion of a symmetrical hydrofoil in a cavitation tunnel
Authors: Å irok, B., Dular, M., Novak, M., Ludwig, G., Bachert, B.
Journal: Strojniski Vestnik/Journal of Mechanical Engineering, 2002, 48(7), pp. 368ā€“378
Citations: 13

Conclusion:

The candidate is a strong contender for the Best Researcher Award due to their extensive academic qualifications, leadership experience, and contributions to education and research. Their background in mechanical engineering is complemented by significant roles in academia and industry, making them a well-rounded and influential figure in the field. To enhance their candidacy, they could focus on a more specialized area of research, highlight any innovative contributions, and ensure their recent research activities are at the forefront of their application.