Jinxia Zhang | Defect detection | Best Researcher Award

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

 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 🎓

Assoc Prof Dr. Jinxia Zhang  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 Zhang  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 Honors  🏆

Assoc Prof Dr. Jinxia Zhang  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 Focus  🔬

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.

Publication  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.

Dr. Masih Paknejad | precision machining Award | Best Researcher Award

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Dr. Masih Paknejad | precision machining Award | Best Researcher Award

Dr. Masih Paknejad, KSF (Kompetenzzentrum für Spanende Fertigung), Germany

Dr. Masih Paknejad is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles:

Orcid

Google scholar

Work Experience 🛠️

Institute of Advanced Machining (KSF), GermanyTeam Leader, Postdoctoral Research Fellow2023 – PresentMachine Tools Committee ISO/ISIRI TC 39, IranSenior Member, Chief and Technical Editor of Machine Tools Standards2022 – PresentTurbine Engineering and Manufacturing Co. (TUGA), IranExpert Engineer (R&D Department)2019 – 2021Persian Ultrasonic Co., IranCEO, Design and Manufacture of High Power Ultrasonic Transducer2019 – PresentHitec-Machinery Trading Co., IranTechnical Advisor, Supervisor of Test and Calibration of Machine Tools2017 – 2019Semnan University, IranLecturer2018 – 2019Courses: Materials Science and Engineering, Metrology Lab., Machine Tools Workshop, Engineering Drawing, Hydraulics and Hydraulics Lab, Welding WorkshopAmirkabir University of Technology, IranStrength of Material Lab Expert, Metrology Lab Expert, Teacher Assistant2012 – 2018Courses: Nontraditional Manufacturing Processes, Machine Element DesignIslamic Azad University (Saveh Branch), IranLecturer2011 – 2012Courses: Metrology, Production Methods, Nontraditional Manufacturing Processes

Education 🎓

Furtwangen University – KSF Institute
Feb 2022 – Sep 2023Postdoc FellowTitle: Ultras-Short Pulse Laser-Assisted Micro-Grinding of Silicon CeramicsAmirkabir University of TechnologySep 2011 – Nov 2017
Ph.D.Dissertation: Theoretical-Experimental Model of Heat Generation in Ultrasonic Assisted Dry Creep Feed Grinding ProcessFurtwangen University – KSF Institute
Jun 2014– Jan 2015Sabbatical ResearcherAmirkabir University of TechnologySep 2008 – Jul 2011M.Sc.Thesis: Theoretical and Experimental Analysis of Ultrasonic Assisted Indentation Forming of TubeIsfahan University of TechnologySep 2004– Sep 2008B.Sc.Thesis: Design of Centrifugal Chip Lubricant Separator DeviceAwards & Honors 🏆Scholarship Award granted by the Ministry of Science Research and Technology of IranAward of the Alborz Regional Innovation and Flourishing Festival, National Elites FoundationPatent for “Design and Manufacture of Ultrasonic Assisted Indentation Forming Device”Award of Elite Entrance, National Organization for Educational Testing (NOET)Ranked 3rd among 39 Undergraduate Students, Mechanical Engineering Department, Isfahan University of TechnologyComputer Skills 💻Mechanical Eng. Software: ABAQUS, ANSYS, CATIA, MasterCAM, MSC Visual

Nastran, Automation StudioProgramming Language: MATLABSoftware Packages: Microsoft Office, Windows

Awards & Honors 🏆

Scholarship Award granted by the Ministry of Science Research and Technology of IranAward of the Alborz Regional Innovation and Flourishing Festival, National Elites FoundationPatent for “Design and Manufacture of Ultrasonic Assisted Indentation Forming Device”Award of Elite Entrance, National Organization for Educational Testing (NOET)Ranked 3rd among 39 Undergraduate Students, Mechanical Engineering Department, Isfahan University of Technology

Computer Skills 💻

Mechanical Eng. Software: ABAQUS, ANSYS, CATIA, MasterCAM, MSC Visual Nastran, Automation StudioProgramming Language: MATLABSoftware Packages: Microsoft Office, Windows

📊 Citation Metrics (Google Scholar):

Citations by: All – 87, Since 2019 – 70
h-index: All – 3, Since 2018 – 3
i10 index: All – 3, Since 2018 –3

 

📖 Publications  Top Note :

Investigation of laser-assisted cylindrical grinding of silicon nitride ceramics with controlled damage zone

Journal: Optics & Laser Technology

Date: July 2024

DOI: 10.1016/j.optlastec.2024.110616

Contributors: Esmaeil Ghadiri Zahrani; Masih Paknejad; Ali Zahedi; Bahman Azarhoushang

Laser-assisted surface grinding of innovative superhard SiC-bonded diamond (DSiC) materials

Journal: Ceramics International

Date: February 2024

DOI: 10.1016/j.ceramint.2024.02.323

Contributors: Masih Paknejad; Bahman Azarhoushang; Ali Zahedi; Mehdi Khakrangin; Robert Bösinger; Faramarz Hojati

Investigation of material removal mechanisms of laser-structured Si3N4 via single diamond grit scratching

Journal: The International Journal of Advanced Manufacturing Technology

Date: March 2023

DOI: 10.1007/s00170-022-10793-0

Contributors: Masih Paknejad; Bahman Azarhoushang; Ali Zahedi; Mehdi Khakrangin; Mohammad Ali Kadivar

Investigation of material removal mechanisms of laser-structured Si3N4 via single diamond grit scratching

Date: September 2, 2022

DOI: 10.21203/rs.3.rs-1974605/v1

Contributors: Masih Paknejad; Bahman Azarhoushang; Ali Zahedi; Mehdi Khakrangin; Mohammad Ali Kadivar

Ductile-brittle transition mechanisms in micro-grinding of silicon nitride

Journal: Ceramics International

Date: August 2022

DOI: 10.1016/j.ceramint.2022.08.088

Contributors: Masih Paknejad

Numerical Simulation of Ultrasonic Assisted Indentation Tube Forming

Journal: ADMT Journal

Date: September 2020

DOI: 10.30495/admt.2020.1869462.1124

Contributors: Masih Paknejad

Effects of high power ultrasonic vibration on temperature distribution of workpiece in dry creep feed up grinding

Journal: Ultrasonics Sonochemistry

Date: November 2017

DOI: 10.1016/j.ultsonch.2017.04.029

Contributors: Masih Paknejad

Theoretical and experimental analyses of ultrasonic-assisted indentation forming of tube

Journal: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Date: March 2014

DOI: 10.1177/0954405413501502

Contributors: Masih Paknejad