Guoqing Wang | Industrial engineering Award | Best Researcher Award

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Prof.Guoqing Wang | Industrial engineering Award | Best Researcher Award

Prof.Guoqing Wang,University of Electronic Science and Technology of China, China

Dr. Guoqing Wang is a distinguished professor at the University of Electronic Science and Technology of China (UESTC), located in Chengdu, Sichuan Province, China. He holds expertise in the field of electronic engineering, particularly in the areas of signal processing, communication systems, and wireless networks. With numerous publications and research contributions to his name, Dr. Wang is recognized for his innovative approaches to solving complex problems in telecommunications. He plays a pivotal role in advancing both academic and industrial research endeavors, fostering collaboration and driving technological advancements in China’s electronic engineering landscape.

Professional Profiles:

Scopus

Education:

Ph.D. in Computer Science and Engineering (Sep. 2017 – Jan. 2021,Advisors: Dr. Changming Sun, Prof. Arcot Sowmya,Thesis: “Unbiased Representation Learning Networks for Single Rainy Image ,M.S. in Control Engineering (Sep. 2014 – Jul. 2017)

Research Interests:

  • Machine Learning:
    • Self-/semi-/un- supervised learning and few-shot learning
    • Domain adaptation, meta-learning, and multi-task learning
    • Network interpretation and optimization

    Computer Vision:

    • Holistic image/video understanding, including classification, generation, restoration, salient object detection, semantic segmentation, depth estimation, etc.
    • Adversarial attack mitigation
    • Network compression, neural architecture search, and efficient network routing

Honors and Awards:

  • National Natural Science Fund for Excellent Young Scientists Fund Program (Overseas)
  • Dean’s Award for Outstanding PhD Theses
  • Tecent Open Fund for Excellent Young Scholar
  • ICCV Student Travel Grant
  • UNSW Postgraduate Research Student Support (PRSS) Scholarship
  • UNSW/CSIRO Postgraduate Scholarships
  • Best Master Dissertation of Jiangsu Province (2022)

 

Publications:

    • 1. Enhanced Context Encoding for Single Image Raindrop Removal
      • Authors: Guoqing Wang, Yang Yang*, Xing Xu, Jingjing Li, HengTao Shen
      • Published in: Science in China (Technological Sciences), 2021
      • [pdf]

      2. Attentive Feature Refinement Network for Single Rainy Image Restoration

      • Authors: Guoqing Wang, Changming Sun*, Arcot Sowmya
      • Published in: IEEE Transactions on Image Processing, 2020
      • [pdf]

      3. Context-enhanced Representation Learning for Single Image De-Raining

      • Authors: Guoqing Wang, Changming Sun*, Arcot Sowmya
      • Published in: International Journal of Computer Vision, 2020
      • [pdf]

      4. Cascaded Attention Guidance Network for Single Rainy Image Restoration

      • Authors: Guoqing Wang, Changming Sun*, Arcot Sowmya
      • Published in: IEEE Transactions on Image Processing, 2020
      • [pdf]

      5. Multi-Scale Deep Representation Aggregation for Vein Recognition

      • Authors: Zaiyu Pan, Jun Wang*, Guoqing Wang, Jihong Zhu
      • Published in: IEEE Transactions on Information Forensics and Security, 2020
      • [pdf]

      6. Learning a Compact Vein Discrimination Model With GAN-erated Samples

      • Authors: Guoqing Wang, Changming Sun*, Arcot Sowmya
      • Published in: IEEE Transactions on Information Forensics and Security, 2019
      • [pdf]

      7. Multi-Weighted Co-Occurrence Descriptor Encoding for Vein Recognition

      • Authors: Guoqing Wang, Changming Sun*, Arcot Sowmya
      • Published in: IEEE Transactions on Information Forensics and Security, 2019
      • [pdf]

      8. Spatial Pyramid Pooling of Selective Convolutional Features for Vein Recognition

      • Authors: Jun Wang, Zaiyu Pan*, Guoqing Wang, Ming Li, Yulian Li
      • Published in: IEEE Access, 2018
      • [pdf]

      9. Minutiae Based Weighting Aggregation of Deep Convolutional Features for Vein Recognition

      • Authors: Jun Wang, Kai Yang, Zaiyu Pan*, Guoqing Wang, Ming Li, Yulian Li
      • Published in: IEEE Access, 2018
      • [pdf]

      10. Gender Attribute Mining with Hand Dorsa Vein Image Based on Unsupervised Sparse Feature Learning

      • Authors: Jun Wang, Guoqing Wang*, Zaiyu Pan
      • Published in: IEICE Transactions on Information and Systems, 2018

Babar Shah | Aerodynamics | Best Researcher Award

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Mr. Babar Shah | Aerodynamics | Best Researcher Award

Mr. Babar Shah, International Islamic University, Pakistan

Mr. Babar Shah, currently serving as Vice-Principal at Riphah International College, is a dedicated educator and researcher based in Pakistan. With a Ph.D. in progress at the International Islamic University Islamabad, his focus lies in “Heat Transfer Analysis of Non-Similar Axisymmetric Flows.” As a lecturer at FCC & S College Fateh Jang from 2016 to 2022, he taught a range of graduate courses spanning Calculus, Analytical Geometry, Mathematical Methods, Numerical Analysis, Mechanics, and Vector Analysis. Babar Shah’s mathematical interests encompass fluid dynamics, heat and mass transfer, and computational fluid dynamics, showcasing a diverse academic portfolio. He has earned accolades, including a Ph.D. Reimburse Scholarship and participation in the International Research Support Initiative Program (IRSIP) at Monash University, Australia. 🏆🌐

🎓 Academic Pursuits:

Ph.D. candidate at the International Islamic University Islamabad, with a research focus on “Heat Transfer Analysis of Non-Similar Axisymmetric Flows” under the guidance of Associate Prof. Dr. Ahmer Mehmood. M.Phil. degree (2015-2017) explored “Boundary Layer Flow due to Uniform Stretching of a Circular Cylinder” with a CGPA of 3.25/4. M.Sc. in Laplace Transform from Preston University, Islamabad, in 2014 with a CGPA of 3.8/4. B.Ed. from Preston University, Islamabad, in 2017.

🧮 Mathematical Interests:

Babar Shah’s mathematical interests span Ordinary/Partial Differential Equations, Continuous Moving Surfaces, Newtonian/Non-Newtonian fluids, Turbulent Boundary Layer Flows, Convective Heat, and Mass Transfer, Porous Media, MHD Fluid Flow, and Computational Fluid Dynamics.

🏆 Awards and Fellowships:

Ph.D. Reimburse Scholarship. International Research Support Initiative Program (IRSIP) for Monash University, Australia.

Professional Profiles:

Research Focus 🚀:

Mr. Babar Shah, associated with the International Islamic University in Pakistan, excels in theoretical and computational analyses of fluid dynamics with a focus on convective transport, radiation effects, and heat transfer phenomena. His research delves into the intricacies of laminar flows over bodies of revolution, exploring the combined impacts of surface sharpness and transverse curvature on thermal transport. Babar Shah’s expertise extends to computational analysis, evident in studies on flow separation in mixed convection MHD flows and analyzing the effects of TVC (thrust vector control) on seizing flow around a moving continuous cylinder. His contributions significantly advance our understanding of fluid behavior in complex scenarios. 📈🔍

🎓 Publications Top Note:

 

Enrique Del Castillo | Industrial Engineering | Best Researcher Award

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Prof. Enrique Del Castillo | Industrial Engineering | Best Researcher Award

Prof. Enrique Del Castillo, Pennsylvania State University, United States

Dr. Enrique del Castillo, a Distinguished Professor in the Industrial and Manufacturing Engineering Department at Penn State, boasts a remarkable career at the intersection of statistics and industrial engineering. His research, backed by over $2.3 million in funding from entities like NSF, General Motors R&D, and Netflix, spans process optimization, statistical process control, time series analysis, Bayesian Statistics, and machine learning.

👨‍🏫 Academic Leadership:

Director of the Engineering Statistics and Machine Learning Laboratory. Member of the Operations Research Program Committee at PSU. Affiliated member of the Institute for Computational and Data Sciences. Faculty in the Computational Science Graduate minor at PSU.

📚 Academic Appointments:

Distinguished Professor of Industrial Engineering at Penn State. Professor of Statistics (joint appointment) at the Eberly School of Science, PSU.

🌍 International Engagements:

Member of the Scientific Advisory Committee at the Institute for Data Science and Computer Aided Design In Mechanical Engineering, University of Navarra, Spain. Advisory board member at the Department of Industrial Engineering, Mexican Institute of Technology (ITAM), Mexico City. Fulbright Scholar and Visiting Researcher at the University of Coimbra, Portugal (2019).

🏆 Awards and Honors:

Youden Award for the best paper in the Technometrics journal (2022). Fellow of the Royal Statistical Society (2019). NSF CAREER Award recipient. Distinguished Professor of Engineering at Penn State.

📖 Textbooks:

“Process Optimization with Multiple Response Variables, a Predictive Distribution Approach with R and Stan” (2023) – In preparation. “Process Optimization: A Statistical Approach” (2007). “Statistical Process Adjustment for Quality Control” (2002).

📚 Editorship:

Co-editor of “Bayesian Process Monitoring, Control, and Optimization” (2006). Co-editor of “Run to Run Process Control for Semiconductor Manufacturing” (2000).

Professional Profiles:

The impact of her research is evident in citation metrics and indices from Google Scholar:

  • Cited by: All – 7317.
  • Citations – 7317.
  • h-index – 43.
  • Documents – 238.

A prolific researcher making meaningful contributions to the academic world!

Research Focus 🚀:

Prof. Enrique Del Castillo, based at Pennsylvania State University, stands as a trailblazer in statistical methodology for industrial engineering. His prolific research, evidenced by over 500 citations in numerous pivotal works, spans diverse areas. Notably, his focus on “Modified Desirability Functions for Multiple Response Optimization” and “Process Optimization: A Statistical Approach” reflects his significant contributions to optimization methodologies. From addressing dual response problems to seminal works in semiconductor manufacturing control, Prof. Del Castillo’s expertise traverses nonlinear programming, distribution fitting, and adaptive control systems. His enduring impact extends to pioneering literature reviews and e-Handbooks, shaping statistical methods in academia and industry. 🌐🏆

🎓 Publications Top Note: