Fatima Akram | Industrial | Best Researcher Award

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Assist Prof Dr . Fatima Akram | Industrial | Best Researcher Award

Assist Prof Dr. Fatima Akram ,Saint Louis University, MO, USA, United States

Dr. Fatima Akram is an Assistant Professor at Saint Louis University in Missouri, USA. She is recognized for her contributions to her field through both research and teaching. Dr. Akram’s work focuses on advancing knowledge and practices within her discipline, and she is actively involved in various academic and professional communities. Her dedication to education and research has made her a respected figure at Saint Louis University and beyond.

Summary:

Dr. Fatima Akram is a highly accomplished researcher with a strong background in biotechnology, specifically in the area of biofuel production. Her academic achievements, extensive research experience, and numerous awards highlight her as a significant contributor to her field. Her work on thermostable enzymes and biofuel from plant biomass has not only garnered recognition but also has practical applications in the renewable energy sector. Her current post-doctoral fellowship in the United States further emphasizes her commitment to advancing her research skills and collaborating internationally.

Professional Profiles:

🎓 Education :

Dr. Fatima Akram has an extensive academic background in the fields of biotechnology and botany. She completed her Ph.D. in Biotechnology from GC University Lahore, where her research focused on “Gene Cloning, Characterization, and Thermodynamic Studies of Highly Thermostable Cellulolytic Enzymes from Genus Thermotoga.” Her M.Phil., also from GC University Lahore, concentrated on “Cloning, Expression, and Characterization of Thermostable Cellulolytic Gene (β-glucosidase) from Hyperthermophilic Bacterium (Thermotoga petrophila).” Prior to these, Dr. Akram earned her M.Sc. in Botany from the University of the Punjab, Lahore, and her B.Sc. in Botany, Zoology, and Chemistry from Queen Mary College, Lahore. Her foundational education was completed at Queen Mary College, where she pursued F.Sc. in Pre-Medical.

🏢 Experience:

Dr. Akram’s professional journey is marked by a progression from research roles to academic positions of increasing responsibility. Currently, she is serving as a Post-Doctoral Fellow in Biochemistry at Saint Louis University, USA. Prior to this, she has been an Assistant Professor at the Institute of Industrial Biotechnology, Government College University Lahore, since February 2018. She also served as a Lecturer at the same institute from June 2012 to February 2018. Additionally, Dr. Akram worked as a Research Officer on several notable projects funded by the Ministry of Science and Technology and the Higher Education Commission (HEC) of Pakistan, which further honed her expertise in biotechnology and enzyme characterization.

🛠️Skills:

Dr. Akram possesses a diverse set of skills that are integral to her research and teaching endeavors. Her technical expertise includes gene cloning, enzyme characterization, and thermodynamic studies, with a particular focus on thermostable cellulolytic enzymes from thermophilic bacteria. She is proficient in molecular biology techniques such as cloning, expression, and purification of recombinant proteins. Dr. Akram also has experience in biofuel production from plant biomass, highlighting her interdisciplinary approach that bridges biotechnology and sustainable energy.

🔬Awards:

Dr. Akram has been recognized multiple times for her contributions to science and innovation. Notably, she received the prestigious SATHA Award as a team member in the project “Production of Bio-energy from Plant Biomass” during the 6th Invention to Innovation Summit in 2017. Her innovation and research excellence have also earned her several awards at various summits, including the Global Cleantech Innovation Programme by UNIDO and multiple Innovation Awards at the Invention to Innovation Summits held at the University of the Punjab. Additionally, her academic excellence is underscored by a Roll of Honor and Gold Medal from Queen Mary College and a Talent Award from the University of the Punjab.

Research Focus:

Dr. Akram’s research primarily revolves around the production of biofuels from plant biomass, with a deep focus on the cloning, expression, and characterization of thermostable enzymes. Her work is instrumental in advancing the understanding of thermophilic bacteria, particularly those belonging to the genus Thermotoga, and their potential applications in industrial biotechnology. Her research has also led to the development of hyperstable recombinant enzymes, contributing to the fields of enzyme technology and sustainable energy. Dr. Akram’s dedication to her research is evidenced by her numerous patents, which showcase her innovative contributions to biotechnology.

Conclusion:

Dr. Fatima Akram is a suitable candidate for the Best Researcher Award. Her extensive academic background, research achievements, and numerous accolades make her a strong contender. However, to enhance her profile further, a more substantial publication record and evidence of leadership in research projects would be beneficial. Nonetheless, her current qualifications and contributions already position her as a distinguished researcher with significant potential for future impact in her field.

 

Publications :

Book Title: Techniques in Biochemistry and Biotechnology
Author: Dr. Fatima Akram
Publisher: Paramount Books (Pvt) Ltd
Year: 2018

 

Chapter Title: Role of Polyphosphate-Accumulating Organisms in Enhanced Biological Phosphorous Removal
Authors: Fatima Akram, Amna Aqeel, Zeeshan Ahmed, Javeria Zafar, Ikram ul Haq
Source: Advances in Pollution Research “Microbial Consortium and Biotransformation for Pollution Decontamination”
Publisher: Elsevier
Year: 2022

 

Chapter Title: Mentha
Authors: Muhammad Akram, Muhammad Tayyab Akhtar, Fatima Akram, Umar Farooq Gohar
Source: Essentials of Medicinal and Aromatic Crops
Publisher: Springer, Cham
Year: 2023

 

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