qi zhang | food processing | Excellence in Innovation Award

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Assoc. Prof. Dr. qi zhang | food processing | Excellence in Innovation Award 

Associate professor at Yangzhou University, China

Dr. Sarah (Qi) Zhang is an Associate Professor at Yangzhou University, China, in the School of Mechanical Engineering. With extensive experience in research and academia, she has contributed significantly to the field of mechanical engineering, particularly in manufacturing, renewable energy, and AI-driven optimization. Dr. Zhang has worked on numerous high-profile projects, authored/co-authored over 40 research papers, and collaborated with leading universities and industry partners globally. Her work focuses on energy efficiency, biofuel production, and the application of computational fluid dynamics (CFD) in various engineering processes.

Publications Profile

Google Scholar

🎓 Education Details

  • Ph.D. in Industrial Engineering, Kansas State University, Manhattan, KS (Aug 2013)
    • Dissertation: “Investigation on pelleting temperature, pelleting quality, pellet sugar yield in ultrasonic-vibration assisted pelleting for ethanol manufacturing.”
  • B.S. in Information Technology, University of Wollongong, Australia (Nov 2005)

👩‍🔬 Professional Experience

1. Associate Professor, Yangzhou University, China (Aug 2016 – Present)

  • Established English graduate courses and collaborated with faculties from various international universities (University of Oregon, University of North Carolina State University, University of Texas Technology, University of Texas – Rio Grande Valley).
  • Focused on energy-saving and optimization in large-scale dryer systems, as well as AI extruder design using CFD.
  • Led two National Natural Science Foundation of China (NSFC) projects.

2. Assistant Professor, Yangzhou University, China (Sept 2013 – July 2017)

  • Worked on new biomass treatment methods for cellulosic ethanol production.
  • Managed three renewable energy projects funded by Jiangsu Province.
  • Contributed to two NSFC projects.

3. Research Assistant, Kansas State University, US (May 2009 – Aug 2013)

  • Participated in NSF projects, including the design and maintenance of an NSF career writing workshop website.
  • Taught material processing in manufacturing.

4. Software Engineer, Motorola Electronic Co. LTD, Singapore (Sept 2005 – Sept 2008)

  • Developed software programs using ASP, SQL, VB, and C.
  • Managed projects related to Hyperion Management software.

🌱 Research Interests

Dr. Zhang’s research interests are primarily centered around:

  • Energy-saving technologies: Development of energy-efficient systems, with a focus on dryers and extruder design.
  • Biomass and biofuel production: Innovation in cellulosic ethanol production, including the use of ultrasonic-vibration assisted pelleting.
  • Computational fluid dynamics (CFD): Application of CFD to optimize airflow and moisture distribution in drying and manufacturing processes.
  • AI and optimization techniques: Use of artificial intelligence in optimizing manufacturing systems and processes.

🏆 Awards and Honors

  • Yangzhou Excellent Ph.D. Award (2014-2016) – PI (Principal Investigator)
  • Scientific Research Fund from Jiangsu Province: Multiple awards for research on renewable energy and ethanol production technologies.
  • China Postdoc Fund: Investigation of ultrasonic vibration pelleting mechanisms (2014).
  • NSF Career Writing Workshops: Led several workshops from 2009-2013.
  • NSFC Projects: Several contributions to national-level projects, including optimization in 3D ultrasonic machining and non-perfect geometric parameters.

🔍 Conclusion

Dr. Sarah (Qi) Zhang is a dedicated academic and researcher, known for her leadership in the fields of mechanical engineering, renewable energy, and manufacturing systems. Her collaborative spirit has led her to work with prominent international institutions and contribute to cutting-edge research projects. With a passion for energy optimization and sustainable technologies, she continues to make significant strides in the application of CFD and AI in manufacturing and biofuel production.

Her extensive list of publications, teaching roles, and funded research projects underscore her influential role in advancing the field and fostering global academic and industry collaborations.

Publications 📚

📑 Dialdehyde cellulose nanocrystal/gelatin hydrogel optimized for 3D printing applications
📝 Y Jiang, J Zhou, Z Yang, D Liu, X Xv, G Zhao, H Shi, Q Zhang
📘 Journal of Materials Science 53, 11883-11900 (80 citations, 2018)

📑 Relationships between cellulosic biomass particle size and enzymatic hydrolysis sugar yield: Analysis of inconsistent reports in the literature
📝 Q Zhang, P Zhang, ZJ Pei, D Wang
📘 Renewable Energy 60, 127-136 (64 citations, 2013)

📑 Preparation of cellulose nanocrystals from Humulus japonicus stem and the influence of high temperature pretreatment
📝 Y Jiang, J Zhou, Q Zhang, G Zhao, L Heng, D Chen, D Liu
📘 Carbohydrate Polymers 164, 284-293 (55 citations, 2017)

📑 3D printing process of oxidized nanocellulose and gelatin scaffold
📝 X Xu, J Zhou, Y Jiang, Q Zhang, H Shi, D Liu
📘 Journal of Biomaterials Science, Polymer Edition 29 (12), 1498-1513 (52 citations, 2018)

📑 Preparation of cellulose nanocrystal/oxidized dextran/gelatin (CNC/OD/GEL) hydrogels and fabrication of a CNC/OD/GEL scaffold by 3D printing
📝 Y Jiang, J Zhou, H Shi, G Zhao, Q Zhang, C Feng, X Xv
📘 Journal of Materials Science 55 (6), 2618-2635 (48 citations, 2020)

📑 Preparation of cellulose nanofiber-reinforced gelatin hydrogel and optimization for 3D printing applications
📝 Y Jiang, X Xv, D Liu, Z Yang, Q Zhang, H Shi, G Zhao, J Zhou
📘 BioResources 13 (3) (44 citations, 2018)

📑 Effects of ultrasonic vibration-assisted pelleting on chemical composition and sugar yield of corn stover and sorghum stalk
📝 Q Zhang, P Zhang, ZJ Pei, F Xu, D Wang, P Vadlani
📘 Renewable Energy 76, 160-166 (30 citations, 2015)

📑 Investigation on characteristics of corn stover and sorghum stalk processed by ultrasonic vibration-assisted pelleting
📝 Q Zhang, P Zhang, Z Pei, D Wang
📘 Renewable Energy 101, 1075-1086 (27 citations, 2017)

📑 Ultrasonic vibration-assisted pelleting of sorghum stalks: effects of pressure and ultrasonic power
📝 Q Zhang, PF Zhang, T Deines, ZJ Pei, D Wang, X Wu, G Pritchett
📘 International Manufacturing Science and Engineering Conference 49460, 129-135 (27 citations, 2010)

📑 The untapped potential of zeolites in techno-augmentation of the biomaterials and food industrial processing operations: A review
📝 P Sharma, PP Sutar, H Xiao, Q Zhang
📘 Journal of Future Foods 3 (2), 127-141 (25 citations, 2023)

📑 A universal CRISPR/Cas12a-powered intelligent point-of-care testing platform for multiple small molecules in the healthcare, environment, and food
📝 Y Zhao, W Wu, X Tang, Q Zhang, J Mao, L Yu, P Li, Z Zhang
📘 Biosensors and Bioelectronics 225, 115102 (23 citations, 2023)

📑 Rapid, on-site, ultrasensitive melamine quantitation method for protein beverages using time-resolved fluorescence detection paper
📝 G Li, D Wang, A Zhou, Y Sun, Q Zhang, A Poapolathep, L Zhang, Z Fan, …
📘 Journal of Agricultural and Food Chemistry 66 (22), 5671-5676 (21 citations, 2018)

📑 Ultrasonic vibration-assisted pelleting of cellulosic biomass for ethanol manufacturing: An investigation on pelleting temperature
📝 Q Zhang, P Zhang, Z Pei, M Rys, D Wang, J Zhou
📘 Renewable Energy 86, 895-908 (21 citations, 2016)

📑 Inhibition of Aspergillus flavus growth and aflatoxins production on peanuts over α-Fe2O3 nanorods under sunlight irradiation
📝 D Sun, J Mao, Z Wang, H Li, L Zhang, W Zhang, Q Zhang, P Li
📘 International Journal of Food Microbiology 353, 109296 (20 citations, 2021)

📑 Design and experiment of no-tube seeder for wheat sowing
📝 X Xi, C Gu, Y Shi, Y Zhao, Y Zhang, Q Zhang, Y Jin, R Zhang
📘 Soil and Tillage Research 204, 104724 (20 citations, 2020)

📑 Predictive temperature modeling and experimental investigation of ultrasonic vibration-assisted pelleting of wheat straw
📝 Q Zhang, Z Shi, P Zhang, Z Li, M Jaberi-Douraki
📘 Applied Energy 205, 511-528 (18 citations, 2017)

📑 Efficient Prevention of Aspergillus flavus Spores Spread in Air Using Plasmonic Ag-AgCl/α-Fe2O3 under Visible Light Irradiation
📝 D Sun, J Mao, H Wei, Q Zhang, L Cheng, X Yang, P Li
📘 ACS Applied Materials & Interfaces 14 (24), 28021-28032 (17 citations, 2022)

📑 An on-site, ultra-sensitive, quantitative sensing method for the determination of total aflatoxin in peanut and rice based on quantum dot nanobeads strip
📝 S Ouyang, Z Zhang, T He, P Li, Q Zhang, X Chen, D Wang, H Li, X Tang, …
📘 Toxins 9 (4), 137 (17 citations, 2017)

📑 Experimental determination of the phase equilibrium in the Mg–Cu–Ca ternary system at 350°C
📝 Z Zhang, Q Zhang, L Jin, Y Zhang, T Cai, L Zhao, J Wang, Z Jin, L Sheng
📘 Journal of Alloys and Compounds 818, 152865 (14 citations, 2020)

📑 Computational fluid dynamic analysis of airflow in belt dryer: effects of conveyor position on airflow distribution
📝 P Zhang, Y Mu, Z Shi, Q Zhang, M Wei, M Jaberi-Douraki
📘 Energy Procedia 142, 1367-1374 (13 citations, 2017)

 

 

 

 

 

 

 

 

Qing Liang | Food Safety and Quality Control | Best Researcher Award

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Ms. Qing Liang | Food Safety and Quality Control | Best Researcher Award

College of Mechanical and Electrical Engineering at College of Mechanical and Electrical Engineering, China

Qing Liang is a graduate student in Mechanical Engineering with a strong focus on food safety and quality control. His research combines non-destructive testing methods, such as dielectric spectroscopy, with machine learning to address challenges in food quality, particularly within the dairy industry. Liang has contributed to several publications in well-regarded journals, demonstrating his expertise and commitment to advancing food science. With a passion for innovation, he is working towards bridging the gap between mechanical engineering and food safety. Liang’s ongoing research positions him as a promising young researcher in the fields of engineering and food technology.

Professional Profile

Education

Qing Liang is currently pursuing a postgraduate degree in Mechanical Engineering, graduating in the class of 2023. His academic journey has been marked by a strong foundation in engineering principles, alongside specialized focus areas such as non-destructive testing and machine learning applications in food safety and quality control. Liang’s academic training has equipped him with advanced problem-solving skills, research methodologies, and a deep understanding of both mechanical engineering and food science. His rigorous coursework and research have allowed him to contribute to innovative solutions in food safety, further solidifying his expertise in the intersection of engineering and food technology.

Professional Experience

Qing Liang currently works as a graduate student researcher at the Xinjiang Production and Construction Corps Key Laboratory of Utilization and Equipment of Special Agricultural and Forestry Products in Southern Xinjiang, China. In this role, he focuses on developing and testing innovative solutions for food safety and quality control, particularly within the dairy industry. His professional experience spans non-destructive testing, machine learning, and food safety methodologies. Qing has contributed to various projects that explore advanced techniques like dielectric spectroscopy to improve the quality and safety of agricultural products. Through his research, he actively bridges mechanical engineering and food science to address industry challenges.

Research Interests

Qing Liang’s research interests lie at the intersection of mechanical engineering, food safety, and machine learning. He focuses on applying non-destructive testing methods, such as dielectric spectroscopy, to enhance food quality control and safety, particularly in dairy products. His work explores innovative approaches to detecting adulteration, protein content, and other key factors influencing food safety. Liang is also passionate about integrating machine learning techniques with traditional testing methods to improve accuracy and efficiency in food quality assessment. By combining engineering principles with food science, his research aims to develop sustainable solutions that address current challenges in food safety and quality control.

Awards and Honors

Although Qing Liang is still early in his career, his research has already earned recognition in academic circles. He has authored multiple research papers in high-impact journals, such as the Journal of Food Science and Foods, focusing on innovative methods for food safety and quality control. Liang’s work has garnered citations, reflecting its growing influence in the field. His contributions to advancing non-destructive testing and machine learning applications in food science showcase his potential for future awards and honors. As a promising researcher, Liang’s continuous commitment to innovation positions him for further accolades in his field.

Conclusion

While LiangQing has demonstrated promise as an emerging researcher with a focus on innovative topics, they may currently lack the breadth and depth of achievements typically expected for the Best Researcher Award. Strengthening their profile with completed high-impact research, industry collaborations, and leadership roles in the scientific community would make them a stronger contender for future awards.

Publications Top Noted

  • Non-destructive detection of water adulteration level in fresh milk based on combination of dielectric spectrum technology and machine learning method
    • Authors: Liang, Q., Liu, Y., Zhang, H., Xia, Y., Li, S.
    • Journal: Journal of Food Composition and Analysis
    • Year: 2024
    • Volume: 136
    • Article Number: 106807
    • Citations: 0
  • The Study on Nondestructive Detection Methods for Internal Quality of Korla Fragrant Pears Based on Near-Infrared Spectroscopy and Machine Learning
    • Authors: Che, J., Liang, Q., Xia, Y., Zhang, H., Lan, H.
    • Journal: Foods
    • Year: 2024
    • Volume: 13(21)
    • Article Number: 3522
    • Citations: 3
  • Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk
    • Authors: Liang, Q., Liu, Y., Zhang, H., Che, J., Guo, J.
    • Journal: Journal of Food Science
    • Year: 2024
    • Volume: 89(11)
    • Pages: 7791–7802
    • Citations: 0
  • Non-Destructive Testing of the Internal Quality of Korla Fragrant Pears Based on Dielectric Properties
    • Authors: Tang, Y., Zhang, H., Liang, Q., Che, J., Liu, Y.
    • Journal: Horticulturae
    • Year: 2024
    • Volume: 10(6)
    • Article Number: 572
    • Citations: 1