Zexiao Liang | Machine Learning | Best Researcher Award

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Dr. Zexiao Liang | Machine Learning | Best Researcher Award

Doctorate at School of Integrated Circuits, Guangdong University of Technology, China

Summary:

Dr. Zexiao Liang is a postdoctoral assistant researcher at the School of Integrated Circuits, Guangdong University of Technology. He completed his Bachelor’s, Master’s, and Ph.D. degrees in Automation from Guangdong University of Technology between 2012 and 2022. Dr. Liang has extensive experience in machine learning, with a focus on multi-information fusion algorithms and domain-specific applications. He has published multiple SCI papers as the lead author and holds several invention patents. Dr. Liang is also skilled in guiding students, contributing to the publication of additional SCI papers and conference papers.

Profile:

Education:

Dr. Zexiao Liang completed his Bachelor’s degree in Automation from Guangdong University of Technology in 2016. He continued his studies at the same institution, earning a Master’s degree in Automation in 2019. Dr. Liang then pursued a Ph.D. in Automation at Guangdong University of Technology, which he completed in 2022. Throughout his academic journey, Dr. Liang consistently demonstrated exceptional academic performance, securing top ranks in his major and achieving multiple academic milestones, including the publication of several papers and the acquisition of invention patents.

Professional Experience:

Dr. Zexiao Liang has accumulated valuable professional experience as a postdoctoral assistant researcher at the School of Integrated Circuits, Guangdong University of Technology since July 2022. His work primarily focuses on the research and design of machine learning algorithms, particularly in the integration of multi-information fusion and clustering analysis. Dr. Liang has developed algorithms to address specific domain challenges, such as predicting the effects of multi-drug interactions and conducting reliability analyses for low-quality chip images. His role also involves guiding students, which has led to the publication of numerous scientific papers and contributions to various research projects.

Research Interests:

Dr. Zexiao Liang’s research interests lie in the field of multi-information fusion machine learning algorithms, including the integration of multiple transformation domain information and the development of multi-modal, multi-view learning techniques. He is particularly interested in clustering analysis and the design and application of machine learning algorithms to address domain-specific challenges. His work encompasses algorithms for predicting the effects of multi-drug interactions and reliability analysis for low-quality chip images. Dr. Liang is dedicated to advancing machine learning methodologies and their practical applications in solving complex problems in various domains.

Skills:

Dr. Zexiao Liang specializes in advanced machine learning and data analysis techniques, focusing on the integration of multiple transformation domain information, multi-modal and multi-view learning, and clustering analysis. His expertise also includes designing algorithms to address domain-specific challenges, such as predicting multi-drug interactions and analyzing low-quality chip images for reliability. He is proficient in feature fusion strategies and parameter optimization, as well as dimensionality reduction techniques for manifold-based semi-supervised classification.

 

Publications:

 

Spectral clustering based on high‐frequency texture components for face datasets

  • Authors: Z Liang, S Guo, D Liu, J Li
  • Journal: IET Image Processing
  • Volume: 15
  • Issue: 10
  • Pages: 2240-2246
  • Year: 2021
  • Citations: 3

Optimal Mean Linear Classifier via Weighted Nuclear Norm and L2,1 Norm

  • Authors: D Zeng, Z Liang, Z Wu
  • Journal: 电子与信息学报
  • Volume: 44
  • Issue: 5
  • Pages: 1602-1609
  • Year: 2022
  • Citations: 2

An effective clustering algorithm for the low-quality image of integrated circuits via high-frequency texture components extraction

  • Authors: Z Liang, G Tan, C Sun, J Li, L Zhang, X Xiong, Y Liu
  • Journal: Electronics
  • Volume: 11
  • Issue: 4
  • Article Number: 572
  • Year: 2022
  • Citations: 2

HDGN: Heat diffusion graph network for few-shot learning

  • Authors: Q Tan, Z Wu, J Lai, Z Liang, Z Ren
  • Journal: Pattern Recognition Letters
  • Volume: 171
  • Pages: 61-68
  • Year: 2023
  • Citations: 1

2D DOA Estimation Through a Spiral Array Without the Source Number

  • Authors: J Li, J Dai, Z Liang, D Liu, S Guo, Y Liu
  • Journal: Circuits, Systems, and Signal Processing
  • Volume: 41
  • Issue: 5
  • Pages: 3011-3022
  • Year: 2022
  • Citations: 1

A fusion representation for face learning by low-rank constrain and high-frequency texture components

  • Authors: Z Liang, D Zeng, S Guo, J Li, Z Wu
  • Journal: Pattern Recognition Letters
  • Volume: 155
  • Pages: 48-53
  • Year: 2022
  • Citations: 1

Face recognition via optimal mean robust linear discriminant analysis

  • Authors: D Zeng, Z Wu, Z Ren, Z Liang, S Xie
  • Conference: 2018 Chinese Automation Congress (CAC)
  • Pages: 1504-1509
  • Year: 2018
  • Citations: 1

Rajesh Prasad | Artificial Intelligence and Machine Learning for cancer detection | Best Researcher Award

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Prof Dr. Rajesh Prasad | Artificial Intelligence and Machine Learning for cancer detection | Best Researcher Award

Prof. Dr. Rajesh Prasad, a trailblazer in Artificial Intelligence and Machine Learning for cancer detection, serves as the Associate Dean (Engineering) at MIT Art, Design and Technology University, Pune, India. With a Ph.D. in Computer Science & Engineering and 27 years of experience, he has held key positions, including Director at Amity University, Jaipur, and academic roles at prestigious institutions. 🌐 Recognized for his contributions, he’s a Senior Member of IEEE, a Fellow of the Institution of Engineers, and a Life Member of ISTE and CSI. 🏆 His accolades include awards for academic excellence and a post-doc from Lincoln University College Malaysia. 🚀

Profile:

Scopus

Orcid

Google Scholar

Education:

🎓 Dr. Rajesh Prasad, an accomplished scholar and innovator, earned his Ph.D. in Computer Science & Engineering from Swami Ramanand Tirth Marathwada University in March 2012. His academic journey includes a First Class Master’s in Computer Engineering from the University of Pune in June 2004, an A Grade MBA from North Maharashtra University in June 1998, and a Distinction in BE Computer Science & Engineering from North Maharashtra University in June 1996. 🏆 With this rich educational background, Dr. Prasad has become a prominent figure in the field, contributing significantly to the realms of Artificial Intelligence and Machine Learning. 🚀

Experience:

🌟 With a diverse and enriching career spanning 27 years, Dr. Rajesh Prasad has been a dynamic force in the education sector. 🏫 He has served in pivotal roles, from Deputy Academic Director at iNurture Education Pvt. Ltd. in Bengaluru to Director at Amity School of Engg. & Tech., Amity University, Jaipur. 🎓 Dr. Prasad’s leadership includes a notable tenure as Principal, Professor, and Head of the Computer Engineering department at Sinhgad Institutes, Pune. 🚀 His impactful journey also features roles as Professor & Dean (Student’s Affair) and Head of the Department at ZES’s Dnyanganga College of Engineering and Research, Pune, and Vishwakarma Institute of Information Technology, Pune, respectively. 👨‍🏫✨

Special achievement & Awards:

🔍 Dr. Rajesh Prasad, a luminary in the realm of academia and research, boasts a stellar portfolio of accomplishments and recognitions. 🏆 Serving as a distinguished member of the editorial board for Elsevier’s International Journal of Intelligent Systems and Applications in Engineering, he brings expertise to the forefront. 🌐 His multifaceted role extends to being a key figure in educational governance, with positions on the Board of Studies at JSPM’s Rajarshi Shahu College of Engineering and as a Research Review Committee member at Symbiosis International University. 🌟 A Senior Member of IEEE, he earned recognition as an Adjunct Professor at Prowess University, Delaware, USA. 🎓 Dr. Prasad’s journey is punctuated with accolades, including the prestigious Bhartiya Bhasha Index and awards for teaching excellence. 🚀

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