Peican Zhu -Natural language processing (NLP) – Best Researcher Award

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Peican Zhu -Natural language processing (NLP)

Dr.Peican zhu   distinguished academic and researcher in the field of Natural lanuage processing. Since May 2022, he has been serving as an Associate Professor at the School of Artificial Intelligence, Optics, and Electronics (iOPEN) within Northwestern Polytechnical University. Prior to this, from March 2016 to April 2022, he held the position of Associate Professor at the School of Computer Science, specifically contributing to the Center for Multidisciplinary Convergence Computing at the same university. Throughout his tenure, he has been actively engaged in academia, making significant contributions to the field of computer science and multidisciplinary convergence computing.

Education

He pursued his academic journey with a Ph.D. from the University of Alberta, Canada, spanning from September 2011 to August 2015 under the guidance of Dr. J. Han. Following this, he continued to expand his knowledge and expertise by obtaining a Master’s degree at Northwestern Polytechnical University, China, from September 2008 to April 2011, with Dr. X. Gao as his supervisor. His educational foundation was laid during his undergraduate studies at Northwestern Polytechnical University, China, where he earned his Bachelor’s degree from September 2007 to June 2008. Throughout his educational pursuits, he has demonstrated a commitment to academic excellence and a passion for advancing his understanding in the fields of computer science and related disciplines.

Professional Profiles:

Research Interest

Social computation and network science; Complex networks; Epidemic spreading and behavior vaccination; Reliability evaluation and criticality analysis Monte Carlo simulations and stochastic analysis; Evolutionary game theory; Data Science

Honors & Awards

He has garnered several prestigious honors and awards throughout his career, underscoring his dedication and contributions to various domains. In 2014, he received a Travel Award from the Canadian Institutes of Health Research (CIHR) to attend the Canadian Bioinformatics Workshops, followed by another CIHR Travel Award in 2013 for the 11th Asia Pacific Bioinformatics Conference (APBC). Notably, from May 2014 to May 2015, he was honored with the Alberta Innovates Graduate Student Scholarship, including the AITF (Alberta Innovates Technology Futures) Top-Up Award, recognizing his outstanding achievements during his graduate studies in Alberta, Canada.

Furthermore, his excellence in the field has been acknowledged with the Qian Weichang Prize in Chinese Information Processing Science and Technology, a prestigious award he received in November 2018. Adding to his list of accolades, in March 2021, he was bestowed with the Natural Science Award of Shaanxi Province, earning the coveted First Prize No. 3. These honors underscore his significant contributions and achievements in the realms of bioinformatics, technology, and information processing.

Academic Activities

He actively engages in various academic activities, particularly as a referee for numerous peer-reviewed journals, showcasing his commitment to contributing to the scholarly community. Notably, he has served as a referee for esteemed journals such as Reliability Engineering and System Safety, Microelectronic Reliability, Chaos Solitons & Fractals, Chaos, Annals of Operations Research, Scientific Reports, BMC System Biology, Biosystems, IEEE Biomedical Circuits and Systems, IEEE Transactions on Circuits and Systems II: Express Briefs, BioMed Research International, IEEE Access, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Reliability, IEEE Transactions on Industrial Electronics, Mathematical Problems in Engineering, DATE, DFT, ECCV, KSEM, and more.

In addition to his role as a reviewer, he is an active member of prominent professional organizations, including the Institute of Electrical and Electronics Engineers (IEEE) and the Reliability Branch of the China Operational Research Society. His affiliations extend to memberships in the China Computer Federation (CCF), Chinese Society of Optimization, Overall Planning and Economic Mathematics, Chinese Association for Artificial Intelligence, Association for the Advancement of Artificial Intelligence, and the Chinese Association of Automation.

Moreover, he contributes to the academic community as an associate editor for journals such as Humanities & Social Sciences Communications and Heliyon. His editorial responsibilities also include serving as a guest editor for Frontiers in Physics, Complexity (Hindawi), Mathematics (mdpi), and Applied Sciences (mdpi). These diverse roles highlight his extensive involvement and leadership within the academic and research realms.

Grants

He has been actively involved in securing research grants, showcasing his leadership and expertise in various domains. As the principal investigator, he leads the Key Research and Development Program of Shaanxi Province (Grant No. 2022KW-26) from January 2022 to December 2023, focusing on the research of intelligent decision theory and its applications. Furthermore, he spearheads the National Key Research and Development Project of China (Grant No. 2020AAA0107704) from November 2021 to October 2023, dedicated to enhancing the robustness and automatic attack and defense mechanisms of AI systems.

In the realm of network populations, he serves as the principal investigator for the National Science Foundation of China (Grant No. 62073263) from January 2021 to December 2024, exploring the mechanisms of information dissemination. His earlier contributions include leading projects such as the Stochastic Analysis of Two-layered Multiplex Networks funded by the National Science Foundation for Young Scientists of China (Grant No. 61601371) from January 2017 to December 2019.

His research extends to the aerospace domain, as seen in projects like the Reliability Evaluation of Wireless Sensor Networks in Aerospace Crafts through Stochastic Analysis (Aerospace Science and Technology Fund, January 2017 – December 2017). Additionally, he delves into reliability evaluation and optimization of complex systems through the Natural Science Basic Research Plan in Shaanxi Province of China (Grant No. 2018JQ6075) from January 2018 to December 2019.

Participating as the principal investigator and project participant in various national and provincial research initiatives, he addresses diverse topics, including epidemic spreading in dynamical complex networks, game decision under incomplete information, multi-source spatio-temporal large data perception, fusion, and analysis in public security, multi-source heterogeneous large data fusion and analysis based on network public security, and key technologies of new infrastructure’s automatic network attack-defense countermeasure. These grant projects underscore his multifaceted contributions to advancing knowledge and innovation in his field.

Publication

  1. A stochastic computational approach for accurate and efficient reliability evaluation
    J Han, H Chen, J Liang, P Zhu, Z Yang, F Lombardi
    IEEE Transactions on Computers 63 (6), 1336-1350
  2. Investigation of epidemic spreading process on multiplex networks by incorporating fatal properties
    P Zhu, X Wang, S Li, Y Guo, Z Wang
    Applied Mathematics and Computation 359, 512-524- 2019
  3. Investigating the co-evolution of node reputation and edge-strategy in prisoner’s dilemma game
    P Zhu, X Wang, D Jia, Y Guo, S Li, C Chu
    Applied Mathematics and Computation 386, 125474 – 2020
  4. A stochastic approach for the analysis of dynamic fault trees with spare gates under probabilistic common cause failures
    P Zhu, J Han, L Liu, F Lombardi
    IEEE Transactions on Reliability 64 (3), 878-892 – 2015
  5. Properties and structural analyses of USA’s regional electricity market: a visibility graph network approach
    J Hu, C Xia, H Li, P Zhu, W Xiong
    Applied Mathematics and Computation 385, 125434 – 2020
  6. Lévy noise promotes cooperation in the prisoner’s dilemma game with reinforcement learning
    L Wang, D Jia, L Zhang, P Zhu, M Perc, L Shi, Z Wang
    Nonlinear Dynamics 108 (2), 1837-1845 – 2022
  7. Difference and cluster analysis on the carbon dioxide emissions in China during COVID-19 lockdown via a complex network model
    J Hu, J Chen, P Zhu, S Hao, M Wang, H Li, N Liu
    Frontiers in psychology 12, 795142 – 2022
  8. Investigating the effects of updating rules on cooperation by incorporating interactive diversity
    P Zhu, X Hou, Y Guo, J Xu, J Liu
    The European Physical Journal B 94, 1-8 – 2021
  9. Suppression of epidemic spreading process on multiplex networks via active immunization
    Z Li, P Zhu, D Zhao, Z Deng, Z Wang
    Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (7) – 2019
  10. Community detection in temporal networks via a spreading process
    P Zhu, X Dai, X Li, C Gao, M Jusup, Z Wang
    Europhysics Letters 126 (4), 48001 – 2019

 

Guangli Wu – Video Summarization – Best Researcher Award

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Guangli Wu – Video Summarization

prof Dr. Guangli Wu  distinguished academic and researcher in the field  Video summarization.  The existence of software vulnerabilities will cause serious network attacks and information leakage problems. Timely and accurate detection of vulnerabilities in software has become a research focus on the security field. Most existing work only considers instruction-level features, which to some extent overlooks certain syntax and semantic information in the assembly code segments, affecting the accuracy of the detection model. In this paper, we propose a binary code vulnerability detection model based on multi-level feature fusion. The model considers both word-level features and instruction-level features. In order to solve the problem that traditional text embedding methods cannot handle polysemy, this paper uses the Embeddings from Language Models (ELMo) model to obtain dynamic word vectors containing word semantics and other information. Considering the grammatical structure in the assembly code segment, the model randomly embeds the normalized assembly code segment to represent it. Then the model uses bidirectional Gated Recurrent Unit (GRU) to extract word-level sequence features and instruction-level sequence features respectively.

Eduvation

He pursued his academic journey with a solid foundation in computer science and technology, earning a Bachelor’s degree from Shandong Technology and Business University in 2003. Building upon this, he delved into the realm of Computer Application Technology, completing his Master’s degree at Northwest Minzu University in 2007. Driven by a passion for cultural diversity and linguistic exploration, he further expanded his expertise by attaining a doctoral degree in Chinese Minority Ethnic Languages and Literature from Northwest Minzu University in 2011. This educational trajectory reflects his commitment to a multidisciplinary approach, seamlessly blending computer technology with a profound understanding of language and culture.
Professional Profiles:

RESEARCH INTEREST

⚫ Video Summarization
⚫ Temporal Language Localization in videos
⚫ Botnet Detection
⚫ Binary Code Vulnerability Detection
⚫ Video Abnormal Event Detection
FUND PROJECTS
1. Natural Science Foundation of Gansu Province (17JR5RA161, 21JR7RA570)
2. Gansu University of Political Science and Law Major Scientific Research and Innovation Projects
(GZF2020XZDA03)
3. Young Doctoral Fund Project of Higher Education Institutions in Gansu Province (2022QB-123)
4. Gansu Province Higher Education Innovation Fund Project (2017A-068)
5. University-level Innovative Research Team of Gansu University of Political Science and Law
6. Longyuan Youth Innovation and Entrepreneurship Talent Project (2022QB-123)

MAIN SCIENTIFIC PUBLICATIONS

1. Guangli Wu,ShengTao Wang,Shipeng Xu. “Feature fusion over hyperbolic graph convolution networks for
video summarization.” IET Computer Vision,2023.
2. Guangli Wu,Tongjie Xu. “Video Moment Localization Network Based on Text Multi-semantic Clues
Guidance.” Advances in Electrical and Computer Engineering,2023,23(3):85-92.
3. Guangli Wu,Huili Tang. “Binary Code Vulnerability Detection Based on Multi-Level Feature Fusion.” IEEE
Access,2023,11: 63904-63915.
4. Guangli Wu,Shanshan Song,Leiting Li. “Video Summarization Generation Model Based on Transformer
and Deep Reinforcement Learning.” in 2023 8th International Conference on Computer and
Communication Systems (ICCCS). IEEE, 2023: 916-921.
5. Guangli Wu,Shengtao Wang,Liping Liu. “Fast Video Summary Generation Based On Low Rank Tensor
Decomposition.” IEEE Access,2021,9:127917-127926.
6. Guangli Wu,Zhenzhou Guo,Mianzhao Wang,Leiting Li and Chengxiang Wang. “Video Abnormal Event
Detection Based on CNN and Multiple Instance Learning.” in twelfth international conference on signal
processing systems. SPIE,2021:134-139.
7. Guangli Wu,Zhenzhou Guo,Leiting Li and Chengxiang Wang. “Video Abnormal Event Detection Based on
CNN and LSTM.” in 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP).
IEEE,2020: 334-338.
8. Guangli WU,Leiting LI,Zhenzhou GUO,Chengxiang WANG and Yanpeng, YAO. “Video summarization
Based on ListNet Scoring Mechanism.” in 2020 5th International Conference on Computer and
Communication Systems (ICCCS). IEEE,2020: 281-285.
9. Guangli WU,Liping LIU,Chen Zhang and Dengtai TAN. “Video Abnormal Event Detection Based on ELM.”
in 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).IEEE,2019: 367-371