Qiang Li | Artificial Intelligence | Best Researcher Award

Prof. Qiang Li | Artificial Intelligence | Best Researcher Award   🏆

Professor at Anhui Agricultural University, China

Prof. Qiang Li is a distinguished mathematician specializing in applied and computational mathematics. He holds a Doctor of Science from Southeast University and has over a decade of academic experience, starting with his Bachelor’s degree at Changzhi University. Currently, he serves in the Department of Applied Mathematics at Anhui Agricultural University. Prof. Li’s research focuses on stochastic systems, neural networks, and state estimation, resulting in multiple high-impact publications in renowned journals like Applied Mathematics and Computation and Neural Networks. His work contributes to advancements in Markovian switching systems, semi-Markovian models, and capital systems with stochastic effects, demonstrating his expertise and innovation.

Profile

Scopus

ORCID

Education 🎓:

Prof. Qiang Li has an impressive educational background in mathematics, showcasing a strong foundation and expertise in the field. He earned his Doctor of Science degree from the School of Mathematics at Southeast University in 2021, focusing on applied and computational mathematics. Prior to this, he completed his Master of Science at the School of Mathematics and Information Science, North Minzu University, in 2017, where he honed his skills in mathematical modeling and analysis. He began his academic journey with a Bachelor of Science degree from the Faculty of Mathematics at Changzhi University in 2014, establishing a robust base in mathematical theories and applications.

Work Experience 💼:

Prof. Qiang Li has accumulated extensive experience in the field of applied mathematics and computational systems. Since 2021, he has been a faculty member in the Department of Applied Mathematics at the School of Science, Anhui Agricultural University, where he engages in teaching, research, and academic mentorship. His professional journey encompasses expertise in stochastic systems, Markovian switching models, and neural network analysis, with a particular focus on state estimation, synchronization, and numerical methods. His collaborative efforts have led to significant advancements in mathematical modeling and computation, as evidenced by his impactful publications in esteemed international journals.

Skills 🔍

Prof. Qiang Li possesses exceptional skills in advanced mathematical modeling, stochastic processes, and numerical analysis, enabling him to address complex challenges in dynamic systems. He is proficient in analyzing Markovian and semi-Markovian switching systems, with expertise in state estimation, synchronization, and stability. Prof. Li demonstrates strong capabilities in computational tools and techniques, including matrix measures and numerical methods for fractional Brownian motion and Poisson jumps. Additionally, he has a keen understanding of neural networks, specifically complex-valued neural networks (CVNNs), and their applications in dynamic systems. His analytical and problem-solving skills are complemented by a deep commitment to innovative research.

Awards and Honors 🏆

Prof. Qiang Li has earned recognition for his significant contributions to applied mathematics and computational research. His achievements are underscored by several prestigious awards and honors, reflecting his academic excellence and impact in the field. These accolades highlight his groundbreaking work in Markovian and semi-Markovian switching systems, stability analysis, and numerical methods. His research outputs, published in high-impact journals such as Applied Mathematics and Computation and Neural Networks, have further solidified his reputation as a leading scholar, earning him respect and acknowledgment within the global academic community.

Research Interests:

Prof. Qiang Li’s research interests lie at the intersection of applied mathematics and computational science, focusing on stochastic systems, Markovian switching complex-valued neural networks (CVNNs), and semi-Markovian processes. His work delves into state estimation, synchronization, and stability analysis of dynamic systems, often under complex conditions such as missing measurements, quantization effects, and mode-dependent delays. He is also deeply engaged in exploring dissipative methods, fractional Brownian motion, and numerical methods for systems with Poisson jumps. Prof. Li’s research aims to develop innovative mathematical frameworks and computational tools for solving real-world problems in dynamic and stochastic systems.

📚 Publications 

Asynchronous Nonfragile Guaranteed Performance Control for Singular Switched Positive Systems: An Event-Triggered Mechanism

  • Authors: J. Wang, Q. Li, S. Li, L. Zhang
  • Journal: International Journal of Robust and Nonlinear Control
  • Volume: 34, Issue 17, Pages 11451-11468
  • Publication Year: 2024
  • Cited by: 0

Improved Execution Efficiency of FPE Scheme Algorithm Based on Structural Optimization

  • Authors: X.-W. Yang, L. Wang, M.-L. Xing, Q. Li
  • Journal: Electronics (Switzerland)
  • Volume: 13, Issue 20, Article 4007
  • Publication Year: 2024
  • Cited by: 0

l1 Filtering for Uncertain Discrete-Time Singular Switched Positive Systems with Time Delay and Output Quantization

  • Authors: J. Wang, A. Gao, Q. Li, B. Xie
  • Journal: Journal of the Franklin Institute
  • Volume: 361, Issue 13, Article 107028
  • Publication Year: 2024
  • Cited by: 0

Exponential Stability of Impulsive Stochastic Neutral Neural Networks with Lévy Noise Under Non-Lipschitz Conditions

  • Authors: S. Ma, J. Li, R. Liu, Q. Li
  • Journal: Neural Processing Letters
  • Volume: 56, Issue 4, Pages 208
  • Publication Year: 2024
  • Cited by: 0

Mathematical Analysis of Stability and Hopf Bifurcation in a Delayed HIV Infection Model with Saturated Immune Response

  • Authors: Z. Hu, J. Yang, Q. Li, S. Liang, D. Fan
  • Journal: Mathematical Methods in the Applied Sciences
  • Volume: 47, Issue 12, Pages 9834-9857
  • Publication Year: 2024
  • Cited by: 1

Dissipative Synchronization of Semi-Markovian Jumping Delayed Neural Networks Under Random Deception Attacks: An Event-Triggered Impulsive Control Strategy

  • Authors: H. Wei, K. Zhang, M. Zhang, Q. Li, J. Wang
  • Journal: Journal of the Franklin Institute
  • Volume: 361, Issue 8, Article 106835
  • Publication Year: 2024
  • Cited by: 8

Conclusion 

Prof. Qiang Li’s academic credentials, professional expertise, and groundbreaking research establish him as an outstanding candidate for the Best Researcher Award. His innovative contributions to Markovian systems and nonlinear mathematics position him as a leader in his field, deserving of recognition for his impact and dedication to advancing mathematical sciences.

 

JiaLi Zhu | Artificial Intelligence | Best Researcher Award

Ms JiaLi Zhu | Artificial Intelligence | Best Researcher Award 🏆

Research Fellow at University of Naples Federico II , Italy🎓

Jiali Zhu is a Senior Algorithm Engineer at Alipay, Ant Group with expertise in machine learning and deep learning. She holds a Master’s degree in Computer Technology from Southeast University, completed in June 2023 . Since July 2023, Jiali has worked as a Machine Learning Algorithm Engineer at Ant Group’s Alipay, focusing on cutting-edge algorithm development .

Professional Profile

Education🎓

Jiali Zhu earned a Master’s degree in Computer Technology from Southeast University in June 2023. Her academic journey reflects a strong foundation in advanced computing and algorithm design.

💼Work Experience

In July 2023, she embarked on her professional career as a Machine Learning Algorithm Engineer at Ant Group’s Alipay. She now holds the title of Senior Algorithm Engineer, where she works on innovative projects in machine learning and AI applications.

 🛠️Skills

Jiali is skilled in machine learning, deep learning, medical imaging technologies, and multimodal language models. Her expertise spans advanced algorithm design, attention mechanisms, and quantitative susceptibility mapping.

🏆Awards and Honors

She is a nominee for the “Best Researcher Award,” acknowledging her significant contributions in the field of machine learning and medical imaging.

 Research Focus 🔬

Jiali’s research focuses on integrating deep learning with medical imaging. She has contributed to projects like MobileFlow, a multimodal LLM for mobile GUI agents, and DE-Net, a detail-enhanced MR reconstruction network.

 

📖Publications : 

  • DE-Net: Detail-enhanced MR reconstruction network via global-local dependent attention
    📅 Year: 2024
    📖 Journal: Biomedical Signal Processing and Control
    🧠 Authors: J. Zhu, D. Hu, W. Mao, J. Zhu, R. Hu, Y. Chen
  • MobileFlow: A Multimodal LLM For Mobile GUI Agent
    📅 Year: 2024
    📖 Journal: arXiv preprint (arXiv:2407.04346)
    🧠 Authors: S. Nong, J. Zhu, R. Wu, J. Jin, S. Shan, X. Huang, W. Xu
  • Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction
    📅 Year: 2022
    📖 Journal: Quantitative Imaging in Medicine and Surgery
    🧠 Authors: J. Du, Y. Ji, J. Zhu, X. Mai, J. Zou, Y. Chen, N. Gu