Juncheng Yang | Artificial Intelligence | Best Researcher Award

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Mr. Juncheng Yang | Artificial Intelligence | Best Researcher Award

Juncheng Yang, born in 1982, is a PhD candidate and associate professor at Henan Polytechnic Institute. A Senior Member of the China Computer Federation, his research primarily focuses on artificial intelligence, including machine learning and AI applications. With extensive experience in both academia and research, he is dedicated to advancing AI technologies and their practical uses.

Mr. Juncheng Yang | Henan Polytechnic Institute | China

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🎓 Education

    • Juncheng Yang, born in 1982, is currently a PhD candidate. He has pursued his academic journey with a strong focus on artificial intelligence, contributing to his expertise in the field.

💼 Experience

    • Juncheng is an associate professor at Henan Polytechnic Institute. With years of experience in academia, he has made significant contributions to teaching and research in the realm of computer science and artificial intelligence.

 🏆 Honors and Awards

    • He holds the distinction of being a Senior Member of the China Computer Federation. This recognition reflects his high standing and achievements in the computer science and artificial intelligence communities.

🛠️ Skills and Certifications

    •  Juncheng Yang possesses a range of advanced skills in artificial intelligence, machine learning, and computer science. His expertise includes both theoretical and applied aspects of AI, making him a key figure in his research field.

🔬 Research Focus

    •   His main research interest lies in artificial intelligence, where he explores various aspects, including algorithms, machine learning models, and AI applications. Juncheng Yang’s work aims to push the boundaries of AI technologies and their practical implementations.

Conclusion

    • Juncheng Yang’s combination of innovative research, high-quality publications, and proven leadership in the AI field makes him an ideal candidate for the Best Researcher Award. His research not only advances the frontiers of AI technology but also holds substantial practical relevance for various industries. His achievements, ongoing contributions, and forward-looking perspective position him as one of the leading figures in AI research today.

📄Publications

  • A Time-Series-Based Sample Amplification Model for Data Stream with Sparse Samples
    Authors: Yang, J., Yu, W., Yu, F., Li, S.
    Journal: Neural Processing Letters, 2024, 56(2), 72
  • Generalizing to Unseen Domains via PatchMix
    Authors: Yang, J., Li, Z., Li, C., Yu, W., Li, S.
    Journal: Multimedia Systems, 2024, 30(1), 31
  • Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models
    Authors: Yang, J., Li, Z., Xie, S., Yu, W., Li, S.
    Conference: Proceedings – IEEE International Conference on Multimedia and Expo, 2024
  • DSDRNet: Disentangling Representation and Reconstruct Network for Domain Generalization
    Authors: Yang, J., Li, Q., Xie, S., Yu, W., Li, S.
    Conference: Proceedings of the International Joint Conference on Neural Networks, 2024
  • Soft-Prompting with Graph-of-Thought for Multi-modal Representation Learning
    Authors: Yang, J., Li, Z., Xie, S., Li, S., Du, B.
    Conference: 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 – Main Conference Proceedings, 2024

Qingyi Pan | Artificial Intelligence | Best Researcher Award

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Mr. Qingyi Pan | Artificial Intelligence | Best Researcher Award

Research Impact and Recognition:

  • Mr. Qingyi Pan has contributed to a range of impactful research projects, such as the LUNCH method for adaptive task balancing and the Virtual Trendmix Training for semi-supervised time series classification. Their work has received significant attention, evidenced by their extensive experimental validation and the reported improvements in model performance and interpretability
Mr. Qingyi Pan, Tsinghua University, China

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Scopus

🌱EARLY ACADEMIC PURSUITS

  • The individual began their academic journey at Qinghai University, graduating Rank 1/112 in Computer Science. Notable projects included developing a tourist recommendation system and optimizing HPC benchmarks on heterogeneous platforms, setting the stage for their future research in data science and computational models.

💼PROFESSIONAL ENDEAVORS

  • After serving as a lecturer at Qinghai University, the researcher gained practical experience through a Research Internship at RealAI Technology Co., Ltd, improving multivariate time series analysis. Currently pursuing a Ph.D. at Tsinghua University, they contribute to courses like Operating Systems and Students Research Training, while advancing research in Machine Learning and Data Science.

🔬CONTRIBUTIONS AND RESEARCH FOCUS 

  • The researcher’s work spans several key projects:
    1. Moment-Matching Prior Networks (MMPN) improves uncertainty estimation in deep regression.
    2. LUNCH enhances task balancing in continual learning.
    3. Virtual Trendmix Training makes time series classification more interpretable.
    4. Multivariate Time Series Forecasting integrates temporal interpretations for better predictive accuracy.

📚ACADEMIC CITES 

  • Mr. Qingyi Pan has received prestigious awards such as the China Youth Science and Technology Innovation Award, IJCAI Student Grant, and Global Second Prize in the ASC Supercomputer Challenge, reflecting their strong presence in the global research community.

🌍IMPACT AND INFLUENCE

  • Their research has greatly impacted machine learning and continual learning communities, offering scalable solutions for uncertainty quantification and adaptive learning. The focus on interpretable AI also aids industries where model transparency is crucial, like finance and healthcare.

🛠️TECHNICAL SKILLS AND TOOLBOX 

  • Proficient in Python, C++, Matlab, and C, the researcher uses Pandas, PyTorch, NumPy, and Matplotlib for data analysis and modeling, while leveraging tools like Google Cloud Platform and VS Code for efficient development and cloud computing.

🌟LEGACY AND FUTURE AND CONTRIBUTIONS

  • Looking ahead, the researcher aims to drive advancements in interpretable AI, scalable deep learning, and ethical AI, with a focus on applications like personalized medicine and automated decision systems, ensuring that AI systems are not only effective but also transparent and accountable.

📄Publications

  • Retinex Decomposition Based Low-Light Image Enhancement by Integrating Swin Transformer and U-Net-like Architecture
    • Authors: Wang, Z., Qingge, L., Pan, Q., Yang, P.
    • Journal: IET Image Processing
  • DiagNCF: Diagnosis Neural Collaborative Filtering for Accurate Medical Recommendation
    • Authors: Pan, Q., Zhang, J.
    • Journal: Lecture Notes in Computer Science (LNBI)
  • BayesTSF: Measuring Uncertainty Estimation in Industrial Time Series Forecasting from a Bayesian Perspective
    • Authors: Pan, Q., Yang, P., Zhang, J.
    • Journal: Lecture Notes in Computer Science (LNCS)
  • PMT-IQA: Progressive Multi-task Learning for Blind Image Quality Assessment
    • Authors: Pan, Q., Guo, N., Qingge, L., Zhang, J., Yang, P.
    • Journal: Lecture Notes in Computer Science (LNAI)
  • Independent Travel Recommendation Algorithm Based on Analytical Hierarchy Process and Simulated Annealing for Professional Tourists
    • Authors: Pan, Q., Wang,
    • Journal: Applied Intelligence