张炼
职务/职称
研究科学家
研究方向
科学与工程计算、流固耦合；深度学习算法与应用、图像处理、大语言模型
电子邮箱
zhanglian@sribd.cn
教育背景
浙江大学学士 2011-2015
香港科技大学博士 2015-2019
个人介绍
张炼博士于2015年在浙江大学数学系获得学士学位，2019年在香港科技大学数学系获得博士学位，2019年8月至2020年8月在美国宾州州立大学数学系从事博士后研究工作，随后在应超智能计算有限公司工作，于2022年12月加入深圳市大数据研究院。张炼博士的研究兴趣涵盖科学与工程计算及深度学习，特别关注流固耦合和计算机视觉的算法研究及其在工业领域的应用。加入研究院后，他的主要研究方向聚焦于大模型的算法及其垂直应用。
代表性论文
- Juhao Liang, Zhenyang Cai, Jianqing Zhu, Huang Huang, Kewei Zong, Bang An, Mosen Alharthi, Juncai He, Lian Zhang, Haizhou Li, Benyou Wang, Jinchao Xu. Alignment at Pre-training! Towards Native Alignment for Arabic LLMs. NeurIPS 2024.
- Huang Huang, Fei Yu, Jianqing Zhu, Xuening Sun, Hao Cheng, Dingjie Song, Zhihong Chen, Abdulmohsen Alharthi, Bang An, Ziche Liu, Zhiyi Zhang, Junying Chen, Jianquan Li, Benyou Wang, Lian Zhang, Ruoyu Sun, Xiang Wan, Haizhou Li, Jinchao Xu. AceGPT, localizing large language models in Arabic. NAACL 2024.
- Juncai He, Jinchao Xu, Lian Zhang, Jianqing Zhu. An Interpretive Constrained Linear Model for ResNet and MgNet, Neural Networks, 162, 384-392 2023.
- Jianqing Zhu, Juncai He, Lian Zhang, Jinchao Xu. FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting, Journal of Computational Sciences, 102005, 2023.
- Xiaofeng Xu, Lian Zhang, Yin Shi, Long-Qing Chen, Jinchao Xu. Integral Boundary Conditions in Phase Field Models, Computer and Mathematics with Application, 135, 1–5, 2023.
- Mingchao Cai, Mo Mu, Lian Zhang. Decoupling Techniques for Coupled PDE Models in Fluid Dynamics, Book chapter in The Essence of Large-Eddy Simulations, 10.5772/intechopen.105997, 2022.
- Jianhong Chen, Wenrui Hao, Pengtao Sun and Lian Zhang. Predict Blood Pressure by Photoplethysmogram with the Fluid-Structure Interaction Modeling, Communications in Computational Physics 31(4), 1114-1133, 2022.
- Wenrui Hao, Pengtao Sun, Jinchao Xu and Lian Zhang. An efficient computational approach for solving the fluid-structure interaction problem with an application in aneurysm, Journal of Computational Physics 433, 110181, 2021.
- Juncai He, Xiaodong Jia, Jinchao Xu, Lian Zhang, and Liang Zhao. Make l1 Regularization Effective in Training Sparse CNN, Computational Optimization and Applications 77, 163-182, 2020.
- Lian Zhang, Mingchao Cai and Mo Mu. A multirate approach for fluid-structure interaction computation with decoupled methods, Communications in Computational Physics 27, 1014-1031, 2020.
