陈亮 副教授 邮箱:lchenshu@shu.edu.cn 上海星空体育官网
导师介绍: 从事集成电路多物理场建模与仿真技术研究,以及集成电路EDA软件开发。在集成电路EDA和电磁场微波相关领域发表SCI/EI论文20余篇,包括IEEE T-MTT、T-CAD、T-ED、T-VLSI、IMS、EuMC、DAC、ICCAD、ASP-DAC等,参与了国家自然科学基金和美国国家自然科学基金的多个研究项目。 招收微电子、应用数学、计算机仿真、电子设计自动化等相关专业背景的硕士研究生。
研究方向: 1.电-热-应力多物理场建模与计算 2.机器学习在多物理场仿真中的应用 3.集成电路电迁移和热可靠性分析 4.高速电路信号完整性分析
教育背景: 2020年博士毕业于上海交通大学电子科学与技术专业 2015年本科毕业于西北工业大学电磁场与无线技术专业
工作经历: 2023年02月-至今 上海大学 讲师 2022年11月-2023年02月 美国加州大学河滨分校 访问助理项目科学家 2020年11月-2022年10月 美国加州大学河滨分校 博士后 2018年11月-2020年09月 美国加州大学河滨分校 访问学者
科研成果及获奖情况: 在相关领域国际权威期刊上发表SCI期刊9篇和EI会议论文13篇,包括IEEE T-MTT、T-CAD、T-ED、T-VLSI、IMS、EuMC、DAC、ICCAD、ASP-DAC等。担任2021年亚太微波会议器件与电路建模分会场主席,IEEE会员。荣获上海交通大学优秀奖学金、国家留学基金委奖学金、2016年“华为杯”第十三届全国研究生数学建模竞赛三等奖,2017年全国微波毫米波会议优秀学生论文提名等。
近五年代表性论文: Liang Chen, Sheriff Sadiqbatcha, Hussam Amrouch, and Sheldon X.-D. Tan, “Electrothermal Simulation and Optimal Design of Thermoelectric Cooler Using Analytical Approach,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 41, no. 9, pp. 3066-3077, Sept. 2022. Min Tang, Liang Chen(通讯作者), Bo Li, Haikun Yue, Yang Tang, and Junfa Mao, “Nonlinear Thermal Analysis of AlGaN/GaN HEMTs With Temperature-Dependent Parameters,” IEEE Transactions on Electron Devices, vol. 68, no. 9, pp. 4565-4570, Sept. 2021. Liang Chen, Sheldon X.-D. Tan, Zeyu Sun, Shaoyi Peng, Min Tang, and Junfa Mao, “A Fast Semi-Analytic Approach for Combined Electromigration and Thermomigration Analysis for General Multisegment Interconnects,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 40, no. 2, pp. 350-363, Feb. 2021. Liang Chen, Sheldon X.-D. Tan, Zeyu Sun, Shaoyi Peng, Min Tang, and Junfa Mao, “Fast Analytic Electromigration Analysis for General Multisegment Interconnect Wires,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 28, no. 2, pp. 421-432, Feb. 2020. Liang Chen, Min Tang, Zuhui Ma and Junfa Mao, “A novel numerical method for steady-state thermal simulation based on loop-tree and HBRWG basis functions,” Numerical Heat Transfer, Part B: Fundamentals, vol. 78, no. 5, pp.348-363, Jul. 2020. Liang Chen, Min Tang, and Junfa Mao, “A Semianalytical Gradient Model for Characterization of Conductors With Surface Roughness,” IEEE Transactions on Microwave Theory and Techniques, vol. 66, no. 12, pp. 5391-5398, Dec. 2018. Liang Chen, Wentian Jin and Sheldon X.-D. Tan, “Fast Thermal Analysis for Chiplet Design based on Graph Convolution Networks,” 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), Taipei, Taiwan, 2022, pp. 485-492. Liang Chen and Lesley Tan, “Physics-Enforced Modeling for Insertion Loss of Transmission Lines by Deep Neural Networks,” 2021 IEEE Asia-Pacific Microwave Conference (APMC), Brisbane, Australia, 2021, pp. 276-278. Liang Chen, Min Tang and Junfa Mao, “An Analytical Gradient Model for the Characterization of Conductor Surface Roughness Effects,” 2018 IEEE/MTT-S International Microwave Symposium - IMS, Philadelphia, PA, USA, 2018, pp. 1036-1038. Liang Chen, Min Tang, Qiangqiang Feng and Junfa Mao, “Transient electromagnetic-thermal simulation of debye media using alternating-direction-implicit method,” 2017 47th European Microwave Conference (EuMC), Nuremberg, Germany, 2017, pp. 892-895. Wentian Jin, Liang Chen, Subed Lamichhane, Mohammadamir Kavousi, and Sheldon X.-D. Tan, “HierPINN-EM: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnects Using Hierarchical Physics-Informed Neural Network,” 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD), San Diego, CA, USA, 2022, pp. 1-9. Wentian Jin, Liang Chen, Sheriff Sadiqbatcha, Shaoyi Peng, and Sheldon X.-D. Tan, “EMGraph: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnect Using Graph Convolution Networks,” 2021 58th ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, 2021, pp. 919-924. Mohammadamir Kavousi, Liang Chen, and Sheldon X.-D. Tan, “Electromigration Immortality Check considering Joule Heating Effect for Multisegment Wires,” 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD), San Diego, CA, USA, 2020, pp. 1-8.
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