头像

吕良剑

职称: 副教授

直属机构: 通信与电子工程学院

学科:

10 访问

相关教师

个人资料

  • 部门: 通信与电子工程学院
  • 性别:
  • 专业技术职务: 副教授、博导
  • 毕业院校: 复旦大学
  • 学位: 博士
  • 学历: 研究生
  • 联系电话:
  • 电子邮箱: ljlv@cee.ecnu.edu.cn
  • 办公地址: 信息楼605
  • 通讯地址: 上海市闵行区东川路500号
  • 邮编: 200241
  • 传真:

教育经历

2016 ~ 2020  复旦大学  微电子学与固体电子学专业  理学博士

2010 ~ 2013  复旦大学  微电子学与固体电子学专业  理学硕士

2006 ~ 2010  南京大学  物理学专业  理学学士

工作经历

2021 ~ 至今  华东师范大学  副教授

2020 ~ 2021  复旦大学  研究助理

2015 ~ 2016  复旦大学  研究助理

2013 ~ 2015  泰凌微电子  工程师

个人简介

2010年在南京大学获物理学专业学士学位,2013年和2020年在复旦大学分别获微电子学与固体电子学专业硕士和博士学位,2021年起任华东师范大学副教授。在模拟混合信号集成电路设计领域具有10余年的科研及工作经验,最近的研究内容主要包括高通量无线脑机接口及智能感知芯片与系统。近5年来在SCI期刊及国际顶级会议发表文章30余篇,其中包括集成电路设计领域的顶级期刊TBioCAS、JSSC、TMTT、TCAS-II等和顶级会议ISSCC、CICC、ESSCIRC、ASSCC、ISCAS、RFIC等。多次获得国际会议最佳论文奖,包括以第一作者获得了2019年ISCAS生物医疗方向最佳论文奖和2020年ISCAS学生最佳论文奖,以通讯作者入选2024年CICC学生最佳论文候选。2020年入选上海脑科学与类脑研究中心首批“求索杰出青年”——“求索”青年研究员。

社会兼职

参加学会:IEEE会员,中国电子学会会员,中国神经科学学会。

担任审稿:IEEE TCAS-I,ISCAS等。

研究方向

依托华东师范大学集成电路学院吴幸教授团队原位先进器件中心,紧跟国际半导体器件路线图(ITRS),围绕着国家战略、集成电路的重大需求,重点开展“超越摩尔”领域的高可靠性芯片设计探索。主要研究内容包括:

1、高可靠性芯片设计:基于系统架构创新实现芯片性能与可靠性的提升,建立全面的高可靠性芯片评估体系,涵盖从芯片制造到应用的全生命周期,并拓展其在高通量无线脑机接口、智能感知系统等领域的应用。

2、IC for Life Science:开发集成模拟前端、片上处理和无线通信于一体生物医疗芯片,助力生物信息的高效采集和原位分析,促进更精准有效的诊断治疗

3、模拟集成电路设计:基于电路分析和人工智能算法,构建高效的模拟电路建模和优化算法,实现快速准确的可重构电路设计,结合先进的工艺制程提升设计的灵活性和可扩展性,满足不同应用场景要求。


超越摩尔:


IC for Life Science:

1. 高通量无线脑机接口芯片与系统设计,包括神经信号放大器、模数转换器、电源管理、射频收发机、无线能量采集电路、神经信号数据压缩与处理算法。

2. 智能感知芯片与系统设计,研究传感器信号读出及近传感器计算的低功耗片上实现。


近年来代表性芯片成果(部分):



招生信息:

1. 招收博士研究生(集成电路设计方向)。

2. 每年招收硕士研究生3~4人,包括学术型硕士研究生(微电子学与固体电子)和专业型硕士研究生(集成电路工程)。

欢迎具有微电子、电子工程、计算机等相关学科背景的同学加入!

Email: ljlv@cee.ecnu.edu.cn


招生与培养

开授课程

本科生课程:《工程与社会》,《模拟电子线路及实验》。


科研项目

进行中项目:

  1. 国家自然科学基金青年科学基金项目,面向高通量神经接口的混合信号数据压缩技术研究,2023至2025,主持

  2. 中国科学院战略性先导科技专项,基于感存算一体架构的神经接口芯片研究,2022至2024,主持

  3. 临港实验室“求索杰出青年计划”开放课题,基于微芯片的光电融合多模态神经活动记与调控系统,2022至2024,主持

  4. 上海市市级科技重大专项,脑机接口关键技术与核心器件,2021至2024,芯片项目负责人

  5. 科技部科技创新2030——“脑科学与类脑研究”重大项目,神经信号处理芯片及集成系统,2021至2026,课题骨干

  6. 上海市科委,脑态调控的神经机制研究,2020至2023,参与


已结题项目:

  1. 上海市科委,类脑芯片与片上系统研究,2016至2020,参与

  2. 上海市科委,基于微芯片技术的脑活动多道记录系统,2016至2019,参与

学术成果

芯片设计:

  1. H. Ren, L. Lyu*, B. Chen and C.-J. R. Shi, A -104dBm-sensitivity receiver with shared wireless LO and envelope-tracking mixer achieving -46dB SIR, 2024 IEEE Custom Integrated Circuits Conference (CICC), Denver, CO, USA, 2024, pp. 1-2, doi: 10.1109/CICC60959.2024.10528957. (Student best paper award final list)

  2. J. Yang, L. Lyu*, Z. Dong, H. Ren and C.-J. R. Shi, A 28-nW noise-robust voice activity detector with background aware feature extraction, 2023 IEEE Asian Solid-State Circuits Conference (A-SSCC), Haikou, China, 2023, pp. 1-3, doi: 10.1109/A-SSCC58667.2023.10347926.

  3. Q. Wang, W. Gu, H. Bi, L. Lyu*, D. Qiao and X. Wu, A spike-sorting-assisted compressed sensing processor for high-density neural interfaces, 2023 IEEE 15th International Conference on ASIC (ASICON), Nanjing, China, 2023, pp. 1-4, doi: 10.1109/ASICON58565.2023.10396355.

  4. R. Gan, L. Lyu* and C.-J. Richard Shi, A 7-Channel Bio-Signal Analog Front End Employing Single-End Chopping Amplifier Achieving 1.48 NEF, ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC), Lisbon, Portugal, 2023, pp. 5-8, doi: 10.1109/ESSCIRC59616.2023.10268787.

  5. H. Jiang et al., A 2.53 uW/channel Event-Driven Neural Spike Sorting Processor with Sparsity-Aware Computing-In-Memory Macros, 2023 IEEE International Symposium on Circuits and Systems (ISCAS), Monterey, CA, USA, 2023, pp. 1-5, doi: 10.1109/ISCAS46773.2023.10181615.

  6. H. Ren et al., A 19 uW Blocker-Tolerant Wake-Up Receiver With −90–dBm Energy-Enhanced Sensitivity, in IEEE Transactions on Microwave Theory and Techniques (TMTT), vol. 71, no. 10, pp. 4377-4392, Oct. 2023, doi: 10.1109/TMTT.2023.3267542.

  7. G. Mu, L. Lyu, D. Ye, and C.-J. Richard Shi, A chopper amplifier with a low duty-cycle sub-sampling in the switched-capacitor integrator for noise reduction. Electronics Letters.

  8. L. Lyu, Q. Wang, Z. Huang, and X. Wu, An in situ digital background calibration algorithm for multi-channel R-βR ladder DACs, Journal of Electronic Science and Technology, vol. 20, no. 1, 2022.

  9. R. Gan, L. Lyu, G. Mu, and C.-J. R. Shi, A neural recording analog front-end with exponentially tunable pseudo resistors and on-chip digital frequency calibration loop achieving 3.4% deviation of high-pass cutoff frequency in 5-to-500 Hz range, in 2022 IEEE Custom Integrated Circuits Conference (CICC), 2022: IEEE, pp. 1-2.

  10. G. Mu, D. Ye, L. Lyu, X. Zhao, and C.-J. R. Shi, An 8-channel analog front-end with a PVT-insensitive switched-capacitor and analog combo DC servo loop achieving 300mV tolerance and 0.64 s recovery time to electrode-DC offset for physiological signal recording, in 2021 IEEE Custom Integrated Circuits Conference (CICC), 2021: IEEE, pp. 1-2.

  11. L. Lyu et al., A fully-integrated 64-channel wireless neural interfacing soc achieving 110 dB AFE PSRR and supporting 54 Mb/s symbol rate, meter-range wireless data transmission,IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II), vol. 67, no. 5, pp. 831-835, 2020.

  12. L. Lyu et al., A fully-integrated 64-channel wireless neural recording SoC achieving 110 dB AFE PSRR and supporting 54 Mb/s symbol rate, meter-range wireless data transmission, in 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020: IEEE, pp. 1-4.(Student best paper award)

  13. L. Lyu, D. Ye, and C.-J. R. Shi, A 340 nW/channel 110 dB PSRR neural recording analog front-end using replica-biasing LNA, level-shifter assisted PGA, and averaged LFP servo loop in 65 nm CMOS, IEEE Transactions on Biomedical Circuits and Systems, vol. 14, no. 4, pp. 811-824, 2020.

  14. L. Lyu, Y. Wang, C. Chen, and C.-J. R. Shi, A 0.6 V 1.07 μW/Channel neural interface IC using level-shifted feedback, Integration, vol. 70, pp. 51-59, 2020.

  15. R. Xu, D. Ye, L. Lyu, and C.-J. R. Shi, A 2.0-2.9 GHz digital ring-based injection-locked clock multiplier using a self-alignment frequency tracking loop for reference spur reduction, in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), 2020: IEEE, pp. 11-14.

  16. Y. Tu, R. Xu, D. Ye, L. Lyu, and C.-J. R. Shi, A 400 MHz, 8-bit, 1.75-ps resolution pipelined-two-step time-to-digital converter with dynamic time amplification, in 2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020: IEEE, pp. 1-4.

  17. L. Lyu, D. Ye, and C.-J. R. Shi, A 340nW/channel neural recording analog front-end using replica-biasing LNAs to tolerate 200mVpp interfere from 350mV power supply, in 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019: IEEE, pp. 1-4. (Best paper award of BioCAS track)

  18. L. Lyu, Y. Wang, C. Chen, and C.-J. R. Shi, A low-voltage low-power multi-channel neural interface IC using level-shifted feedback technology, in Proceedings of the 24th Asia and South Pacific Design Automation Conference (ASP-DAC), 2019, pp. 13-14.

  19. D. Ye, R. Xu, L. Lyu, and C.-J. R. Shi, A 2.46 GHz,− 88dBm Sensitivity CMOS passive mixer-first nonlinear receiver with > 50dB tolerance to in-band interferer, in 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019: IEEE, pp. 1-4.

  20. D. Ye, Y. Wang, Y. Xiang, L. Lyu, H. Min, and C.-J. R. Shi, A wireless power and data transfer receiver achieving 75.4% effective power conversion efficiency and supporting 0.1% modulation depth for ASK demodulation, IEEE Journal of Solid-State Circuits (JSSC), vol. 55, no. 5, pp. 1386-1400, 2019.

  21. Y. Wang, D. Ye, L. Lyu, Y. Xiang, H. Min, and C.-J. R. Shi, A 13.56 MHz wireless power and data transfer receiver achieving 75.4% effective-power-conversion efficiency with 0.1% ASK modulation depth and 9.2 mW output power, in 2018 IEEE International Solid-State Circuits Conference (ISSCC), 2018: IEEE, pp. 142-144.


智能感知:

  1. Y. Chen et al., Review of the Intelligent Sensor-Memory-Control Fusion Systems. Advanced Sensor Research, 2: 2200034.

  2. H. Wangxu, L. Lyu, H. Bi, and X. Wu, Flexible pressure sensor array with multi-channel wireless readout chip, Sensors, vol. 22, no. 10, p. 3934, 2022.

  3. S. Y. Wang et al., Waterproof and Breathable Graphene-Based Electronic Fabric for Wearable Sensors. Adv. Mater. Technol. 2022, 7, 2200149.

  4. L. Chen et al., High throughput in‐situ temperature sensor array with high sensitivity and excellent linearity for wireless body temperature monitoring, Small Structures.

  5. X. Yao et al., High‐performance flexible humidity sensors for breath detection and non‐touch switches, Nano Select, 2022.

  6. X. Liu et al., Graphene‐based hydrogel strain sensors with excellent breathability for motion detection and communication, Macromolecular Materials and Engineering, 2022.

荣誉及奖励

个人荣誉:

1、2020年,上海脑科学与类脑研究中心首批“求索杰出青年”


最佳论文奖:

1、2024年,IEEE固态电路学会顶级会议CICC最佳学生论文候选Best Student Paper Final List

     (100+篇录用文章中7篇入选,通讯作者)

2、2020年,IEEE电路与系统学会旗舰会议ISCAS最佳学生论文Student Best Paper

     (800+篇录用文章中3篇获奖,第一作者)

3、2019年,IEEE电路与系统学会旗舰会议ISCAS生物医疗方向最佳论文Best Paper of the BioCAS Track

     (60+篇录用文章中唯一1篇获奖,第一作者)