Li Jia Department
of Computer Science & Engineering, Shanghai Jiao Tong University Office:
Rm521, SEIEE Building #03, Dong Chuan Road #800, Min Hang District, Shanghai Tel:
86-21-34208232 Photo Email: ljiang_cs
AT sjtu.edu.cn I'm
recuiting self-motivated students for Ph.D, Master postgraduate
program and research assistants. I＇ｍ recruiting Experienced
system engineers, Scholars in computer architecture, EDA and AI areas,
and self-motivated student research assistant! |
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News |
探索键值压缩的边界：MILLION开源框架定义模型量化推理新范式，入选顶会DAC
2025: 开源链接：https://github.com/ZongwuWang/MILLION -
Our paper“BLADE”on DRAM-based
LLM Acceleration has been accepted to ASP-DAC 2026. Congratulations to
Yilong. -
The“FlexQuant”quantization
framework for LLM Acceleration has been reported by Asystem Team From Ant
Group (Chinese: 蚂蚁集团). Congratulations to Zongwu. -
Our two papers on“PIM+NeRF”and“PIM+Database (OLAP and OLTP)”have been
accepted by ASPLOS 2026! Congratulations to Haomin and Yilong. -
Our paper on“Enhancing Robustness of Binary
Hyper-Dimensional Computing”has been accepted by ACM
TACO 2025! Congratulations to Haomin. -
Our two papers on brain-inspired computing (HDC) and
Quantum-Classical Computing have been accepted by ISCA 2025! Congratulations
to Haomin. -
Our paper " PUSHtap:
PIM-based In-Memory HTAP with Unifed Data Storage Format" has been
accepted by ASPLOS 2025! Congratulation to Yilong Zhao and others. -
Our paper " ASDR:
Exploiting Adaptive Sampling and Data Reusefor CIM-based Instant Neural
Rendering" has been accepted by ASPLOS 2025! Congratulation to Haomin Li
and others. -
Our two papers on the Acceleration with Sparse Compilation
Optimization and Guassian Splatting have been accepted by HPCA 2025!
Congratulations to Shiyuan Huang and others. -
Our five papers on the brain-inspired HDC and LLM acceleration
have been accepted by DATE 2025! Congratulations to Haomin Li, Zongwu Wang,
Ning Yang and others. Welcome to follow our public account！WeChat
ID：gh_c7b330226334 |
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Short Bio |
Li Jiang
received the B.S. degree from the Dept. of CS&E, Shanghai Jiao Tong
University in 2007, the MPhil, and the Ph.D. degree from the Dept. of
CS&E, the Chinese University of Hong Kong in 2010 and 2013, respectively.
He has
been working on Computer Architecture and Design Automation for years. His
research interests are Domain Specific Architecture for emerging
applications, e.g., AI, database and Networking, emerging computer
architecture such as compute-in-memory, near-data processing and etc. He has
published more than 100 peer-review papers in top-tier computer architecture,
EDA and AI/Database conferences and journals, including ISCA, MICRO, DAC,
ICCAD, AAAI, ICCV, SigIR, TC, TCAD, TPDS and etc. He received the Best Paper
Award in DATE＇22,
DATE＇23,
Best Paper Nomination in ICCAD10, and DATE21. According to the IEEE Digital
Library, five articles ranked in the top 5 of citations of all papers
collected at its conferences. Some of the achievements have been introduced
into the IEEE P1838 standard, and several technologies have been in
commercial use in cooperation with TSMC, Huawei, and Alibaba. He got
the best Ph.D. Dissertation award in ATS 2014, and he was in the final list
of TTTC＇s
E. J. McCluskey Doctoral Thesis Award. He received ACM Shanghai Rising Star
award and CCF VLSI early career award in 2019. He received the 2nd
class prize of Wu Wenjun Award for Artificial Intellegence. He
has been selected the national ten
thousand talents plan—top-notch young talents, 2023. He serves as co-chair
and TPC member in several international and national conferences, such as
MICRO, DATE, ASP-DAC, ITC-Asia, ATS, CFTC, CTC, etc. He is an Associate
Editor of IET Computers Digital Techniques, VLSI, the Integration Journal. He
is the co-founder of ChinaDA and ACM/SigDA East China Branch. |
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Research Interest |
- Near Data Processing,
Compute-in-memory, Neuromorphic Computing - Domain Specific
Architecture for AI, Database, networking etc. - AI compiling framework |
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Teaching |
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CS3301 GPU
Computing and Deep Learning(2024，2025) -
CS7310H Algorithm
Design and Analysis(2024，2025) -
CS7359 Artificial Intelligence Systems and
Optimization(2024，2025) -
CS2951
Computer System (2022，2023，2024) -
CS308
Compiler Principles (2015-2017, 2021, 2022) -
CS427
Multicore Architecture and Parallel
Programming (2014-2016,2021,2022,2023) -
CS222
Algorithm Design and Analysis (2018-2020) -
CS339 Computer Networks (2014-2016) |
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Honor |
- Selected The National Ten
Thousand Talents Plan—Top-notch Young Talents, 2023（入选万人计划——青年拔尖人才计划） - Wu Wen Jun Award for
Artificial Intelligence, 2nd class, 2021 - CCF Distinguished
Lecturer, 2020 - CCF VLSI Early Career
Award, 2019 - ACM Shanghai Rising Star
Award, 2019 - Youth sailing program of
excellence in science and technology, 2015 - IEEE TTTC Doctoral Thesis
Award Semi-final, Asian Test Symposium, Best Thesis Award (Rank 1), Nov. 2014 - CCF-Tecent "rhino
bird" creativity award fund - Nominated for Best Paper
Award, IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
2010 - Certificate of Merit for
Excellent Teaching Assistant Department of CS&E, CUHK, Hongkong SAR 2010 - Outstanding graduate of
colleges and universities in Shanghai, China 2007 |
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Honor(student) |
- Best Paper Award (Embedded
Systems Design Track), DATE 2023. Congratulation to Zhuoran Song and others. - Spark Award
(Data-free/Label-free), Huawei, 2022. Congratulation to Fangxiu Liu. - Best Paper Award (Test
& Dependability Track), DATE 2022. Congratulation to Zongwu Wang and
others. - Best Paper Award
Nomintion(E Track), DATE 2022. Congratulation to Tao Yang and others. -National
Scholarship(2021,2022)-Fangxiu Liu; -National Scholarship(2021)-Tao
Yang; -Wu Wen Jun Honorary
Doctoral Scholarship, 2021-Fangxiu Liu. |
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Publication |
My DBLP，Google
Scholar，IEEE and ACM profile Recent Publication: Transactions and Journals 2025 [1] Jiahao Sun, Yijian Zhang, Fangxin Liu*, Li
Jiang, and Rui Yang, " A Sub-10 μs In-Memory-Search Collision Detection
Accelerator Based on RRAM-TCAMs," accepted by IEEE Transactions on
Computer-Aided Design of Integrated Circuits and Systems(TCAD), 2025(CCF-A) [2] Shiyuan
Huang, Fangxin Liu*, Tao Yang, Zongwu Wang, Ning Yang and Li Jiang*, " SpMMPlu-Pro: An Enhanced Compiler Plug-in for Efficient SpMM and Sparsity Propagation Algorithm,"accepted
by IEEE Transactions on Computer-Aided Design of Integrated Circuits and
Systems (TCAD), 2025 (CCF-A) [3] Shiyuan
Huang=, Fangxin Liu=, Tian Li, Zongwu
Wang, Ning Yang, Haomin Li, and Li Jiang*,
" STCO: Enhancing Training Efficiency via Structured Sparse Tensor
Compilation Optimization,"accepted by ACM
Transactions on Design Automation of Electronic Systems (TODAES), 2025 (CCF-B)
[4] Haomin Li, Fangxin Liu*,
Zongwu Wang, Ning Yang, Shiyuan
Huang, Xiaoyao Liang, and Li Jiang,
"Attack and Defense: Enhancing Robustness of Binary Hyper-Dimensional
Computing," accepted by ACM Transactions on Architecture and Code
Optimization (TACO), 2025(CCF-A) [5] Zhuoran Song, Jiabei Long, Li Jiang, Naifeng Jing, Xiaoyao Liang,
"GCNTrain+: A Versatile and Efficient
Accelerator for Graph Convolutional Neural Network Training," accepted
by ACM Transactions on Architecture and Code Optimization (TACO), 2025(CCF-A) [6] Xuhang Wang, Zhuoran Song, Chunyu Qi, Fangxin
Liu, Naifeng Jing, Li Jiang, Xiaoyao Liang, "RTSA: A Run-Through Sparse Attention
Framework for Video Transformer,"accepted by
IEEE Transactions on Computers (TC), 2025 (CCF-A) 2024 [1].
Fangxin Liu, Zongwu Wang,Wenbo Zhao, Ning Yang, Yongbiao Chen,Shiyuan
Huang,Haomin Li,Tao Yang,Songwen Pei,Xiaoyao Liang and Li
Jiang*, “Exploiting Temporal-Unrolled Parallelism for Energy-Efficient SNN
Acceleration＂, accepted by IEEE Transactions on
Parallel and Distributed Systems (TPDS), 2024 (CCF-A) [2].
Shiyuan
Huang, Fangxin Liu*, Tao Yang, Zongwu Wang, Ning Yang and
Li Jiang*, “SpMMPlu-Pro: An Enhanced Compiler Plug-in for Efficient SpMM and
Sparsity Propagation Algorithm＂, accepted by IEEE Transactions
on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2024 (CCF-A) 2023 [3].
Fangxin
Liu, Wenbo Zhao, Zongwu Wang,Yongbiao Chen, Xiaoyao Liang and
Li Jiang*, “ERA-BS: Boosting the Efficiency of ReRAM-based PIM Accelerator
with Fine-Grained Bit-Level Sparsity＂, accepted by IEEE
Transactions on Computers (TC), 2023 (CCF-A) 2022 [4].
Fangxin
Liu,Zongwu Wang,Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang and Li
Jiang*, “SoBS-X:Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural
Network Accelerator＂, accepted by IEEE Transactions on Computer-Aided Design
of Integrated Circuits and Systems(TCAD), 2022
(CCF-A) [5].
Tao
Yang，Dongyue
Li，Fei Ma，Zhuoran Song，Yilong Zhao，Jiaxi Zhang，Fangxin Liu and Li Jiang*, “PASGCN:
An ReRAM-Based PIM Design for GCN with Adaptively Sparsified Graphs”, accepted by IEEE Transactions on Computer-Aided Design of
Integrated Circuits and Systems（TCAD）, 2022 (CCF-A) [6].
Weidong
Cao, Yilong Zhao, (CO-first author), Boloor Adith Jagadish, Yinhe Han, Xuan
Zhang*, Li Jiang*, “Neural-PIM: Efficient Processing-In-Memory with Neural
Approximation of Peripherals”, accepted by IEEE
Transactions on Computers (TC), Accepted, 2022 (CCF-A) [7]. Fangxin Liu,
Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Tao Yang and Li Jiang*, “SSTDP:
Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural
Network Training”, accepted by Frontiers in Neuroscience, section Neuromorphic
Engineering, 2022 [8].
Fangxin
Liu, Wenbo Zhao, Zongwu Wang, Yilong Zhao, Tao Yang, Yiran Chen and Li
Jiang*, “IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied
Quantization“, IEEE Transactions on Computer-Aided
Design of Integrated Circuits and Systems(TCAD）, 2022 (CCF-A) Peered-review Conferences 2022 [9]. Fangxin Liu, Zongwu Wang,
and Li Jiang*, “Irregular and Match: A Co-Design Framework for Energy Efficient
Processing in Spiking Neural Networks”, to appear in
IEEE International Conference on Computer Design, 2022 (CCF-B) [10]. Xuan Zhang, Zhuoran Song,
Xing Li, Linan Yang, Qijun Zhang, Zhezhi He, Li Jiang, Naifeng Jing
and Xiaoyao Liang*, “IHAA: An Item-Hotness-Aware RRAM-based Accelerator for
Recommendation Model”, to appear in IEEE
International Conference on Computer Design, 2022 (CCF-B) [11].
Zhi
Li, Yanan Sun, Zhezhi He, Liukai Xu, Li Jiang*, “CIM-ISP: Computing
In-Memory for Image Signal Processing”, Proceedings
of Asia and South Pacific Design Automation Conference (ASP-DAC),
Japan, 2022 (CCF-C) [12].
Qidong
Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li
Jiang*, "HAWIS: Hardware-Aware Automated WIdth Search for Accurate,
Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product
Engine," 27th Asia and South Pacific Design Automation Conference (ASP-DAC),
2022, pp. 226-231 (CCF-C) [13].
Yu
Gong, Zhihan Xu, Zhezhi He, Weifeng Zhang, Xiaobing Tu, Xiaoyao Liang, Li
Jiang*, “N3H-Core: Neuron-designed Neural Network Accelerator via
FPGA-based Heterogeneous Computing Cores”,
Proceedings of the 2022 ACM/SIGDA International Symposium on
Field-Programmable Gate Arrays (FPGA), February 2022, Pages 112–122 (CCF-B) [14].
Fangxin
Liu，Haomin
Li，Xiaokang Yang，Li Jiang*, “L3E-HD: A Framework Enabling Efficient Ensemble in
High-Dimensional Space for Language Tasks”，International
Conference on Research and Development in Information Retrieval (SIGIR),
2022 (CCF-A) [15].
Fangxin
Liu, Wenbo Zhao, Zongwu Wang,Qidong Tang, Yongbiao Chen,Zhezhi He,Naifeng
Jing,Xiaoyang Liang and Li Jiang*, “EBSP: Evolving Bit Sparsity Patterns for
Hardware-Friendly Inference of Quantized Deep Neural Networks”, ACM/IEEE Design Automation Conference (DAC), 2022 (CCF-A) [16].
Fangxin
Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang
Yang and Li Jiang*, “SATO: Spiking Neural Network Acceleration via Temporal-Oriented
Dataflow and Architecture”, ACM/IEEE Design
Automation Conference (DAC), 2022 (CCF-A) [17].
Fangxin
Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong
Tang, Tao Yang, Cheng Zhuo and Li Jiang*, ”PIM-DH: ReRAM-based
Processing-in-Memory Architecture for Deep Hashing Acceleration”, ACM/IEEE Design Automation Conference (DAC), 2022 (CCF-A) [18].
Fangxin
Liu，Wenbo
Zhao, Zongwu Wang,Yongbiao Chen, Li Jiang*, “SpikeConverter:
An Efficient Conversion Framework Zipping the Gap between Artificial Neural
Networks and Spiking Neural Networks”, Association
for the Advancement of Artificial Intelligence(AAAI), 2022 (CCF-A) [19].
Tao
Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi
He and Li Jiang*, “DTQAtten: Leveraging Dynamic Token-based Quantization for
Efficient Attention Architecture”, Design Automation
& Test in Europe Conference & Exhibition (DATE), 2022 (CCF-B) [20].
Zongwu
Wang, Zhezhi He, Rui Yang, Shiquan Fan, Jie Lin, Fangxin Liu, Yueyang Jia,
Chenxi Yuan, Qidong Tang, and Li Jiang*, “Self-Terminated Write
of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing”, Design Automation & Test in Europe Conference &
Exhibition (DATE), 2022 (CCF-B) (Best
Paper Award) |
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Finished Project |
1．国家自然科学基金重点项目、“集成电路近似计算基础理论与设计方法”
、2019/01-2023/12、子课题负责人 2．亿铸智能科技：“面向基于ReRAM忆阻器的存算一体智能芯片架构和编译器研究项目”，2021-2024、主持 3．华为横向课题，“近cache计算架构”，2021-2022、主持 4.华为横向课题，“面向通信系统的存算一体实现研究项目”， 2021-2022、主持 5.华为横向课题，“稀疏AI框架研究”， 2021-2022、主持 6.国家自然科学基金青年项目、“单体三维碳纳米晶体管存储器的容错技术研究与实现”、2017/01-2019/12、主持。 7.国家重点研发计划，“信息产品及科技服务集成化众测服务平台研发与应用”、参与（校内主持），2019/01-2021/12 8.上海交通大学重点前瞻布局基金，“忆阻器阵列芯片”，2020-2021、主持 9.上海市青年科技英才扬帆计划、“基于碳纳米管技术的计算机体系架构探索与研究”、2015/01-2017/12、主持 10.上海市自然科学基金探索类项目、“适合在线学习的类脑芯片计算架构”、2018/01-2021/7、主持 11.中兴通讯产学研合作项目，“低能耗CNN深度学习图像识别算法”，主持，2018-2020 12.阿里巴巴AIR横向课题，“分布式系统IO性能问题检测与定位”，参与，2019-2020 13.阿里巴巴AIR横向课题、“A LSTM-Recurrent Generative Adversarial Network (RGAN) based
Health-Status Analysis for Distributed System”、主持，
2018-2019 14.阿里巴巴AIR横向课题，“基于样本与特征增强的大规模数据中心内存故障预测”，主持，2019-2020 15.阿里巴巴AIR横向课题，“针对资源受限架构的DNN模型压缩技术”， 主持，2019-2020 16.华为横向课题，“基于ReRAM的高效可靠DNN加速器技术研究”， 2019-2020，主持 17.华为横向课题，“端侧稀疏化深度神经网络训练框架”， 2019-2020、主持 18.华为智库专家， 2019-2020 19.华为横向课题，“低延迟SoC通信协议评估与优化”， 2019-2020、主持 20. Intel Gift, DNN
acceleration with heterogeneous computing, 2020 |
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On-Going Project |
1、科技部-国家重点研发计划：“面向存算AI芯片的“模型压缩部署, 架构自动搜索”框架及关键技术研究”，2025-2027、主持 2、中组部人才项目：“基于DRAM的近存计算系统架构关键技术研究”，2024-2026、主持 3、华为技术：“基于低精度格式的模型加速技术合作”，2025-2026、主持（刘方鑫老师） 4、深圳中兴软件：“软硬件协同的多模型量化稀疏压缩产学研合同”，2025-2027、主持（刘方鑫老师） 5、阿里云飞天信息技术：“大模型面向AI推理业务的显存占用优化”，2025-2026、主持（刘方鑫老师） 6、华为技术：“基于低精度格式的模型加速技术合作”，2025-2026、主持（刘方鑫老师） 7、华为技术：“基于数学方法的大模型混合精度量化寻优技术合作”，2025-2026、主持（刘方鑫老师） 8、阿里人工智能与系统联合实验室：“面向大模型的自适应负载感知分布式训练和推理优化技术研究”，2024-2026、参与（刘方鑫老师） 9、华为集群与协同智算网络联合实验室：“面向大规模异构算力的同步通信加速项目委托研发”，2024-2026、参与（刘方鑫老师） 10、华为技术：“转发高性能仿真委托研发项目”，2025-2026、主持（刘方鑫老师） 11、中兴通讯：“多模型适配的高效量化压缩平台技术研究”，2024-2025、主持（刘方鑫老师） 12、华为技术：“基于PQ压缩 KVCache 以查代算推理和长序列切分感知调度加速技术合作项目委托研发”，2024-2025、主持（刘方鑫老师） |
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Research Group |
Current: PhD: Ning Yang; Yilong Zhao;
Haoming Li; Hanjing Shen; Runpei
Cai; Jiaxuan Zhang. Master: Yiwei Hu; Tianheng
Wang; Gongye Chen; Kaixiang Yang; Ziyan Gan; Bowen Zhu;
Xuwen Zhou; Yue Liang; Chenyang
Guan. Collaborators @ SJTU team: @ School of Computer Science Zhezhi He (Associate Professor), Zhuoran Song (Associate Professor), and Xiaoyao Liang (Professor) @ School of lntegrated Circuits Yanan Sun (Associate
Professor), Yaoyao Ye (Associate Professor), Naifeng
Jing (Professor) @ Joint Institute Rui Yang (Professor), Weikang Qian (Associate Professor) Alumni: Graduated in 2025: Zongwu Wang (SJTU-SQZ Joint Postdoctoral Fellow),Shiyuan Huang (SHU Faculty),Longyu Zhao (Huawei), Peng
Xu (SJTU-SQZ Joint PhD Candidate) Graduated in 2024: Hui Ma(Huawei),Feng Xu(Tencent) Graduated in 2023: Fangxin Liu(Assistant Professor@SJTU), Tao Yang(Huawei's "Genius Youth" program 2023),
Qidong Tang(MING HONG INVESTMENT), Yiyuan Zhou(MOORE THREADS) Graduated in 2022: Tian Li
(Huawei), Yunyan Hong (ByteDance), Hanchen Guo (ICBC) Graduated in 2021: Zhuoran Song(co-supervised, Associate
Professor@SJTU) Graduated in 2020: Xiaoyi
Sun (AntGroup), Xingyi Wang (ByteDance), Yilong Zhao (Shanghai Qizhi Research
Institute), Chaoqun Chu (Megvii) Graduated in 2019: Zishan
Jiang (SenseTime),Chengwen Xu(NVIDIA), Jianfei Wang( Sensetime) Graduated in 2018: Jun Li
(miHoYo), Hao Dong (Akuna Capital),Yi Liu (DJI),Lerong Chen
(Entrepreneurship),Tianjian Li ( Sensetime) Graduated in 2017: Feng Xie
(ele.me), Xiangyu Wu (Google), Xiangwei Huang(Huawei) Graduated in 2016: Yihuang Huang (Netease Games), Hao Chen (UT-Austin), Mengyun Liu (Duke), Wenkang Yu (UCSD), Jiawen Li (UCLA), Xiangyu Bi (UT-Austin), Yan Han, Chengkai Zhu (UCSD) |
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Research Activity |
Chair: TPC chair in
CFTC2021, General Chair in ChinaDA, Tutorial Chair in ITC-Asia, Workshop
Chair in CTC/CFTC Associate Editor: IET
Journal on Computers & Digital Techniques TPC Member: Design
Automation and Test in Europe Conference (DATE); Asia and South Pacific
Design Automation Conference (ASP-DAC); Asian Test Symposium (ATS); 3D-Test
workshop; IEEE/ACM International Symposium on Nanoscale Architectures
(NANOARCH), IEEE Computer Society Annual Symposium on VLSI (ISVLSI), IEEE
Microarchitecture (MICRO) Reviewer: IEEE Transaction
on CAD of Integrated Circuits and Systems (TCAD), IEEE Transactions on Very
Large Scale Integration (VLSI) Systems (TVLSI), IEEE Transactions on Computer
(TC), ACM/IEEE Design Automation Conference (DAC), Asian Test Symposium conference
(ATS). |
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