Hai Li

15.9k citations
467 papers · 10.1k indexed · 1 hit paper · h-index 52

Impact in

Papers in

Hai Li

441 papers receiving 9.9k citations

Hit Papers

PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning 2017 · 622 citations
6222017202620202023200400600

Peers

Hai Li
Comparison fields: 5 of 151
  • Hardware and Architecture 1.9k
  • Electrical and Electronic Engineering 6.8k
  • Computer Networks and Communications 2.0k
  • Artificial Intelligence 2.5k
  • Cellular and Molecular Neuroscience 1.2k
Replace Huazhong Yang with:
Huazhong Yang China
Xiaobo Sharon Hu United States
David Blaauw United States
Dennis Sylvester United States
Xiaowei Li China
Yuan Xie United States
Anand Raghunathan United States
Francky Catthoor Belgium
Vivienne Sze United States
Jason Cong United States
Hai Li relative to Huazhong Yang China Huazhong Yang's profile →
Citations per field
00.5×2.7×
Huazhong Yang · 1×
Citations per year

Countries citing papers authored by Hai Li

Since Specialization
Citations

This map shows the geographic impact of Hai Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hai Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Li more than expected).

Fields of papers citing papers by Hai Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hai Li. The network helps show where Hai Li may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Hai Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hai Li Line = papers co-authored together Hai Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20240
4 20240
5 20247
6 202411
7 20243
8 202315
9 20233
10 202319
11 20234
12 202289
13 202040
14 20201
15 201916
16 20184
17 20176
18
TernGrad: ternary gradients to reduce communication in distributed deep learning
2017154
19
Faster CNNs with Direct Sparse Convolutions and Guided Pruning
201618
20 200342

About Hai Li

Hai Li is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 467 papers that have together received 10.1k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (203 papers), Ferroelectric and Negative Capacitance Devices (134 papers), Advanced Neural Network Applications (54 papers), Magnetic properties of thin films (46 papers), Parallel Computing and Optimization Techniques (45 papers), Neuroscience and Neural Engineering (42 papers), Semiconductor materials and devices (41 papers) and Advanced Data Storage Technologies (39 papers). The work is most often cited by research in Hardware and Architecture (1.9k citations), Electrical and Electronic Engineering (6.8k citations), Computer Networks and Communications (2.0k citations), Artificial Intelligence (2.5k citations) and Cellular and Molecular Neuroscience (1.2k citations). Hai Li has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Yiran Chen, Linghao Song, Xuehai Qian, Qing Wu, Miao Hu, Kaushik Roy, Garrett S. Rose, Xiuyuan Bi, Wei Wen and Chenchen Liu. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Magnetics, IEEE Transactions on Circuits and Systems I Regular Papers and IEEE Transactions on Computers.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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