Linyan Mei

537 total citations
17 papers, 300 citations indexed

About

Linyan Mei is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Linyan Mei has authored 17 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Electrical and Electronic Engineering, 12 papers in Computer Vision and Pattern Recognition and 11 papers in Hardware and Architecture. Recurrent topics in Linyan Mei's work include Advanced Neural Network Applications (12 papers), Parallel Computing and Optimization Techniques (11 papers) and Advanced Memory and Neural Computing (10 papers). Linyan Mei is often cited by papers focused on Advanced Neural Network Applications (12 papers), Parallel Computing and Optimization Techniques (11 papers) and Advanced Memory and Neural Computing (10 papers). Linyan Mei collaborates with scholars based in Belgium, Switzerland and United Kingdom. Linyan Mei's co-authors include Marian Verhelst, Vikram Jain, Juan Sebastian Piedrahita Giraldo, Christian Enz, Vincent Camus, Peter Debacker, Dimitrios Rodopoulos, Rudy Lauwereins, Arindam Mallik and Ioannis A. Papistas and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Computers and IEEE Transactions on Circuits and Systems I Regular Papers.

In The Last Decade

Linyan Mei

17 papers receiving 291 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Linyan Mei Belgium	9	187	122	83	66	53	17	300
Jon J. Pimentel United States	6	158 0.8×	136 1.1×	80 1.0×	85 1.3×	86 1.6×	8	303
Vikram Jain Belgium	8	169 0.9×	83 0.7×	70 0.8×	47 0.7×	66 1.2×	23	264
Shixuan Zheng China	7	275 1.5×	167 1.4×	83 1.0×	146 2.2×	31 0.6×	8	415
Eric Qin United States	8	252 1.3×	144 1.2×	188 2.3×	125 1.9×	116 2.2×	11	459
Xitian Fan China	9	208 1.1×	238 2.0×	70 0.8×	90 1.4×	31 0.6×	13	375
Biresh Kumar Joardar United States	12	230 1.2×	80 0.7×	89 1.1×	103 1.6×	101 1.9×	39	332
Angelo Garofalo Italy	11	178 1.0×	98 0.8×	113 1.4×	71 1.1×	52 1.0×	29	286
Sehwan Lee South Korea	7	155 0.8×	95 0.8×	57 0.7×	46 0.7×	75 1.4×	22	273
Alec Lu Canada	7	114 0.6×	77 0.6×	62 0.7×	60 0.9×	41 0.8×	17	222

Countries citing papers authored by Linyan Mei

Since Specialization

Citations

This map shows the geographic impact of Linyan Mei'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 Linyan Mei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Linyan Mei more than expected).

Fields of papers citing papers by Linyan Mei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Linyan Mei. 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 Linyan Mei. The network helps show where Linyan Mei may publish in the future.

Co-authorship network of co-authors of Linyan Mei

This figure shows the co-authorship network connecting the top 25 collaborators of Linyan Mei. A scholar is included among the top collaborators of Linyan Mei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Linyan Mei. Linyan Mei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

Mei, Linyan, et al.. (2024). Stream: Design Space Exploration of Layer-Fused DNNs on Heterogeneous Dataflow Accelerators. IEEE Transactions on Computers. 74(1). 237–249. 3 indexed citations

Mei, Linyan, et al.. (2023). DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling. Lirias (KU Leuven). 570–583. 20 indexed citations

Jain, Vikram, et al.. (2023). TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge. IEEE Journal of Solid-State Circuits. 58(8). 2360–2371. 26 indexed citations

Mei, Linyan, et al.. (2023). SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–5. 2 indexed citations

Mei, Linyan, et al.. (2023). Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators. Lirias (KU Leuven). 355–357. 3 indexed citations

Mei, Linyan, Huichu Liu, Tony F. Wu, et al.. (2022). A Uniform Latency Model for DNN Accelerators with Diverse Architectures and Dataflows. 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE). 220–225. 8 indexed citations

Verhelst, Marian, et al.. (2022). ML Processors Are Going Multi-Core: A performance dream or a scheduling nightmare?. IEEE Solid-State Circuits Magazine. 14(4). 18–27. 6 indexed citations

Jain, Vikram, et al.. (2022). TinyVers: A 0.8-17 TOPS/W, 1.7 μW-20 mW, Tiny Versatile System-on-chip with State-Retentive eMRAM for Machine Learning Inference at the Extreme Edge. 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits). 20–21. 14 indexed citations

Mei, Linyan, et al.. (2022). Taxonomy and Benchmarking of Precision-Scalable MAC Arrays Under Enhanced DNN Dataflow Representation. IEEE Transactions on Circuits and Systems I Regular Papers. 69(5). 2013–2024. 7 indexed citations

10.

Mei, Linyan, et al.. (2021). Processor Architecture Optimization for Spatially Dynamic Neural Networks. Lirias (KU Leuven). 1–6. 4 indexed citations

11.

Jain, Vikram, Linyan Mei, & Marian Verhelst. (2021). Analyzing the Energy-Latency-Area-Accuracy Trade-off Across Contemporary Neural Networks. Lirias (KU Leuven). 1–4. 1 indexed citations

12.

Mei, Linyan, et al.. (2021). LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation. Lirias (KU Leuven). 1–4. 14 indexed citations

13.

Mei, Linyan, et al.. (2021). ZigZag: Enlarging Joint Architecture-Mapping Design Space Exploration for DNN Accelerators. IEEE Transactions on Computers. 70(8). 1160–1174. 78 indexed citations

14.

Mei, Linyan, et al.. (2021). Hardware-Efficient Residual Neural Network Execution in Line-Buffer Depth-First Processing. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 11(4). 690–700. 5 indexed citations

15.

Cosemans, Stefan, Linyan Mei, Ioannis A. Papistas, et al.. (2020). Opportunities and Limitations of Emerging Analog in-Memory Compute DNN Architectures. Lirias (KU Leuven). 29.1.1–29.1.4. 19 indexed citations

16.

Mei, Linyan, et al.. (2019). Sub-Word Parallel Precision-Scalable MAC Engines for Efficient Embedded DNN Inference. Lirias (KU Leuven). 6–10. 27 indexed citations

17.

Camus, Vincent, Linyan Mei, Christian Enz, & Marian Verhelst. (2019). Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 9(4). 697–711. 63 indexed citations

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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