Minjia Zhang

3.8k citations
98 papers · 2.1k indexed · h-index 28
Topics
Parallel Computing and Optimization Techniques (19 papers)Biochemical and Molecular Research (12 papers)Distributed systems and fault tolerance (11 papers)

In The Last Decade

Minjia Zhang

94 papers receiving 2.1k citations

Peers

Minjia Zhang
Comparison fields: 5 of 154
  • Molecular Biology 751
  • Cellular and Molecular Neuroscience 456
  • Computer Networks and Communications 379
  • Hardware and Architecture 276
  • Artificial Intelligence 270
Replace Yan Cai with:
Yan Cai China
Vikas Chandra United States
Daniel J. Costello Ireland
Xiang Wu China
Long Lu United States
Alfredo Pulvirenti Italy
Jiajing Chen China
Qingqing Chen China
John Boyle United States
Qi Guo China
Minjia Zhang relative to Yan Cai China Yan Cai's profile →
Citations per field
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Yan Cai · 1×
Citations per year

Countries citing papers authored by Minjia Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Minjia Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minjia Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Minjia Zhang. A scholar is included among the top collaborators of Minjia Zhang 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 Minjia Zhang. Minjia Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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11
DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation
4
12
HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous Memory.
17
13
AdaTune: Adaptive Tensor Program Compilation Made Efficient
9
14
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
1
15 26
16 28
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Learning Intrinsic Sparse Structures within Long Short-Term Memory
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19 108
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About Minjia Zhang

Minjia Zhang is a scholar working on Computational Mathematics, Hardware and Architecture and Parasitology, having authored 98 papers that have together received 2.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (19 papers), Biochemical and Molecular Research (12 papers) and Distributed systems and fault tolerance (11 papers). The work is most often cited by research in Hardware and Architecture (276 citations), Computational Mathematics (15 citations) and Cellular and Molecular Neuroscience (456 citations). Minjia Zhang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Margaret E. Gnegy, Lizbeth Hedstrom, Gregory D. Cuny, Yuxiong He, Bipasha Guptaroy, Cheryse A. Furman, Suresh Kumar Gorla, Michael D. Bond, Swarnendu Biswas and Aurelio Galli. Their work appears in journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Journal of Neuroscience.

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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