Coleman Hooper

536 total citations · 1 hit paper
11 papers, 215 citations indexed

About

Coleman Hooper is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Coleman Hooper has authored 11 papers receiving a total of 215 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Signal Processing and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Coleman Hooper's work include Speech Recognition and Synthesis (7 papers), Topic Modeling (4 papers) and Speech and Audio Processing (3 papers). Coleman Hooper is often cited by papers focused on Speech Recognition and Synthesis (7 papers), Topic Modeling (4 papers) and Speech and Audio Processing (3 papers). Coleman Hooper collaborates with scholars based in United States and China. Coleman Hooper's co-authors include Kurt Keutzer, Amir Gholami, Zhewei Yao, Sehoon Kim, Michael W. Mahoney, Alexander M. Rush, Thierry Tambe, Paul N. Whatmough, Gu-Yeon Wei and En-Yu Yang and has published in prestigious journals such as IEEE Journal of Solid-State Circuits and IEEE Micro.

In The Last Decade

Coleman Hooper

10 papers receiving 206 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

AI and Memory Wall

2024 79 citations Amir Gholami, Zhewei Yao et al. IEEE Micro profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Coleman Hooper United States	6	92	92	52	46	41	11	215
Marco Donato United States	10	80 0.9×	146 1.6×	62 1.2×	58 1.3×	32 0.8×	24	249
Houxiang Ji United States	7	91 1.0×	81 0.9×	56 1.1×	56 1.2×	60 1.5×	15	181
Mohammad Samragh United States	9	170 1.8×	116 1.3×	56 1.1×	49 1.1×	26 0.6×	23	264
Peiyan Dong United States	10	76 0.8×	81 0.9×	69 1.3×	23 0.5×	17 0.4×	25	214
Sehoon Kim United States	6	78 0.8×	58 0.6×	55 1.1×	27 0.6×	28 0.7×	7	172
Joonho Song South Korea	7	65 0.7×	179 1.9×	105 2.0×	106 2.3×	88 2.1×	16	311
Lucian Prodan Romania	10	111 1.2×	89 1.0×	41 0.8×	22 0.5×	17 0.4×	53	229
Viktor Prasanna United States	5	89 1.0×	32 0.3×	30 0.6×	64 1.4×	71 1.7×	29	172
Sheng-Chun Kao United States	8	68 0.7×	125 1.4×	100 1.9×	118 2.6×	76 1.9×	15	265
Size Zheng China	8	82 0.9×	85 0.9×	115 2.2×	185 4.0×	80 2.0×	18	287

Countries citing papers authored by Coleman Hooper

Since Specialization

Citations

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

Fields of papers citing papers by Coleman Hooper

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Coleman Hooper

This figure shows the co-authorship network connecting the top 25 collaborators of Coleman Hooper. A scholar is included among the top collaborators of Coleman Hooper 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 Coleman Hooper. Coleman Hooper 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:

11 of 11 papers shown

1.

Hooper, Coleman, Muthucumaru Maheswaran, Joonki Paik, et al.. (2025). Squeezed Attention: Accelerating Long Context Length LLM Inference. 32631–32652.

2.

Gholami, Amir, Zhewei Yao, Sehoon Kim, et al.. (2024). AI and Memory Wall. IEEE Micro. 44(3). 33–39. 79 indexed citations breakdown →

3.

Lee, Nick, Se Hoon Kim, Coleman Hooper, et al.. (2024). TinyAgent: Function Calling at the Edge. 80–88. 4 indexed citations

4.

Gholami, Amir, et al.. (2024). KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization. 1270–1303. 1 indexed citations

5.

Hooper, Coleman, et al.. (2023). Property-Aware Multi-Speaker Data Simulation: A Probabilistic Modelling Technique for Synthetic Data Generation. 2 indexed citations

6.

Tambe, Thierry, Jeff Zhang, Coleman Hooper, et al.. (2023). 22.9 A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management. 342–344. 25 indexed citations

7.

Tambe, Thierry, En-Yu Yang, Coleman Hooper, et al.. (2022). A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. IEEE Journal of Solid-State Circuits. 58(2). 569–581. 12 indexed citations

8.

Tambe, Thierry, En-Yu Yang, Coleman Hooper, et al.. (2021). 9.8 A 25mm² SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET. 158–160. 24 indexed citations

9.

Tambe, Thierry, En-Yu Yang, Coleman Hooper, et al.. (2021). SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33^rd Hot Chips Symposium – August 22-24, 2021. 1–13. 1 indexed citations

10.

Tambe, Thierry, Coleman Hooper, Lillian Pentecost, et al.. (2021). EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference. 830–844. 60 indexed citations

11.

Tambe, Thierry, Coleman Hooper, Lillian Pentecost, et al.. (2020). EdgeBERT: Optimizing On-Chip Inference for Multi-Task NLP.. 7 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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