Woochul Kang

835 total citations
41 papers, 569 citations indexed

About

Woochul Kang is a scholar working on Computer Networks and Communications, Hardware and Architecture and Computer Vision and Pattern Recognition. According to data from OpenAlex, Woochul Kang has authored 41 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Networks and Communications, 15 papers in Hardware and Architecture and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Woochul Kang's work include Distributed and Parallel Computing Systems (14 papers), Parallel Computing and Optimization Techniques (11 papers) and Distributed systems and fault tolerance (9 papers). Woochul Kang is often cited by papers focused on Distributed and Parallel Computing Systems (14 papers), Parallel Computing and Optimization Techniques (11 papers) and Distributed systems and fault tolerance (9 papers). Woochul Kang collaborates with scholars based in United States, South Korea and Sweden. Woochul Kang's co-authors include Sang H. Son, Krasimira Kapitanova, John A. Stankovic, B.J. Choi, Aravind Srinivasan, Adrienne Wood, Donald R. Young, Dong In Kim, Tamim Sookoor and Qing Cao and has published in prestigious journals such as Scientific Reports, IEEE Access and IEEE Transactions on Industrial Informatics.

In The Last Decade

Woochul Kang

37 papers receiving 532 citations

Peers

Countries citing papers authored by Woochul Kang

Since Specialization

Citations

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

Fields of papers citing papers by Woochul Kang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Woochul Kang

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	QoS-Aware Inference Acceleration Using Adaptive Depth Neural Networks 2024 ·IEEE Access ·Woochul Kang	0
2	Classification of Wild Vector Mosquito Species using Convolutional Neural Networks 2021 ·KIISE Transactions on Computing Practices ·Junyoung Park, Dong In Kim, Hyung Wook Kwon, Woochul Kang	1
3	A Neural Network Decomposition Algorithm for Mapping on Crossbar-Based Computing Systems 2020 ·Electronics ·(unknown), Jacob A. Abraham, Woochul Kang, Jaeyong Chung	0
4	Classification and Morphological Analysis of Vector Mosquitoes using Deep Convolutional Neural Networks 2020 ·Scientific Reports ·(unknown), Dong In Kim, B.J. Choi, Woochul Kang, Hyung Wook Kwon	73
5	Power- and Time-Aware Deep Learning Inference for Mobile Embedded Devices 2018 ·IEEE Access ·Woochul Kang, Jaeyong Chung	5
6	DeepRT: predictable deep learning inference for cyber-physical systems 2018 ·Real-Time Systems ·Woochul Kang, Jaeyong Chung	10
7	Effective Scheduling of Grid Resources Using Failure Prediction 2016 ·Computing and Informatics / Computers and Artificial Intelligence ·Woochul Kang, Jibum Kim	0
8	Energy-efficient response time management for embedded databases 2016 ·Real-Time Systems ·Woochul Kang, Jaeyong Chung	7
9	QoS Management for Embedded Databases in Multicore-Based Embedded Systems 2015 ·Mobile Information Systems ·Woochul Kang, Jaeyong Chung	4
10	Middleware design for physically-asynchronous logically-synchronous (PALS) systems 2013 ·(unknown), (unknown), Woochul Kang, (unknown), Lui Sha	3
11	Middleware design for Physically-Asynchronous Logically-Synchronous (PALS) systems 2013 ·(unknown), (unknown), Woochul Kang, (unknown), Lui Sha	4
12	Applying Formal Methods to Modeling and Analysis of Real-time Data Streams 2011 ·Journal of Computing Science and Engineering ·Krasimira Kapitanova, Yuan Wei, Woochul Kang, (unknown)	7
13	Semantics-aware communication in sensor network applications 2011 ·Woochul Kang, Krasimira Kapitanova, Sang H. Son	1
14	Modeling and Analyzing Real-Time Data Streams 2011 ·Krasimira Kapitanova, Sang H. Son, Woochul Kang, Won-Tae Kim	3
15	A formal representation of discrete event models in Ptolemy II 2010 ·Hae Young Lee, Won-Tae Kim, (unknown), Woochul Kang, Seung Min Park	2
16	Design, Implementation, and Evaluation of a QoS-Aware Real-Time Embedded Database 2010 ·IEEE Transactions on Computers ·Woochul Kang, Sang H. Son, John A. Stankovic	18
17	PRIDE: A Data Abstraction Layer for Large-Scale 2-tier Sensor Networks 2009 ·Woochul Kang, Sang H. Son, John A. Stankovic	3
18	Failure Prediction in Computational Grids 2007 ·Woochul Kang, Andrew Grimshaw	14
19	LUSTER 2007 ·Leo Selavo, Adrienne Wood, Qing Cao, Tamim Sookoor, (unknown), Aravind Srinivasan, Yafeng Wu, Woochul Kang, John A. Stankovic, Donald R. Young, John H. Porter	164
20	A highly available job execution service in computational service market 2007 ·Woochul Kang, H. Howie Huang, Andrew Grimshaw	6

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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