David S. Kung

1.3k total citations
44 papers, 857 citations indexed

About

David S. Kung is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Artificial Intelligence. According to data from OpenAlex, David S. Kung has authored 44 papers receiving a total of 857 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 10 papers in Hardware and Architecture and 7 papers in Artificial Intelligence. Recurrent topics in David S. Kung's work include Low-power high-performance VLSI design (14 papers), VLSI and FPGA Design Techniques (8 papers) and VLSI and Analog Circuit Testing (8 papers). David S. Kung is often cited by papers focused on Low-power high-performance VLSI design (14 papers), VLSI and FPGA Design Techniques (8 papers) and VLSI and Analog Circuit Testing (8 papers). David S. Kung collaborates with scholars based in United States, Netherlands and India. David S. Kung's co-authors include Ruchir Puri, Ronald D. Armstrong, Leon Stok, David Z. Pan, E. L. Frome, Ulrich Finkler, S. Kulkarni, Dennis Sylvester, Haoxing Ren and John Cohn and has published in prestigious journals such as International Journal of Production Economics, IEEE Signal Processing Magazine and Mathematical Programming.

In The Last Decade

David S. Kung

42 papers receiving 792 citations

Peers

David S. Kung

EEE

HA

CNC

AI

BE

Se June Hong United States

Ghosh United States

Arnold O. Allen United States

Michael R. Grimaila United States

Martin L. Shooman United States

Nicolae Ţãpuş Romania

Sarit Mukherjee United States

Prithviraj Banerjee United States

Josep Carmona Spain

Se June Hong United States

David S. Kung

256 ×0.5

EEE

210 ×0.6

HA

142 ×1.0

CNC

272 ×3.0

AI

18 ×0.3

BE

Citations per year, relative to David S. Kung David S. Kung (= 1×) peers Se June Hong

Countries citing papers authored by David S. Kung

Since Specialization

Citations

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

Fields of papers citing papers by David S. Kung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David S. Kung. 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 David S. Kung. The network helps show where David S. Kung may publish in the future.

Co-authorship network of co-authors of David S. Kung

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

20 of 20 papers shown

1.

Cui, Xiaodong, Wei Zhang, Mingrui Liu, et al.. (2021). Asynchronous Decentralized Distributed Training of Acoustic Models. IEEE/ACM Transactions on Audio Speech and Language Processing. 29. 3565–3576. 1 indexed citations

2.

Zhang, Rui, Conrad M Albrecht, Wei Zhang, et al.. (2020). Map Generation from Large Scale Incomplete and Inaccurate Data Labels. 2514–2522. 12 indexed citations

3.

Cui, Xiaodong, Wei Zhang, Ulrich Finkler, et al.. (2020). Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies. IEEE Signal Processing Magazine. 37(3). 39–49. 17 indexed citations

4.

Finkler, Ulrich, et al.. (2019). BlueConnect: Decomposing All-Reduce for Deep Learning on Heterogeneous Network Hierarchy. 1. 241–251. 4 indexed citations

5.

Cho, Min Chul, Ulrich Finkler, Maurício Serrano, David S. Kung, & Hillery C. Hunter. (2019). BlueConnect: Decomposing all-reduce for deep learning on heterogeneous network hierarchy. IBM Journal of Research and Development. 63(6). 1:1–1:11. 59 indexed citations

6.

Zhang, Wei, Xiaodong Cui, Ulrich Finkler, et al.. (2019). A Highly Efficient Distributed Deep Learning System for Automatic Speech Recognition. 2628–2632. 13 indexed citations

7.

Kung, David S., et al.. (2018). Utilization of Information Technology as Instructional Support in Higher Education – A Case Study. Communications of the IIMA. 16(1). 2 indexed citations

8.

Kung, David S., et al.. (2017). Strategic Analysis of the Role of Information Technology in Higher Education – A KPI-centric model. Communications of the IIMA. 15(1). 1 indexed citations

9.

Finkler, Ulrich, Hubertus Franke, & David S. Kung. (2017). DYCE. 17–26. 1 indexed citations

10.

Kung, David S., et al.. (2014). Strategic use of E-Commerce in the Transformation of the Publishing Industry. Communications of the IIMA. 8(4). 6 indexed citations

11.

Kung, David S., et al.. (2012). Global Supply Chain Compliance Issues: A Cultural Perspective. RePEc: Research Papers in Economics. 149–152. 1 indexed citations

12.

Puri, Ruchir & David S. Kung. (2010). The Dawn of 22nm Era: Design and CAD Challenges. 429–433. 11 indexed citations

13.

Kung, David S. & Ruchir Puri. (2009). CAD challenges for 3D ICs. Asia and South Pacific Design Automation Conference. 421–422. 7 indexed citations

14.

Puri, Ruchir, David S. Kung, & Leon Stok. (2005). Minimizing Power with Flexible Voltage Islands. 21–24. 23 indexed citations

15.

Ren, Haoxing, David Z. Pan, & David S. Kung. (2004). Sensitivity guided net weighting for placement driven synthesis. 10–17. 27 indexed citations

16.

Puri, Ruchir, et al.. (2004). Pushing ASIC performance in a power envelope. 788–793. 17 indexed citations

17.

Kung, David S. & Ruchir Puri. (2003). Optimal P/N width ratio selection for standard cell libraries. 178–184. 11 indexed citations

18.

Kung, David S., et al.. (1992). BDDMAP: a technology mapper based on a new covering algorithm. Design Automation Conference. 484–487. 15 indexed citations

19.

Kung, David S.. (1981). Multiple choice knapsack problem-algorithms and applications. Medical Entomology and Zoology. 1 indexed citations

20.

Armstrong, Ronald D. & David S. Kung. (1979). Algorithm AS 135: Min-Max Estimates for a Linear Multiple Regression Problem. Journal of the Royal Statistical Society Series C (Applied Statistics). 28(1). 93–93. 13 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.

Explore authors with similar magnitude of impact