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.
PacketShader
2010437 citationsSangjin Han, Keon Jang et al.profile →
E2
2015261 citationsShoumik Palkar, Sangjin Han et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Keon Jang'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 Keon Jang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keon Jang more than expected).
This network shows the impact of papers produced by Keon Jang. 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 Keon Jang. The network helps show where Keon Jang may publish in the future.
Co-authorship network of co-authors of Keon Jang
This figure shows the co-authorship network connecting the top 25 collaborators of Keon Jang.
A scholar is included among the top collaborators of Keon Jang 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 Keon Jang. Keon Jang 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
1.
Saeed, Ahmed, Prateesh Goyal, Milad Sharif, et al.. (2020). Annulus. DSpace@MIT (Massachusetts Institute of Technology). 735–749.41 indexed citations
Lee, Changhyun, et al.. (2015). Accurate latency-based congestion feedback for datacenters. USENIX Annual Technical Conference. 403–415.66 indexed citations
6.
Jang, Keon, et al.. (2015). Silo. ACM SIGCOMM Computer Communication Review. 45(4). 435–448.32 indexed citations
7.
Jang, Keon, et al.. (2015). Silo. 435–448.116 indexed citations
8.
Han, Sangjin, Keon Jang, Aurojit Panda, et al.. (2015). SoftNIC: A Software NIC to Augment Hardware. UC Berkeley.120 indexed citations
9.
Ballani, Hitesh, Keon Jang, Thomas Karagiannis, et al.. (2013). Chatty tenants and the cloud network sharing problem. Networked Systems Design and Implementation. 171–184.87 indexed citations
10.
Jang, Keon, et al.. (2013). Silo: Predictable Message Completion Time in the Cloud.15 indexed citations
Han, Sangjin, Keon Jang, KyoungSoo Park, & Sue Moon. (2010). PacketShader: Massively Parallel Packet Processing with GPUs to Accelerate Software Routers. Networked Systems Design and Implementation.2 indexed citations
13.
Han, Sangjin, Keon Jang, KyoungSoo Park, & Sue Moon. (2010). PacketShader. 195–206.437 indexed citations breakdown →
14.
Han, Sangjin, Keon Jang, KyoungSoo Park, & Sue Moon. (2010). PacketShader. ACM SIGCOMM Computer Communication Review. 40(4). 195–206.179 indexed citations
Jang, Keon, Sangman Kim, Geoffrey M. Voelker, & Sue Moon. (2009). Implementation and evaluation of a mobile planetlab node.1 indexed citations
17.
Jang, Keon, Sangman Kim, Geoffrey M. Voelker, & Sue Moon. (2009). Implementation and Evaluation of a Mobile Wireless PlanetLab Node.1 indexed citations
18.
Jang, Keon, et al.. (2008). Improving Delay Estimation with Path Stitching.
19.
Jang, Keon, et al.. (2008). Design consideration for a mobile testbed.1 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.