Edward Gan

443 total citations
14 papers, 260 citations indexed

About

Edward Gan is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Edward Gan has authored 14 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 9 papers in Signal Processing and 5 papers in Computer Networks and Communications. Recurrent topics in Edward Gan's work include Advanced Database Systems and Queries (4 papers), Time Series Analysis and Forecasting (4 papers) and Data Stream Mining Techniques (4 papers). Edward Gan is often cited by papers focused on Advanced Database Systems and Queries (4 papers), Time Series Analysis and Forecasting (4 papers) and Data Stream Mining Techniques (4 papers). Edward Gan collaborates with scholars based in United States, United Kingdom and Israel. Edward Gan's co-authors include Peter Bailis, Jean-Baptiste Tristan, Joseph Tassarotti, Gang Tan, Greg Morrisett, Samuel Madden, Deepak Narayanan, Jialin Ding, Kai Sheng Tai and Matei Zaharia and has published in prestigious journals such as Proceedings of the VLDB Endowment, ACM Transactions on Database Systems and ACM SIGPLAN Notices.

In The Last Decade

Edward Gan

14 papers receiving 249 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Edward Gan United States	8	184	100	93	44	41	14	260
Caroline Trippel United States	8	148 0.8×	47 0.5×	117 1.3×	74 1.7×	24 0.6×	21	271
Medha Atre United States	7	126 0.7×	48 0.5×	118 1.3×	37 0.8×	72 1.8×	14	233
Manuel Rigger Singapore	9	98 0.5×	47 0.5×	153 1.6×	86 2.0×	28 0.7×	31	257
Uri Shaft United States	6	129 0.7×	126 1.3×	210 2.3×	79 1.8×	57 1.4×	13	281
Alexandros Koliousis United Kingdom	9	105 0.6×	44 0.4×	222 2.4×	81 1.8×	54 1.3×	23	289
Anil Shanbhag United States	10	119 0.6×	134 1.3×	289 3.1×	132 3.0×	78 1.9×	14	372
Spyridon Triantafyllis United States	6	104 0.6×	52 0.5×	248 2.7×	156 3.5×	15 0.4×	8	355
Samuel Jero United States	10	146 0.8×	81 0.8×	285 3.1×	58 1.3×	39 1.0×	23	349

Countries citing papers authored by Edward Gan

Since Specialization

Citations

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

Fields of papers citing papers by Edward Gan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Gan

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

14 of 14 papers shown

1.

Kang, Daniel, Edward Gan, Peter Bailis, Tatsunori Hashimoto, & Matei Zaharia. (2020). Approximate selection with guarantees using proxies. Proceedings of the VLDB Endowment. 13(12). 1990–2003. 12 indexed citations

2.

Abuzaid, Firas, Edward Gan, Erik Meijer, et al.. (2020). DIFF: a relational interface for large-scale data explanation. The VLDB Journal. 30(1). 45–70. 12 indexed citations

3.

Gan, Edward, Peter Bailis, & Moses Charikar. (2020). CoopStore. Proceedings of the VLDB Endowment. 13(12). 2174–2187. 4 indexed citations

4.

Chen, Justin, et al.. (2019). CrossTrainer: Practical Domain Adaptation with Loss Reweighting. arXiv (Cornell University). 2. 1 indexed citations

5.

Chen, Justin, et al.. (2019). CrossTrainer. 1–10. 3 indexed citations

6.

Gan, Edward, et al.. (2018). Moment-based quantile sketches for efficient high cardinality aggregation queries. Proceedings of the VLDB Endowment. 11(11). 1647–1660. 31 indexed citations

7.

Abuzaid, Firas, Peter Bailis, Jialin Ding, et al.. (2018). MacroBase. ACM Transactions on Database Systems. 43(4). 1–45. 4 indexed citations

8.

Abuzaid, Firas, Edward Gan, Erik Meijer, et al.. (2018). DIFF. Proceedings of the VLDB Endowment. 12(4). 419–432. 12 indexed citations

9.

Bailis, Peter, et al.. (2017). Prioritizing Attention in Analytic Monitoring.. Conference on Innovative Data Systems Research. 4 indexed citations

10.

Bailis, Peter, et al.. (2017). MacroBase. 541–556. 63 indexed citations

11.

Gan, Edward & Peter Bailis. (2017). Scalable Kernel Density Classification via Threshold-Based Pruning. 945–959. 17 indexed citations

12.

Bailis, Peter, et al.. (2017). Demonstration. 1699–1702. 3 indexed citations

13.

Morrisett, Greg, Gang Tan, Joseph Tassarotti, Jean-Baptiste Tristan, & Edward Gan. (2012). RockSalt. ACM SIGPLAN Notices. 47(6). 395–404. 11 indexed citations

14.

Morrisett, Greg, Gang Tan, Joseph Tassarotti, Jean-Baptiste Tristan, & Edward Gan. (2012). RockSalt. 395–404. 83 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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