Edward Chien

422 citations
18 papers · 239 · h-index 8

Impact in

Papers in

Edward Chien

17 papers receiving 234 citations

Peers

Edward Chien
Comparison fields: 5 of 38
  • Computer Graphics and Computer-Aided Design 166
  • Computational Mechanics 192
  • Computer Vision and Pattern Recognition 46
  • Architecture 2
  • Industrial and Manufacturing Engineering 13
Replace Swen Campagna with:
Swen Campagna Germany
Hsueh‐Ti Derek Liu Canada
Zbyněk Šı́r Czechia
Marko Mihajlović Switzerland
Jean‐Marc Thiery France
Zorah Lähner Germany
Scott Kircher United States
Ramón F. Sárraga United States
Boyang Deng United States
Thibault Groueix United States
Edward Chien relative to Swen Campagna Germany Swen Campagna's profile →
Citations per field
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Citations per year

Countries citing papers authored by Edward Chien

Since Specialization
Citations

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

Fields of papers citing papers by Edward Chien

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Edward Chien, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Edward Chien Line = papers co-authored together Edward Chien links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201854
2 201738
3 201633
4 201623
5 202117
6 202017
7 201916
8 202310
9 20177
10 20236
11 20244
12
Stochastic Wasserstein Barycenters
20184
13
Hierarchical Optimal Transport for Document Representation
20193
14 20243
15
Incorporating unlabeled data into distributionally-robust learning
20212
16 20251
17 20191
18 20250

About Edward Chien

Edward Chien is a scholar working on Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 18 papers that have together received 239 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (8 papers), Advanced Numerical Analysis Techniques (7 papers), Computational Geometry and Mesh Generation (7 papers), Computer Graphics and Visualization Techniques (6 papers), Advanced Vision and Imaging (4 papers), Optical measurement and interference techniques (2 papers), Imbalanced Data Classification Techniques (1 paper) and Numerical methods in engineering (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (166 citations), Computational Mechanics (192 citations), Computer Vision and Pattern Recognition (46 citations), Architecture (2 citations) and Industrial and Manufacturing Engineering (13 citations). Edward Chien has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Ofir Weber, Justin Solomon, David Bommes, Renjie Chen, Emily Whiting, Liane Makatura, Etienne Vouga, Sebastian Claici, Charlie Frogner and Megan Hofmann. Their work appears in journals such as ACM Transactions on Graphics, Computer Graphics Forum, OpenBU (Boston University), International Conference on Machine Learning and arXiv (Cornell University).

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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