Todd Phillips

16 papers receiving 1.1k citations

Todd Phillips's Hit Papers

Hidden technical debt in Machine learning systems 2015 · 457 citations
4570+4+8Years since publication100200300400500

Peers

Todd Phillips
Comparison fields: 5 of 109
  • Health Informatics 51
  • Information Systems 417
  • Artificial Intelligence 525
  • Management Science and Operations Research 185
  • Computer Graphics and Computer-Aided Design 49
Replace Dietmar Ebner with:
Dietmar Ebner Austria
Aditya Parameswaran United States
Zhiting Hu United States
Zhenjie Zhang China
Sebastian Schelter Netherlands
Quan Chen China
Nhien‐An Le‐Khac Ireland
Wee Keong Ng Singapore
Ammar Almomani Jordan
Neoklis Polyzotis United States
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Citations per year

Countries citing papers authored by Todd Phillips

Since Specialization
Citations

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

Fields of papers citing papers by Todd Phillips

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Todd Phillips, 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 Todd Phillips Line = papers co-authored together Todd Phillips links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
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Hit paper breakdown →
2013511
2
Hidden technical debt in Machine learning systems
Hit paper breakdown →
2015457
3
Machine Learning: The High Interest Credit Card of Technical Debt
2014126
4 200725
5 200421
6 202418
7 20099
8
Linear-Size Meshes
20088
9 20116
10 20093
11 20231
12 20241
13 20241
14
Efficient mesh generation for piecewise linear complexes
20091
15
The Centervertex Theorem for Wedge Depth
20091
16 20241
17 20230
18 20250
19 20180

About Todd Phillips

Todd Phillips is a scholar working on Computer Graphics and Computer-Aided Design, Computer Networks and Communications, Computational Mechanics, Surgery and Information Systems, having authored 19 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (9 papers), Computer Graphics and Visualization Techniques (3 papers), Knee injuries and reconstruction techniques (2 papers), Remote Sensing and LiDAR Applications (2 papers), Optimization and Search Problems (2 papers), Advanced Data Storage Technologies (2 papers), Optimization and Packing Problems (2 papers) and Scientific Computing and Data Management (2 papers). The work is most often cited by research in Health Informatics (51 citations), Information Systems (417 citations), Artificial Intelligence (525 citations), Management Science and Operations Research (185 citations) and Computer Graphics and Computer-Aided Design (49 citations). Todd Phillips has collaborated with scholars based in United States and France. Frequent co-authors include Eugene Davydov, Gary D. Holt, Daniel Golovin, D. Sculley, Michael Young, Dietmar Ebner, H. Brendan McMahan, Lan Nie, Sharat Chikkerur and Martin Wattenberg. Their work appears in journals such as Arthroscopy The Journal of Arthroscopic and Related Surgery, Journal of Pediatric Orthopaedics, Journal of Shoulder and Elbow Surgery, Knee Surgery Sports Traumatology Arthroscopy and JAAOS Global Research and Reviews.

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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