Daniel Rothchild

659 citations
4 papers · 219 · 1 hit paper · h-index 3

Impact in

Papers in

Daniel Rothchild

4 papers receiving 214 citations

Daniel Rothchild's Hit Papers

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink 2022 · 181 citations
1810+1+2Years since publication50100150

Peers

Daniel Rothchild
Comparison fields: 5 of 65
  • Health Informatics 7
  • Instrumentation 12
  • Computer Science Applications 12
  • Astronomy and Astrophysics 35
  • Safety Research 16
Replace Miguel Cárdenas‐Montes with:
Miguel Cárdenas‐Montes Spain
Jaime Sevilla Spain
Daria Stepanova Germany
Lennart Heim Canada
Sergiy Pereverzyev Austria
Michael W. Evans United States
Zhipeng Wang China
Jiaxin Huang China
Martin Homola Slovakia
Thierry Louge France
Daniel Rothchild relative to Miguel Cárdenas‐Montes Spain Miguel Cárdenas‐Montes's profile →
Citations per field
00.5×10×15×22×
Miguel Cárdenas‐Montes · 1×
Citations per year

Countries citing papers authored by Daniel Rothchild

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Rothchild

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Daniel Rothchild, 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 Daniel Rothchild Line = papers co-authored together Daniel Rothchild links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Daniel Rothchild

Daniel Rothchild is a scholar working on Astronomy and Astrophysics, Atomic and Molecular Physics, and Optics, Instrumentation, Molecular Biology and Artificial Intelligence, having authored 4 papers that have together received 219 indexed citations. Recurring topics across this work include Stellar, planetary, and galactic studies (2 papers), Astronomy and Astrophysical Research (2 papers), Adaptive optics and wavefront sensing (1 paper), Machine Learning in Materials Science (1 paper), Gamma-ray bursts and supernovae (1 paper), Advanced Chemical Physics Studies (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Protein Structure and Dynamics (1 paper). The work is most often cited by research in Health Informatics (7 citations), Instrumentation (12 citations), Computer Science Applications (12 citations), Astronomy and Astrophysics (35 citations) and Safety Research (16 citations). Daniel Rothchild has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include David R. So, Jeff Dean, Joseph E. Gonzalez, Lluís-Miquel Munguía, Maud Texier, David S. Patterson, Liang Chen, Urs Hölzle, Quoc V. Le and S. Huber. Their work appears in journals such as Computer, Publications of the Astronomical Society of the Pacific, Chemical Science and Springer Link (Chiba Institute of Technology).

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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