Mikhail Khodak

49 total papers · 5.2k total citations
10 papers, 232 citations indexed

About

Mikhail Khodak is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Mikhail Khodak has authored 10 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Signal Processing. Recurrent topics in Mikhail Khodak's work include Topic Modeling (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Natural Language Processing Techniques (2 papers). Mikhail Khodak is often cited by papers focused on Topic Modeling (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Natural Language Processing Techniques (2 papers). Mikhail Khodak collaborates with scholars based in United States, Russia and United Kingdom. Mikhail Khodak's co-authors include Nikunj Saunshi, Sanjeev Arora, Orestis Plevrakis, Kiran Vodrahalli, Carlee Joe‐Wong, Liang Zheng, Mung Chiang, Andrew Lan, Andrej Risteski and Maria-Florina Balcan and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and International Conference on Learning Representations.

In The Last Decade

Mikhail Khodak

9 papers receiving 217 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mikhail Khodak 158 62 32 17 11 10 232
H. Niewiadomski 98 0.6× 27 0.4× 20 0.6× 12 0.7× 11 1.0× 7 170
A. Sutherland 135 0.9× 42 0.7× 33 1.0× 9 0.5× 13 1.2× 11 242
S. Inkinen 53 0.3× 68 1.1× 25 0.8× 11 0.6× 5 0.5× 8 200
Jack D. Hidary 170 1.1× 29 0.5× 49 1.5× 19 1.1× 3 0.3× 9 242
Aaron Adcock 100 0.6× 88 1.4× 12 0.4× 23 1.4× 2 0.2× 10 243
Ori Ram 230 1.5× 71 1.1× 30 0.9× 11 0.6× 1 0.1× 7 307
Lukas Gianinazzi 126 0.8× 49 0.8× 27 0.8× 28 1.6× 11 207
Jessica Zosa Forde 63 0.4× 17 0.3× 40 1.3× 31 1.8× 5 0.5× 14 228
Hao Wang 282 1.8× 47 0.8× 42 1.3× 19 1.1× 17 329
Liangbo Ning 115 0.7× 32 0.5× 36 1.1× 21 1.2× 12 237

Countries citing papers authored by Mikhail Khodak

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Khodak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikhail Khodak

This figure shows the co-authorship network connecting the top 25 collaborators of Mikhail Khodak. A scholar is included among the top collaborators of Mikhail Khodak 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 Mikhail Khodak. Mikhail Khodak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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