Sushant Sachdeva

1.2k total citations
32 papers, 307 citations indexed

About

Sushant Sachdeva is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Sushant Sachdeva has authored 32 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Theory and Mathematics, 15 papers in Artificial Intelligence and 9 papers in Statistics and Probability. Recurrent topics in Sushant Sachdeva's work include Complexity and Algorithms in Graphs (14 papers), Advanced Graph Theory Research (6 papers) and Markov Chains and Monte Carlo Methods (6 papers). Sushant Sachdeva is often cited by papers focused on Complexity and Algorithms in Graphs (14 papers), Advanced Graph Theory Research (6 papers) and Markov Chains and Monte Carlo Methods (6 papers). Sushant Sachdeva collaborates with scholars based in United States, Canada and Switzerland. Sushant Sachdeva's co-authors include Nisheeth K. Vishnoi, Rasmus Kyng, Richard Peng, Maximilian Probst Gutenberg, Lorenzo Orecchia, Yang P. Liu, Sanjeev Arora, Li Chen, Daniel A. Spielman and Anup Rao and has published in prestigious journals such as Communications of the ACM, Journal of the ACM and SIAM Journal on Computing.

In The Last Decade

Sushant Sachdeva

29 papers receiving 284 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sushant Sachdeva United States 10 154 132 63 36 33 32 307
Hariharan Narayanan United States 11 163 1.1× 126 1.0× 69 1.1× 27 0.8× 22 0.7× 42 443
Aravindan Vijayaraghavan United States 8 182 1.2× 140 1.1× 82 1.3× 29 0.8× 34 1.0× 28 340
Rasmus Kyng United States 8 122 0.8× 79 0.6× 55 0.9× 25 0.7× 20 0.6× 17 217
Nati Linial Israel 11 216 1.4× 169 1.3× 52 0.8× 7 0.2× 22 0.7× 35 353
Christine Rüb Germany 6 124 0.8× 158 1.2× 158 2.5× 24 0.7× 16 0.5× 12 384
Paweł Hitczenko United States 14 61 0.4× 87 0.7× 45 0.7× 59 1.6× 45 1.4× 59 568
Gianna M. Del Corso Italy 11 142 0.9× 175 1.3× 48 0.8× 91 2.5× 10 0.3× 42 411
Tobias Müller Netherlands 10 175 1.1× 36 0.3× 48 0.8× 33 0.9× 10 0.3× 59 361
Ali Çivril Türkiye 5 51 0.3× 66 0.5× 31 0.5× 23 0.6× 81 2.5× 6 239
Caterina De Simone Italy 10 231 1.5× 57 0.4× 49 0.8× 47 1.3× 15 0.5× 26 390

Countries citing papers authored by Sushant Sachdeva

Since Specialization
Citations

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

Fields of papers citing papers by Sushant Sachdeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sushant Sachdeva

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

All Works

20 of 20 papers shown
1.
Kyng, Rasmus, et al.. (2025). Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. Journal of the ACM. 72(3). 1–103.
2.
Brand, Jan van den, Li Chen, Rasmus Kyng, et al.. (2023). A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow. 503–514. 11 indexed citations
3.
Chen, Li, Rasmus Kyng, Yang P. Liu, et al.. (2022). Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. 612–623. 59 indexed citations
4.
Bullins, Brian, et al.. (2021). Almost-Linear-Time Weighted 𝓁 p -Norm Solvers in Slightly Dense Graphs via Sparsification.. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 198. 15. 2 indexed citations
5.
Bao, Xuchan, James Lucas, Sushant Sachdeva, & Roger Grosse. (2020). Regularized linear autoencoders recover the principal components, eventually. Neural Information Processing Systems. 33. 6971–6981. 1 indexed citations
6.
Peng, Richard, et al.. (2020). Faster Graph Embeddings via Coarsening. arXiv (Cornell University). 2 indexed citations
7.
Chu, Timothy, et al.. (2020). Graph Sparsification, Spectral Sketches, and Faster Resistance Computation via Short Cycle Decompositions. SIAM Journal on Computing. 52(6). FOCS18–85. 4 indexed citations
8.
Peng, Richard, et al.. (2019). Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. arXiv (Cornell University). 32. 14166–14177. 2 indexed citations
9.
Viswanathan, Krishnamurthy, et al.. (2019). Improved Semi-Supervised Learning with Multiple Graphs. International Conference on Artificial Intelligence and Statistics. 3032–3041. 1 indexed citations
10.
Panigrahy‎, Rina, Ali Rahimi, Sushant Sachdeva, & Qiuyi Zhang. (2018). Convergence Results for Neural Networks via Electrodynamics. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 2 indexed citations
11.
12.
Sachdeva, Sushant, et al.. (2016). An arithmetic analogue of Fox's triangle removal argument. 1–17. 1 indexed citations
13.
Kyng, Rasmus, Yin Tat Lee, Richard Peng, Sushant Sachdeva, & Daniel A. Spielman. (2016). Sparsified Cholesky and multigrid solvers for connection laplacians. 842–850. 34 indexed citations
14.
Kyng, Rasmus, Anup Rao, Sushant Sachdeva, & Daniel A. Spielman. (2015). Algorithms for Lipschitz Learning on Graphs. Conference on Learning Theory. 1190–1223. 7 indexed citations
15.
Arora, Sanjeev, Rong Ge, Ankur Moitra, & Sushant Sachdeva. (2015). Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders. Algorithmica. 72(1). 215–236. 15 indexed citations
16.
Kyng, Rasmus, Anup Rao, & Sushant Sachdeva. (2015). Fast, provable algorithms for Isotonic regression in all ℓ- p -norms. 28. 2719–2727. 9 indexed citations
17.
Sachdeva, Sushant & Nisheeth K. Vishnoi. (2014). Faster Algorithms via Approximation Theory. 9(2). 125–210. 27 indexed citations
18.
Filmus, Yuval, Hamed Hatami, Steven Heilman, et al.. (2014). Real Analysis in Computer Science: A collection of Open Problems. 3 indexed citations
19.
Guruswami, Venkatesan, Sushant Sachdeva, & Rishi Saket. (2013). Inapproximability of Minimum Vertex Cover on k-uniform k-partite Hypergraphs.. Electronic colloquium on computational complexity. 20. 71. 1 indexed citations
20.
Sachdeva, Sushant, et al.. (2009). On the Characterization and Selection of Diverse Conformational Ensembles with Applications to Flexible Docking. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(2). 487–498. 4 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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