Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Robust Deep Learning Methods for Anomaly Detection
2020321 citationsNguyen Lu Dang Khoa, Sanjay Chawla et al.profile →
Interpretable scientific discovery with symbolic regression: a review
This map shows the geographic impact of Sanjay Chawla'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 Sanjay Chawla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanjay Chawla more than expected).
This network shows the impact of papers produced by Sanjay Chawla. 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 Sanjay Chawla. The network helps show where Sanjay Chawla may publish in the future.
Co-authorship network of co-authors of Sanjay Chawla
This figure shows the co-authorship network connecting the top 25 collaborators of Sanjay Chawla.
A scholar is included among the top collaborators of Sanjay Chawla 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 Sanjay Chawla. Sanjay Chawla is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cucuringu, Mihai, Ioannis Koutis, Sanjay Chawla, Gary L. Miller, & Richard Peng. (2016). Simple and Scalable Constrained Clustering: a Generalized Spectral Method. Oxford University Research Archive (ORA) (University of Oxford). 445–454.16 indexed citations
Menon, Aditya Krishna, Harikrishna Narasimhan, Shivani Agarwal, & Sanjay Chawla. (2013). On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. International Conference on Machine Learning. 603–611.33 indexed citations
12.
Chawla, Sanjay, et al.. (2010). On Bayesian Network and Outlier Detection.. 125.5 indexed citations
13.
Chawla, Sanjay, et al.. (2008). Disk-Based Sampling for Outlier Detection in High Dimensional Data. 40–50.
14.
Chawla, Sanjay. (2007). A minmax problem for parabolic systems with competitive interactions. SHILAP Revista de lepidopterología.1 indexed citations
15.
Verhein, Florian & Sanjay Chawla. (2006). Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases.2 indexed citations
Chawla, Sanjay, Shashi Shekhar, & Weili Wu. (2000). Predicting Locations Using Map Similarity (PLUMS): a framework for spatial data mining. 14–24.6 indexed citations
19.
Chawla, Sanjay, et al.. (2000). Extending Data Mining for Spatial Applications: A Case Study in Predicting Nest Locations. University of Minnesota Digital Conservancy (University of Minnesota). 70–77.5 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.