Ashish Sanil

6.0k total citations
33 papers, 981 citations indexed

About

Ashish Sanil is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Ashish Sanil has authored 33 papers receiving a total of 981 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Management Science and Operations Research and 7 papers in Computer Networks and Communications. Recurrent topics in Ashish Sanil's work include Privacy-Preserving Technologies in Data (7 papers), Data Quality and Management (5 papers) and PARP inhibition in cancer therapy (5 papers). Ashish Sanil is often cited by papers focused on Privacy-Preserving Technologies in Data (7 papers), Data Quality and Management (5 papers) and PARP inhibition in cancer therapy (5 papers). Ashish Sanil collaborates with scholars based in United States and Germany. Ashish Sanil's co-authors include Alan F. Karr, Jerome P. Reiter, Xiaodong Lin, David Banks, Anna Oganian, Adam Porter, Adrian Dobra, Alessandro Orso, Murali Haran and X. Sheldon Lin and has published in prestigious journals such as Journal of Clinical Oncology, Journal of the American Statistical Association and Cancer Research.

In The Last Decade

Ashish Sanil

32 papers receiving 891 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashish Sanil United States 18 444 199 160 155 110 33 981
William E. Winkler United States 12 839 1.9× 151 0.8× 831 5.2× 468 3.0× 201 1.8× 32 1.7k
Roberta Siciliano Italy 15 175 0.4× 58 0.3× 110 0.7× 60 0.4× 18 0.2× 49 523
Ciamac C. Moallemi United States 20 155 0.3× 67 0.3× 338 2.1× 286 1.8× 317 2.9× 59 1.4k
Alan Weiss United States 24 137 0.3× 237 1.2× 406 2.5× 59 0.4× 933 8.5× 84 2.1k
André Freitas United Kingdom 15 583 1.3× 11 0.1× 150 0.9× 110 0.7× 41 0.4× 104 925
John Fox United Kingdom 19 623 1.4× 11 0.1× 49 0.3× 80 0.5× 54 0.5× 56 1.2k
Annette ten Teije Netherlands 19 740 1.7× 7 0.0× 106 0.7× 204 1.3× 152 1.4× 81 1.1k
Daniel Teichroew United States 16 115 0.3× 104 0.5× 115 0.7× 79 0.5× 75 0.7× 42 913
Christopher P. Chambers United States 18 135 0.3× 23 0.1× 277 1.7× 51 0.3× 32 0.3× 90 907
Thuc Duy Le Australia 23 383 0.9× 110 0.6× 78 0.5× 104 0.7× 25 0.2× 91 2.3k

Countries citing papers authored by Ashish Sanil

Since Specialization
Citations

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

Fields of papers citing papers by Ashish Sanil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashish Sanil

This figure shows the co-authorship network connecting the top 25 collaborators of Ashish Sanil. A scholar is included among the top collaborators of Ashish Sanil 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 Ashish Sanil. Ashish Sanil 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.
Yau, Christina, Denise M. Wolf, Lamorna Brown Swigart, et al.. (2018). Abstract PD6-14: Analysis of DNA repair deficiency biomarkers as predictors of response to the PD1 inhibitor pembrolizumab: Results from the neoadjuvant I-SPY 2 trial for stage II-III high-risk breast cancer. Cancer Research. 78(4_Supplement). PD6–14. 6 indexed citations
2.
3.
Wolf, Denise M., Christina Yau, Ashish Sanil, et al.. (2016). Abstract 858: Combining sensitivity markers to identify triple-negative breast cancer patients most responsive to veliparib/carboplatin: results from the I-SPY 2 TRIAL. Cancer Research. 76(14_Supplement). 858–858. 2 indexed citations
4.
Leyland‐Jones, Brian, Marco Paoloni, Laura van ‘t Veer, et al.. (2016). Abstract P1-14-03: The evaluation of trebananib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 TRIAL. Cancer Research. 76(4_Supplement). P1–14.
5.
Veer, Laura van’t, Laura Esserman, Ashish Sanil, et al.. (2015). DNA repair deficiency biomarkers and identification of ER-positive breast cancer patients who may benefit from veliparib/carboplatin: Results from the I-SPY 2 trial.. Journal of Clinical Oncology. 1 indexed citations
6.
Rugo, HS, O. Olopade, Angela DeMichele, et al.. (2013). Abstract S5-02: Veliparib/carboplatin plus standard neoadjuvant therapy for high-risk breast cancer: First efficacy results from the I-SPY 2 TRIAL. Cancer Research. 73(24_Supplement). S5–2. 48 indexed citations
7.
Eley, Timothy, Feng Luo, Shruti Agrawal, et al.. (2009). Phase I Study of the Effect of Gastric Acid pH Modulators on the Bioavailability of Oral Dasatinib in Healthy Subjects. The Journal of Clinical Pharmacology. 49(6). 700–709. 85 indexed citations
8.
Haran, Murali, et al.. (2007). Techniques for Classifying Executions of Deployed Software to Support Software Engineering Tasks. IEEE Transactions on Software Engineering. 33(5). 287–304. 37 indexed citations
9.
Karr, Alan F., et al.. (2005). Data swapping as a decision problem. Journal of Official Statistics. 21(4). 635–655. 24 indexed citations
10.
Karr, Alan F., Jun Feng, Xiaodong Lin, et al.. (2005). Secure analysis of distributed chemical databases without data integration. Journal of Computer-Aided Molecular Design. 19(9-10). 739–747. 16 indexed citations
11.
Karr, Alan F., Xiaodong Lin, Ashish Sanil, & Jerome P. Reiter. (2005). Secure Regression on Distributed Databases. Journal of Computational and Graphical Statistics. 14(2). 263–279. 85 indexed citations
12.
Haran, Murali, Alan F. Karr, Alessandro Orso, Adam Porter, & Ashish Sanil. (2005). Applying classification techniques to remotely-collected program execution data. ACM SIGSOFT Software Engineering Notes. 30(5). 146–155. 17 indexed citations
13.
Haran, Murali, Alan F. Karr, Alessandro Orso, Adam Porter, & Ashish Sanil. (2005). Applying classification techniques to remotely-collected program execution data. 146–155. 43 indexed citations
14.
Karr, Alan F., Xiaodong Lin, Ashish Sanil, & Jerome P. Reiter. (2004). Regression on distributed databases via secure multi-party computation. International Conference on Digital Government Research. 108. 4 indexed citations
15.
Sanil, Ashish, Alan F. Karr, Xiaodong Lin, & Jerome P. Reiter. (2004). Privacy preserving regression modelling via distributed computation. 677–682. 86 indexed citations
16.
Karr, Alan F., Xiaodong Lin, Ashish Sanil, & Jerome P. Reiter. (2004). Analysis of Integrated Data without Data Integration. CHANCE. 17(3). 26–29. 15 indexed citations
17.
Karr, Alan F., et al.. (2003). Data swapping: a risk-utility framework and web service implementation. International Conference on Digital Government Research. 1–4. 5 indexed citations
18.
Dobra, Adrian, Alan F. Karr, & Ashish Sanil. (2003). Preserving confidentiality of high-dimensional tabulated data: Statistical and computational issues. Statistics and Computing. 13(4). 363–370. 23 indexed citations
19.
Sanil, Ashish. (2003). Principles of Data Mining. Journal of the American Statistical Association. 98(461). 252–253. 27 indexed citations
20.
Sanil, Ashish, David Banks, & Kathleen M. Carley. (1995). Models for evolving fixed node networks: Model fitting and model testing. Social Networks. 17(1). 65–81. 38 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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