Parag Mhashilkar

510 total citations
20 papers, 298 citations indexed

About

Parag Mhashilkar is a scholar working on Computer Networks and Communications, Information Systems and Management and Hardware and Architecture. According to data from OpenAlex, Parag Mhashilkar has authored 20 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Networks and Communications, 13 papers in Information Systems and Management and 4 papers in Hardware and Architecture. Recurrent topics in Parag Mhashilkar's work include Distributed and Parallel Computing Systems (20 papers), Advanced Data Storage Technologies (17 papers) and Scientific Computing and Data Management (13 papers). Parag Mhashilkar is often cited by papers focused on Distributed and Parallel Computing Systems (20 papers), Advanced Data Storage Technologies (17 papers) and Scientific Computing and Data Management (13 papers). Parag Mhashilkar collaborates with scholars based in United States, Switzerland and Italy. Parag Mhashilkar's co-authors include B. Holzman, I. Sfiligoi, Frank Würthwein, D Bradley, Sanjay Padhi, Gabriele Garzoglio, Dave Dykstra, Hyunwoo Kim, I. Macneill and Ioan Raicu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and Journal of Physics Conference Series.

In The Last Decade

Parag Mhashilkar

18 papers receiving 288 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Parag Mhashilkar United States 4 144 73 43 42 28 20 298
D Bradley United States 6 176 1.2× 81 1.1× 59 1.4× 46 1.1× 40 1.4× 17 336
B. Holzman United States 8 192 1.3× 103 1.4× 62 1.4× 62 1.5× 44 1.6× 34 395
Sanjay Padhi United States 6 132 0.9× 66 0.9× 36 0.8× 122 2.9× 55 2.0× 15 399
G. N. Patrick United Kingdom 10 79 0.5× 43 0.6× 14 0.3× 256 6.1× 11 0.4× 21 399
Ikuo Miyoshi Japan 7 129 0.9× 4 0.1× 133 3.1× 27 0.6× 49 1.8× 9 266
Siniša Veseli United States 15 42 0.3× 34 0.5× 4 0.1× 429 10.2× 9 0.3× 42 555
C. Adams United States 6 21 0.1× 8 0.1× 25 0.6× 65 1.5× 4 0.1× 9 166
M. Dūma Italy 9 31 0.2× 17 0.2× 5 0.1× 145 3.5× 16 0.6× 48 279
Keiichiro Fukazawa Japan 12 109 0.8× 10 0.1× 91 2.1× 33 0.8× 50 1.8× 28 334
L. Moneta Switzerland 8 37 0.3× 5 0.1× 16 0.4× 152 3.6× 4 0.1× 43 215

Countries citing papers authored by Parag Mhashilkar

Since Specialization
Citations

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

Fields of papers citing papers by Parag Mhashilkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Parag Mhashilkar

This figure shows the co-authorship network connecting the top 25 collaborators of Parag Mhashilkar. A scholar is included among the top collaborators of Parag Mhashilkar 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 Parag Mhashilkar. Parag Mhashilkar 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.
Herner, K., P. F. Ding, Dave Dykstra, et al.. (2019). Advances and enhancements in the FabrIc for Frontier Experiments project at Fermilab. SHILAP Revista de lepidopterología. 214. 3059–3059. 1 indexed citations
2.
Hufnagel, D., B. Holzman, Parag Mhashilkar, et al.. (2019). HPC resource integration into CMS Computing via HEPCloud. SHILAP Revista de lepidopterología. 214. 3031–3031. 2 indexed citations
3.
Mhashilkar, Parag, W. Dagenhart, B. Holzman, et al.. (2018). Intelligently-Automated Facilities Expansion with the HEPCloud Decision Engine. 1. 352–353.
4.
Herner, K., Valerio Benedetto, P. F. Ding, et al.. (2017). Advances in Grid Computing for the Fabric for Frontier Experiments Project at Fermilab. Journal of Physics Conference Series. 898. 52026–52026. 2 indexed citations
5.
Herner, K., P. F. Ding, Dave Dykstra, et al.. (2017). The FIFE Project at Fermilab: Computing for Experiments. 176–176.
6.
Dykstra, Dave, Gabriele Garzoglio, K. Herner, et al.. (2015). Progress on the Fabric for Frontier Experiments Project at Fermilab. Journal of Physics Conference Series. 664(6). 62040–62040. 1 indexed citations
7.
Timm, S., Gabriele Garzoglio, Parag Mhashilkar, et al.. (2015). Cloud services for the Fermilab scientific stakeholders. Journal of Physics Conference Series. 664(2). 22039–22039. 3 indexed citations
8.
Sfiligoi, I., S. Belforte, K Larson, et al.. (2014). CMS experience of running glideinWMS in High Availability mode. Journal of Physics Conference Series. 513(3). 32086–32086. 1 indexed citations
9.
Garzoglio, Gabriele, et al.. (2014). Big Data Over a 100G Network at Fermilab. Journal of Physics Conference Series. 513(6). 62017–62017. 3 indexed citations
10.
Mhashilkar, Parag, et al.. (2014). Cloud Bursting with GlideinWMS: Means to satisfy ever increasing computing needs for Scientific Workflows. Journal of Physics Conference Series. 513(3). 32069–32069. 7 indexed citations
11.
Mhashilkar, Parag, et al.. (2013). Optimizing Large Data Transfers over 100Gbps Wide Area Networks. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1. 26–33. 6 indexed citations
12.
Dykstra, Dave, Gabriele Garzoglio, Hyunwoo Kim, & Parag Mhashilkar. (2012). Identifying Gaps in Grid Middleware on Fast Networks with the Advanced Networking Initiative. Journal of Physics Conference Series. 396(3). 32034–32034. 1 indexed citations
13.
Mhashilkar, Parag, Gabriele Garzoglio, B. Holzman, et al.. (2012). End-To-End Solution for Integrated Workload and Data Management Using Glidein WMS and Globus Online. University of North Texas Digital Library (University of North Texas). 1 indexed citations
14.
Mhashilkar, Parag, Zachary Miller, Rajkumar Kettimuthu, et al.. (2012). End-To-End Solution for Integrated Workload and Data Management using GlideinWMS and Globus Online. Journal of Physics Conference Series. 396(3). 32076–32076. 3 indexed citations
15.
Sfiligoi, I., et al.. (2011). Reducing the Human Cost of Grid Computing With glideinWMS. 217–221. 9 indexed citations
16.
Mhashilkar, Parag, et al.. (2010). ReSS: Resource Selection Service for National and Campus Grid Infrastructure. Journal of Physics Conference Series. 219(6). 62059–62059. 1 indexed citations
17.
Sfiligoi, I., D Bradley, B. Holzman, et al.. (2009). The Pilot Way to Grid Resources Using glideinWMS. CERN Bulletin. 428–432. 254 indexed citations
18.
Abbott, B., et al.. (2008). DZero data-intensive computing on the Open Science Grid. Journal of Physics Conference Series. 119(6). 62001–62001. 1 indexed citations
19.
Garzoglio, Gabriele, et al.. (2004). The SAM-Grid Fabric services. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 534(1-2). 33–37. 1 indexed citations
20.
Denis, R. St., et al.. (2004). Experience using grid tools for CDF physics. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 534(1-2). 38–41. 1 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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