Hardik Sharma
- Electrical and Electronic Engineering top 10%
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Hardware and Architecture top 2%
- Computer Networks and Communications top 10%
- Co-authors
- Hadi EsmaeilzadehJongse ParkJoon Kyung KimDivya MahajanEmmanuel AmaroVikas ChandraLiangzhen LaiNaveen Suda
- Topics
- Parallel Computing and Optimization Techniques (5 papers)Advanced Memory and Neural Computing (5 papers)Advanced Neural Network Applications (4 papers)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Hardik Sharma
12 papers receiving 898 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Electrical and Electronic Engineering 518
- Computer Vision and Pattern Recognition 493
- Artificial Intelligence 362
- Hardware and Architecture 280
- Computer Networks and Communications 139
Countries citing papers authored by Hardik Sharma
This map shows the geographic impact of Hardik Sharma'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 Hardik Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hardik Sharma more than expected).
Fields of papers citing papers by Hardik Sharma
This network shows the impact of papers produced by Hardik Sharma. 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 Hardik Sharma. The network helps show where Hardik Sharma may publish in the future.
Co-authorship network of co-authors of Hardik Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Hardik Sharma. A scholar is included among the top collaborators of Hardik Sharma 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 Hardik Sharma. Hardik Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 4 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 66 | |
| 6 | Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networkbreakdown → | 344 |
| 7 | 28 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 115 | |
| 12 | From high-level deep neural models to FPGAsbreakdown → | 273 |
| 13 | 75 |
About Hardik Sharma
Hardik Sharma is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Statistics, Probability and Uncertainty, having authored 13 papers that have together received 918 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (5 papers), Advanced Memory and Neural Computing (5 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Hardware and Architecture (280 citations), Computational Mathematics (19 citations) and Computer Vision and Pattern Recognition (493 citations). Hardik Sharma has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Hadi Esmaeilzadeh, Jongse Park, Joon Kyung Kim, Divya Mahajan, Emmanuel Amaro, Vikas Chandra, Liangzhen Lai, Naveen Suda, Asit Mishra and Amir Yazdanbakhsh. Their work appears in journals such as Fusion Engineering and Design and Materials Today Proceedings.
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.