Hardik Sharma

1.4k total citations · 2 hit papers
13 papers, 918 citations indexed

About

Hardik Sharma is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Electrical and Electronic Engineering. According to data from OpenAlex, Hardik Sharma has authored 13 papers receiving a total of 918 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 5 papers in Hardware and Architecture and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Hardik Sharma's work include Parallel Computing and Optimization Techniques (5 papers), Advanced Memory and Neural Computing (5 papers) and Advanced Neural Network Applications (4 papers). Hardik Sharma is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Advanced Memory and Neural Computing (5 papers) and Advanced Neural Network Applications (4 papers). Hardik Sharma collaborates with scholars based in United States, India and United Kingdom. Hardik Sharma's 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 and has published in prestigious journals such as Fusion Engineering and Design and Materials Today Proceedings.

In The Last Decade

Hardik Sharma

12 papers receiving 898 citations

Hit Papers

align trajectories

What are hit papers?

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.

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network

2018 344 citations Hardik Sharma, Jongse Park et al. profile →
From high-level deep neural models to FPGAs

2016 273 citations Hardik Sharma, Jongse Park et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hardik Sharma United States	6	518	493	362	280	139	13	918
Debbie Marr United States	12	483 0.9×	471 1.0×	350 1.0×	298 1.1×	191 1.4×	17	989
Tong Geng United States	18	339 0.7×	368 0.7×	398 1.1×	289 1.0×	213 1.5×	70	951
Naveen Suda United States	10	624 1.2×	686 1.4×	411 1.1×	191 0.7×	120 0.9×	15	1.1k
Jorge Albericio Canada	12	664 1.3×	677 1.4×	414 1.1×	433 1.5×	237 1.7×	20	1.2k
Patrick Judd Canada	10	674 1.3×	800 1.6×	480 1.3×	283 1.0×	106 0.8×	15	1.1k
Yuwei Hu United States	10	231 0.4×	463 0.9×	341 0.9×	342 1.2×	213 1.5×	12	858
Shengen Yan China	14	332 0.6×	495 1.0×	252 0.7×	371 1.3×	285 2.1×	32	946
Antonio Puglielli United States	7	633 1.2×	571 1.2×	349 1.0×	229 0.8×	123 0.9×	9	1.1k
Ananda Samajdar United States	12	549 1.1×	422 0.9×	287 0.8×	364 1.3×	212 1.5×	17	941

Countries citing papers authored by Hardik Sharma

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Oh, Changhun, et al.. (2024). DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics. 1246–1261. 5 indexed citations

2.

Xu, Hanyang, et al.. (2024). In-Storage Domain-Specific Acceleration for Serverless Computing. 530–548. 4 indexed citations

3.

Sharma, Hardik, et al.. (2021). Face Mask Detection: A Real-Time Android Application Based on Deep Learning Modeling. 106–112. 4 indexed citations

4.

Sharma, Hardik, et al.. (2021). Gauss Jordan method for balancing chemical equation for different materials. Materials Today Proceedings. 51. 451–454. 1 indexed citations

5.

Kim, Joon Kyung, Hardik Sharma, Mohammad Alian, et al.. (2020). Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks. 681–697. 66 indexed citations

6.

Sharma, Hardik, Jongse Park, Naveen Suda, et al.. (2018). Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. 764–775. 344 indexed citations breakdown →

7.

Park, Jongse, et al.. (2017). Scale-out acceleration for machine learning. 367–381. 28 indexed citations

8.

Sharma, Hardik, et al.. (2016). Development of a control system for compression and expansion cycles of critical valve for high vacuum systems. Fusion Engineering and Design. 112. 735–741. 1 indexed citations

9.

Mishra, Jyoti, et al.. (2016). Monitoring and data acquisition of the high speed hydrogen pellet in SPINS. Fusion Engineering and Design. 112. 757–760. 1 indexed citations

10.

Sarvey, Thomas E., et al.. (2016). The impact of 3D stacking on GPU-accelerated deep neural networks: An experimental study. 1–4. 1 indexed citations

11.

Mahajan, Divya, Jongse Park, Emmanuel Amaro, et al.. (2016). TABLA: A unified template-based framework for accelerating statistical machine learning. 14–26. 115 indexed citations

12.

Sharma, Hardik, Jongse Park, Divya Mahajan, et al.. (2016). From high-level deep neural models to FPGAs. 1–12. 273 indexed citations breakdown →

13.

Yazdanbakhsh, Amir, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, & Hadi Esmaeilzadeh. (2015). Neural acceleration for GPU throughput processors. 482–493. 75 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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