Saransh Gupta

1.7k total citations
52 papers, 1.3k citations indexed

About

Saransh Gupta is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Saransh Gupta has authored 52 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Electrical and Electronic Engineering, 16 papers in Artificial Intelligence and 14 papers in Computer Networks and Communications. Recurrent topics in Saransh Gupta's work include Advanced Memory and Neural Computing (30 papers), Ferroelectric and Negative Capacitance Devices (29 papers) and Parallel Computing and Optimization Techniques (11 papers). Saransh Gupta is often cited by papers focused on Advanced Memory and Neural Computing (30 papers), Ferroelectric and Negative Capacitance Devices (29 papers) and Parallel Computing and Optimization Techniques (11 papers). Saransh Gupta collaborates with scholars based in United States, India and South Korea. Saransh Gupta's co-authors include Mohsen Imani, Tajana Rosing, Yeseong Kim, Nishil Talati, Shahar Kvatinsky, Pravin Mane, Tajana Rosing, Minxuan Zhou, Sahand Salamat and Behnam Khaleghi and has published in prestigious journals such as Gastroenterology, IEEE Transactions on Computers and Frontiers in Neuroscience.

In The Last Decade

Saransh Gupta

51 papers receiving 1.2k citations

Peers

Saransh Gupta

EEE

AI

HA

CNC

CMN

Peng Gu United States

Anirban Nag United States

Ping Chi United States

Linghao Song United States

Indranil Sengupta India

Ren-Shuo Liu Taiwan

Izzat El Hajj United States

Yeseong Kim United States

Dimin Niu United States

Tsung-Yung Jonathan Chang Taiwan

Peng Gu United States

Saransh Gupta

891 ×0.9

EEE

299 ×0.9

AI

323 ×1.2

HA

292 ×1.5

CNC

194 ×1.0

CMN

Citations per year, relative to Saransh Gupta Saransh Gupta (= 1×) peers Peng Gu

Countries citing papers authored by Saransh Gupta

Since Specialization

Citations

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

Fields of papers citing papers by Saransh Gupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saransh Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Saransh Gupta. A scholar is included among the top collaborators of Saransh Gupta 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 Saransh Gupta. Saransh Gupta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Zhou, Minxuan, et al.. (2025). FHEmem: A Processing In-Memory Accelerator for Fully Homomorphic Encryption. IEEE Transactions on Emerging Topics in Computing. 13(4). 1367–1382. 1 indexed citations

2.

Xu, Weihong, Saransh Gupta, Justin Morris, et al.. (2024). Tri-HD: Energy-Efficient On-Chip Learning With In-Memory Hyperdimensional Computing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(2). 525–539. 4 indexed citations

3.

Gupta, Saransh, Felipe Lisboa, Seth Schobel, et al.. (2023). ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports. BMC Medical Informatics and Decision Making. 23(1). 262–262. 3 indexed citations

4.

Nam, Yujin, Minxuan Zhou, Saransh Gupta, et al.. (2023). Efficient Machine Learning on Encrypted Data Using Hyperdimensional Computing. 1–6. 5 indexed citations

5.

Chen, Hanning, Yeseong Kim, Elaheh Sadredini, et al.. (2023). Sparsity Controllable Hyperdimensional Computing for Genome Sequence Matching Acceleration. 2. 1–6. 1 indexed citations

6.

Gupta, Saransh, et al.. (2022). COSMO: Computing with Stochastic Numbers in Memory. ACM Journal on Emerging Technologies in Computing Systems. 18(2). 1–25. 3 indexed citations

7.

Gupta, Saransh, et al.. (2022). MemFHE: End-to-end Computing with Fully Homomorphic Encryption in Memory. ACM Transactions on Embedded Computing Systems. 23(2). 1–23. 23 indexed citations

8.

Agarwal, Chirag, Saransh Gupta, Terri E. Weaver, et al.. (2022). Deep Learning Analyses of Brain MRI to Identify Sustained Attention Deficit in Treated Obstructive Sleep Apnea: A Pilot Study. Sleep and Vigilance. 6(1). 179–184. 6 indexed citations

9.

Morris, Justin, et al.. (2022). Stochastic-HD: Leveraging Stochastic Computing on the Hyper-Dimensional Computing Pipeline. Frontiers in Neuroscience. 16. 867192–867192. 1 indexed citations

10.

Bhasuran, Balu, Saransh Gupta, Narbe Mardirossian, et al.. (2022). Su1534: ACCURATE, ROBUST, AND SCALABLE ABSTRACTION OF MAYO ENDOSCOPIC SUBSCORES FROM COLONOSCOPY REPORTS. Gastroenterology. 162(7). S–617.

11.

Gupta, Saransh, et al.. (2020). CryptoPIM: In-Memory Acceleration for RLWE Lattice-based Cryptography. Design Automation Conference. 1 indexed citations

12.

Zhou, Minxuan, Mohsen Imani, Saransh Gupta, Yeseong Kim, & Tajana Rosing. (2019). GRAM. 591–596. 31 indexed citations

13.

Imani, Mohsen, Saransh Gupta, & Tajana Rosing. (2019). Digital-based processing in-memory. 38–40. 1 indexed citations

14.

Gupta, Saransh, et al.. (2019). UPIM: Unipolar Switching Logic for High Density Processing-in-Memory Applications. 255–258. 1 indexed citations

15.

Kim, Yeseong, et al.. (2019). MAPIM: Mat Parallelism for High Performance Processing in Non-volatile Memory Architecture. 145–150. 1 indexed citations

16.

Imani, Mohsen, Ricardo Garcı́a, Saransh Gupta, & Tajana Rosing. (2018). RMAC. 1–6. 33 indexed citations

17.

Imani, Mohsen, Saransh Gupta, & Tajana Rosing. (2018). GenPIM: Generalized processing in-memory to accelerate data intensive applications. 1155–1158. 10 indexed citations

18.

Imani, Mohsen, Saransh Gupta, & Tajana Rosing. (2017). Ultra-Efficient Processing In-Memory for Data Intensive Applications. 1–6. 69 indexed citations

19.

Imani, Mohsen, et al.. (2017). Efficient query processing in crossbar memory. 1–6. 21 indexed citations

20.

Talati, Nishil, Saransh Gupta, Pravin Mane, & Shahar Kvatinsky. (2016). Logic Design Within Memristive Memories Using Memristor-Aided loGIC (MAGIC). IEEE Transactions on Nanotechnology. 15(4). 635–650. 253 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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