Anirban Nag

2.3k total citations · 2 hit papers
6 papers, 1.7k citations indexed

About

Anirban Nag is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Anirban Nag has authored 6 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Electrical and Electronic Engineering, 2 papers in Computer Networks and Communications and 2 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Anirban Nag's work include Advanced Memory and Neural Computing (4 papers), Ferroelectric and Negative Capacitance Devices (3 papers) and Quantum-Dot Cellular Automata (2 papers). Anirban Nag is often cited by papers focused on Advanced Memory and Neural Computing (4 papers), Ferroelectric and Negative Capacitance Devices (3 papers) and Quantum-Dot Cellular Automata (2 papers). Anirban Nag collaborates with scholars based in United States, India and Sweden. Anirban Nag's co-authors include Rajeev Balasubramonian, Vivek Srikumar, Naveen Muralimanohar, Ali Shafiee, John Paul Strachan, Miao Hu, R. Stanley Williams, Bibhash Sen, Biplab K. Sikdar and Edouard Giacomin and has published in prestigious journals such as Journal of Computational Science and ACM SIGARCH Computer Architecture News.

In The Last Decade

Anirban Nag

6 papers receiving 1.6k citations

Hit Papers

align trajectories sort by overperformance

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.

ISAAC

2016 1.1k citations Ali Shafiee, Anirban Nag et al. ACM SIGARCH Computer Architecture News profile →
ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars

2016 483 citations Ali Shafiee, Anirban Nag et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anirban Nag United States	6	1.4k	464	414	261	187	6	1.7k
Linghao Song United States	17	1.3k 0.9×	569 1.2×	583 1.4×	327 1.3×	136 0.7×	40	1.7k
Ping Chi United States	12	1.3k 0.9×	366 0.8×	366 0.9×	357 1.4×	152 0.8×	23	1.6k
Zhezhi He United States	26	1.3k 0.9×	857 1.8×	531 1.3×	302 1.2×	88 0.5×	94	2.1k
Saransh Gupta United States	18	994 0.7×	317 0.7×	162 0.4×	265 1.0×	187 1.0×	52	1.3k
Priyanka Raina United States	14	1.3k 0.9×	401 0.9×	460 1.1×	400 1.5×	199 1.1×	64	1.8k
Win-San Khwa Taiwan	27	2.0k 1.4×	364 0.8×	242 0.6×	307 1.2×	219 1.2×	66	2.2k
Yu-Der Chih Taiwan	31	2.2k 1.5×	304 0.7×	205 0.5×	395 1.5×	242 1.3×	80	2.4k
Ren-Shuo Liu Taiwan	23	2.0k 1.4×	392 0.8×	251 0.6×	415 1.6×	292 1.6×	73	2.4k
Peng Gu United States	18	891 0.6×	299 0.6×	184 0.4×	323 1.2×	194 1.0×	49	1.2k
Lixue Xia China	26	1.8k 1.3×	520 1.1×	392 0.9×	134 0.5×	413 2.2×	43	2.0k

Countries citing papers authored by Anirban Nag

Since Specialization

Citations

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

Fields of papers citing papers by Anirban Nag

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anirban Nag

This figure shows the co-authorship network connecting the top 25 collaborators of Anirban Nag. A scholar is included among the top collaborators of Anirban Nag 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 Anirban Nag. Anirban Nag 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:

6 of 6 papers shown

1.

Nag, Anirban & Rajeev Balasubramonian. (2021). OrderLight: Lightweight Memory-Ordering Primitive for Efficient Fine-Grained PIM Computations. 298–310. 6 indexed citations

2.

Nag, Anirban, et al.. (2019). GenCache. 334–346. 34 indexed citations

3.

Shafiee, Ali, Anirban Nag, Naveen Muralimanohar, et al.. (2016). ISAAC. ACM SIGARCH Computer Architecture News. 44(3). 14–26. 1111 indexed citations breakdown →

4.

Shafiee, Ali, Anirban Nag, Naveen Muralimanohar, et al.. (2016). ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars. 14–26. 483 indexed citations breakdown →

5.

Sen, Bibhash, et al.. (2015). Towards the hierarchical design of multilayer QCA logic circuit. Journal of Computational Science. 11. 233–244. 34 indexed citations

6.

Sen, Bibhash, et al.. (2013). Multilayer design of QCA multiplexer. 3. 1–6. 10 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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