Pritish Narayanan

7.7k citations

87 papers · 4.6k indexed · 4 hit papers · h-index 24

Impact in

Electrical and Electronic Engineering top 0.5%
- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
Cellular and Molecular Neuroscience top 2%
- Neuroscience and Neural Engineering

Papers in

Electrical and Electronic Engineering 83
- Advanced Memory and Neural Computing 55
- Ferroelectric and Negative Capacitance Devices 44
- Semiconductor materials and devices 34
- Advancements in Semiconductor Devices and Circuit Design 29
Artificial Intelligence 24
- Neural Networks and Reservoir Computing 14
- Machine Learning and ELM 5

Co-authors: Geoffrey W. Burr R. M. Shelby Severin Sidler Irem Boybat Kumar Virwani Hyunsang Hwang Carmelo di Nolfo B. N. Kurdi
Journals: IEEE Transactions on Electron Devices (4 papers)Nature Communications (3 papers)IEEE Journal of the Electron Devices Society (3 papers)IEEE Transactions on Nanotechnology (3 papers)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2 papers)
Partner nations: United States Switzerland South Korea

In The Last Decade

Pritish Narayanan

85 papers receiving 4.5k citations

Hit Papers

align trajectories log scale

Equivalent-accuracy accelerated neural-network training using analogue memory 2018 · 770 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2018 Nature
2016 Advances in Physics X
2015 IEEE Transactions on Electron Devices
2015 International Conference on Machine Learning

Peers

Countries citing papers authored by Pritish Narayanan

Since Specialization

Citations

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

Fields of papers citing papers by Pritish Narayanan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pritish Narayanan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pritish Narayanan Line = papers co-authored together Pritish Narayanan links everyone, so they are left out of the graph.

All Works

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

20 of 20 papers shown

#	Work
1	Demonstration of transformer-based ALBERT model on a 14nm analog AI inference chip Nature Communications ·Lynnee Roane, Stefano Ambrogio, Pritish Narayanan, Nogayev Adilbek, Charles Mackin, Andrea Fasoli, Malte J. Rasch, Alexander Friz, Heike E. Weber, Takeo Yasuda, Masatoshi Ishii, David D. McKiernan, Kohji Hosokawa, Ewa Alicja Ogłodek, Seiji Munetoh, Vijay Narayanan, Hsinyu Tsai, Geoffrey W. Burr	2025	1
2	Fabrication of cyclen-iodine decorated 2D nanosheets of GO: Multi-functional platforms for sensitive fluorescent detection of Pb2+ ions Diamond and Related Materials ·Pugalenthi Ramesh, Luigi L. Palese, Pritish Narayanan, Madhappan Santhamoorthy, Prabhakarn Arunachalam, Sandhanasamy Devanesan	2025	0
3	(Invited) Emerging Nonvolatile Memories for Analog Neuromorphic Computing ECS Meeting Abstracts ·An Chen, Stefano Ambrogio, Pritish Narayanan, Nogayev Adilbek, Hsinyu Tsai, Kohji Hosokawa, Charles Mackin, Akiyo Nomura, Alexander Friz, Andrea Fasoli, Heike E. Weber, Geoffrey W. Burr	2024	1
4	Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators Nature Communications ·Malte J. Rasch, Charles Mackin, Manuel Le Gallo, Lynnee Roane, Andrea Fasoli, 修山手, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan	2023	77
5	A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh IEEE Transactions on Very Large Scale Integration (VLSI) Systems ·Shubham Jain, Hsinyu Tsai, Jivansh Ashpalia, R. Muralidhar, Irem Boybat, Martin M. Frank, Stanisław Woźniak, Miloš Stanisavljević, Praneet Adusumilli, Pritish Narayanan, Kohji Hosokawa, Masatoshi Ishii, Josette André, Vijay Narayanan, Geoffrey W. Burr	2022	28
6	Optimised weight programming for analogue memory-based deep neural networks Nature Communications ·Charles Mackin, Malte J. Rasch, An Chen, K. Gudkova, Robert L. Bruce, Ning Li, Pritish Narayanan, Stefano Ambrogio, Manuel Le Gallo, S. R. Nandakumar, Andrea Fasoli, Heike E. Weber, Alexander Friz, Abu Sebastian, Hsinyu Tsai, Geoffrey W. Burr	2022	34
7	Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices Frontiers in Computational Neuroscience ·Martin Wyss, Hsinyu Tsai, An Chen, Malte J. Rasch, Stefano Ambrogio, Charles Mackin, Andrea Fasoli, Alexander Friz, Pritish Narayanan, Miloš Stanisavljević, Geoffrey W. Burr	2021	16
8	Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges Charles Mackin, Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, Martin Wyss, Andrea Fasoli, An Chen, Alexander Friz, R. M. Shelby, Geoffrey W. Burr	2020	4
9	Accelerating Deep Neural Networks with Analog Memory Devices Bulletin of the American Physical Society ·Charles Mackin, Pritish Narayanan, Hsinyu Tsai, Stefano Ambrogio, Chuanhao Sun, Geoffrey W. Burr	2019	1
10	AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed IBM Journal of Research and Development ·M. B. Hoffman, Pritish Narayanan, Daniel G. Tobin, H. Mebarki, Kohji Hosokawa, Charles Mackin, Hsinyu Tsai, Stefano Ambrogio, A. Chen, Geoffrey W. Burr	2019	39
11	Deep Learning with Limited Numerical Precision International Conference on Machine Learning ·Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan Hit paper breakdown →	2015	435
12	On the Origin of Steep $I$ –$V$ Nonlinearity in Mixed-Ionic-Electronic-Conduction-Based Access Devices IEEE Transactions on Electron Devices ·Alvaro Padilla, Geoffrey W. Burr, Rohit S. Shenoy, Karthik V. Raman, Donald S. Bethune, R. M. Shelby, Charles Rettner, 崔治中, Kumar Virwani, Pritish Narayanan, Martin Joseph Mistretta, R. K. Pandey, Mohit Bajaj, K. V. R. M. Murali, B. N. Kurdi, Kailash Gopalakrishnan	2015	7
13	Exploring the Design Space for Crossbar Arrays Built With Mixed-Ionic-Electronic-Conduction (MIEC) Access Devices IEEE Journal of the Electron Devices Society ·Pritish Narayanan, Geoffrey W. Burr, Rohit S. Shenoy, Gaynard Smith, Kumar Virwani, Alvaro Padilla, B. N. Kurdi, Kailash Gopalakrishnan	2015	22
14	(Invited) Large Crossbar Arrays for Storage Class Memory and Non-Von Neumann Computing ECS Meeting Abstracts ·Kumar Virwani, Geoffrey W. Burr, R. M. Shelby, Pritish Narayanan	2015	1
15	Circuit-level benchmarking of access devices for resistive nonvolatile memory arrays Pritish Narayanan, Geoffrey W. Burr, Rohit S. Shenoy, Kumar Virwani, B. N. Kurdi	2014	9
16	Integrated Device–Fabric Explorations and Noise Mitigation in Nanoscale Fabrics IEEE Transactions on Nanotechnology ·Pritish Narayanan, Yuwei Liao, Carmen Mata Barreiro, Chi On Chui, Csaba Andras Moritz	2012	11
17	Parameter Variability in Nanoscale Fabrics: Bottom-Up Integrated Exploration Pritish Narayanan, Jairo Restrepo Galeano, Yuwei Liao, Hiroshi Sugitani, Carmen Mata Barreiro, Chi On Chui, Csaba Andras Moritz	2010	9
18	Impact of process variation on NASIC nanoprocessors with 2-way redundancy Jairo Restrepo Galeano, Pritish Narayanan, Teng Wang, Csaba Andras Moritz	2009	2
19	Combining 2-level logic families in grid-based nanoscale fabrics Scholarworks (University of Massachusetts Amherst) ·Yujia Yang, Pritish Narayanan, Csaba Andras Moritz	2007	14
20	Fault-Tolerant Nanoscale Processors on Semiconductor Nanowire Grids IEEE Transactions on Circuits and Systems I Regular Papers ·Csaba Andras Moritz, Teng Wang, Pritish Narayanan, Jairo Restrepo Galeano, Yao Guo, Catherine Dezan, Jerome Peter Mkiramweni	2007	52

About Pritish Narayanan

Pritish Narayanan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Biomedical Engineering, Materials Chemistry and Computational Theory and Mathematics, having authored 87 papers that have together received 4.6k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (55 papers), Ferroelectric and Negative Capacitance Devices (44 papers), Semiconductor materials and devices (34 papers), Advancements in Semiconductor Devices and Circuit Design (29 papers), Nanowire Synthesis and Applications (18 papers), Neural Networks and Reservoir Computing (14 papers), Machine Learning in Materials Science (6 papers) and Machine Learning and ELM (5 papers). The work is most often cited by research in Electrical and Electronic Engineering (4.2k citations), Cellular and Molecular Neuroscience (1.0k citations), Artificial Intelligence (1.1k citations), Polymers and Plastics (443 citations) and Cognitive Neuroscience (482 citations). Pritish Narayanan has collaborated with scholars based in United States, Switzerland and South Korea. Frequent co-authors include Geoffrey W. Burr, R. M. Shelby, Severin Sidler, Irem Boybat, Kumar Virwani, Hyunsang Hwang, Carmelo di Nolfo, B. N. Kurdi, Hsinyu Tsai and Rohit S. Shenoy. Their work appears in journals such as IEEE Transactions on Electron Devices, Nature Communications, IEEE Journal of the Electron Devices Society, IEEE Transactions on Nanotechnology and IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

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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