Aayush Ankit

1.8k citations

32 papers · 1.1k indexed · h-index 16

Hardware and Architecture top 5%
Electrical and Electronic Engineering top 5%
- Advanced Memory and Neural Computing 27
- Ferroelectric and Negative Capacitance Devices 19
- CCD and CMOS Imaging Sensors 8
- Semiconductor materials and devices 5
Artificial Intelligence top 5%
- Machine Learning and ELM 5
Computer Vision and Pattern Recognition top 5%
- Advanced Neural Network Applications 5
Cellular and Molecular Neuroscience top 10%
- Photoreceptor and optogenetics research 3
Cognitive Neuroscience
- Neural dynamics and brain function 7

Co-authors: Kaushik Roy Abhronil Sengupta Indranil Chakraborty Syed Shakib Sarwar Priyadarshini Panda Mustafa Ali Amogh Agrawal Dejan Milojičić
Cited by: Hardware and Architecture Electrical and Electronic Engineering Artificial Intelligence
Journals: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2 papers)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)Nature Machine Intelligence (1 paper)
Partner nations: United States Lebanon India

In The Last Decade

Aayush Ankit

32 papers receiving 1.0k citations

Peers

Countries citing papers authored by Aayush Ankit

Since Specialization

Citations

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

Fields of papers citing papers by Aayush Ankit

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Aayush Ankit, 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 Aayush Ankit Line = papers co-authored together Aayush Ankit links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	SAMBA: Sparsity Aware In-Memory Computing Based Machine Learning Accelerator IEEE Transactions on Computers ·Klaus Ehlers,Aayush Ankit,Ester Juni Ernita,Kaushik Roy	2023	10
2	Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware ACM Computing Surveys ·Nitin Rathi,Indranil Chakraborty,Adarsh Kumar Kosta,Abhronil Sengupta,Aayush Ankit,Priyadarshini Panda,Kaushik Roy	2022	106
3	NAX Proceedings of the 59th ACM/IEEE Design Automation Conference ·N. Rolland,Indranil Chakraborty,Aayush Ankit,Kaushik Roy	2022	13
4	Identifying Efficient Dataflows for Spiking Neural Networks T.C. Shende,Aayush Ankit,Kaushik Roy	2022	4
5	Mixed Precision Quantization for ReRAM-based DNN Inference Accelerators Sitao Huang,Aayush Ankit,Araz Meilin,Yuri Oliveira Feitosa,Sai Rahul Chalamalasetti,Izzat El Hajj,Klaus Ehlers,Jonathan Aguero,顾馨梅,Sergey Serebryakov,Emily Kearns,Can Li,Paolo Faraboschi,John Paul Strachan,Deming Chen,Kaushik Roy,Wen‐mei Hwu,Dejan Milojičić	2021	24
6	A 35.5-127.2 TOPS/W Dynamic Sparsity-Aware Reconfigurable-Precision Compute-in-Memory SRAM Macro for Machine Learning IEEE Solid-State Circuits Letters ·Mustafa Ali,Indranil Chakraborty,Michael Nyame Acquah,Amogh Agrawal,Aayush Ankit,Kaushik Roy	2021	21
7	In-Memory Computing in Emerging Memory Technologies for Machine Learning: An Overview Kaushik Roy,Indranil Chakraborty,Mustafa Ali,Aayush Ankit,Amogh Agrawal	2020	53
8	Constructing energy-efficient mixed-precision neural networks through principal component analysis for edge intelligence Nature Machine Intelligence ·Indranil Chakraborty,Sarah C. Kopa,陈小娥,Aayush Ankit,Kaushik Roy	2020	27
9	Energy-Efficient Target Recognition using ReRAM Crossbars for Enabling On-Device Intelligence Sourav Sanyal,Aayush Ankit,Craig M. Vineyard,Kaushik Roy	2020	2
10	Circuits and Architectures for In-Memory Computing-Based Machine Learning Accelerators IEEE Micro ·Aayush Ankit,Indranil Chakraborty,Amogh Agrawal,Mustafa Ali,Kaushik Roy	2020	27
11	PCA-driven Hybrid network design for enabling Intelligence at the Edge. arXiv (Cornell University) ·Indranil Chakraborty,Sarah C. Kopa,陈小娥,Aayush Ankit,Kaushik Roy	2019	2
12	Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning Hacene Ghanoriche,Aayush Ankit,Yuri Oliveira Feitosa,Sai Rahul Chalamalasetti,ArimotoS.,Izzat El Hajj,相良建至,Paolo Faraboschi,Martin Foltín,Sitao Huang,Wen‐mei Hwu,K. P. Sossou,D.F. Batista,Dejan Milojičić,法史徳田,P. Klymco,Fitzpatrick KL,Kaushik Roy,Araz Meilin,John Paul Strachan	2018	25
13	Energy-Efficient Neural Computing with Approximate Multipliers ACM Journal on Emerging Technologies in Computing Systems ·Syed Shakib Sarwar,Swagath Venkataramani,Aayush Ankit,Anand Raghunathan,Kaushik Roy	2018	49
14	Neuromorphic Computing Across the Stack: Devices, Circuits and Architectures Aayush Ankit,Abhronil Sengupta,Kaushik Roy	2018	5
15	An All-Memristor Deep Spiking Neural Network: A Step Towards Realizing the Low Power, Stochastic Brain. arXiv (Cornell University) ·María del Carmen Riu de Martín,Aayush Ankit,Abhronil Sengupta,Kaushik Roy	2017	4
16	TraNNsformer: Neural Network Transformation for memristive crossbar based neuromorphic system design arXiv (Cornell University) ·Aayush Ankit,Abhronil Sengupta,Kaushik Roy	2017	20
17	FALCON: Feature Driven Selective Classification for Energy-Efficient Image Recognition IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Priyadarshini Panda,Aayush Ankit,María del Carmen Riu de Martín,Kaushik Roy	2017	15
18	Cross-Layer Design Exploration for Energy-Quality Tradeoffs in Spiking and Non-Spiking Deep Artificial Neural Networks Bing Han,Aayush Ankit,Abhronil Sengupta,Kaushik Roy	2017	11
19	Novel hybrid hardware architecture for nuclei detection in skin histopathological images Aayush Ankit,Mrinal Mandal	2015	3
20	A cascade framework for unoccluded and occluded pedestrian detection The Royal Society of Chemistry’s Journals, Books and Databases (The Royal Society of Chemistry) ·Aayush Ankit,Zh. A. Bermukhambetov,Hyunchul Shin	2014	1

About Aayush Ankit

Aayush Ankit is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (27 papers), Ferroelectric and Negative Capacitance Devices (19 papers), CCD and CMOS Imaging Sensors (8 papers), Neural dynamics and brain function (7 papers), Machine Learning and ELM (5 papers), Semiconductor materials and devices (5 papers), Advanced Neural Network Applications (5 papers) and Photoreceptor and optogenetics research (3 papers). The work is most often cited by research in Hardware and Architecture (109 citations), Electrical and Electronic Engineering (839 citations), Artificial Intelligence (349 citations), Computer Vision and Pattern Recognition (203 citations) and Cellular and Molecular Neuroscience (137 citations). Aayush Ankit has collaborated with scholars based in United States, Lebanon and India. Frequent co-authors include Kaushik Roy, Abhronil Sengupta, Indranil Chakraborty, Syed Shakib Sarwar, Priyadarshini Panda, Mustafa Ali, Amogh Agrawal, Dejan Milojičić, John Paul Strachan and Paolo Faraboschi. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Nature Machine Intelligence, IEEE Micro and IEEE Access.

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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