John Reuben

586 citations

32 papers · 371 indexed · h-index 10

Impact in

Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Electrical and Electronic Engineering top 10%
- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
- Low-power high-performance VLSI design
- CCD and CMOS Imaging Sensors

Papers in ⓘ

Electrical and Electronic Engineering 31
- Advanced Memory and Neural Computing 20
- Ferroelectric and Negative Capacitance Devices 19
- Semiconductor materials and devices 12
- Low-power high-performance VLSI design 9
- VLSI and FPGA Design Techniques 4
- Advancements in PLL and VCO Technologies 4
Cellular and Molecular Neuroscience 6
- Neuroscience and Neural Engineering 6

Co-authors: Dietmar Fey (10 shared papers)Christian Wenger (2 shared papers)Vikramkumar Pudi (4 shared papers)Shahar Kvatinsky (1 shared paper)Harish M. Kittur (8 shared papers)Pierre‐Emmanuel Gaillardon (1 shared paper)Nishil Talati (1 shared paper)Nimrod Wald (1 shared paper)
Journals: IEEE Transactions on Circuits and Systems I Regular Papers (3 papers)Electronics (2 papers)IEEE Transactions on Nanotechnology (2 papers)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)Computers & Electrical Engineering (1 paper)
Partner nations: Germany India Israel

In The Last Decade

John Reuben

30 papers receiving 363 citations

Peers

Countries citing papers authored by John Reuben

Since Specialization

Citations

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

Fields of papers citing papers by John Reuben

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside John Reuben, 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 John Reuben Line = papers co-authored together John Reuben links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Memristive logic: A framework for evaluation and comparison John Reuben, Rotem Ben-Hur, Nimrod Wald, Nishil Talati, Ameer Haj Ali, Pierre‐Emmanuel Gaillardon, Shahar Kvatinsky	2017	63
2	A Modeling Methodology for Resistive RAM Based on Stanford-PKU Model With Extended Multilevel Capability IEEE Transactions on Nanotechnology ·John Reuben, Dietmar Fey, Christian Wenger	2019	54
3	Toward Reliable Compact Modeling of Multilevel 1T-1R RRAM Devices for Neuromorphic Systems Electronics ·Emilio Pérez-Bosch Quesada, Rocío Romero‐Zaliz, Eduardo Pérez, Mamathamba Kalishettyhalli Mahadevaiah, John Reuben, Markus Andreas Schubert, F. Jiménez-Molinos, J.B. Roldán, Christian Wenger	2021	35
4	Accelerated Addition in Resistive RAM Array Using Parallel-Friendly Majority Gates IEEE Transactions on Very Large Scale Integration (VLSI) Systems ·John Reuben, Stefan Pechmann	2021	33
5	Incorporating Variability of Resistive RAM in Circuit Simulations Using the Stanford–PKU Model IEEE Transactions on Nanotechnology ·John Reuben, Mehrdad Biglari, Dietmar Fey	2020	28
6	A Novel In-Memory Wallace Tree Multiplier Architecture Using Majority Logic IEEE Transactions on Circuits and Systems I Regular Papers ·Vijaya Lakshmi, John Reuben, Vikramkumar Pudi	2021	26
7	Rediscovering Majority Logic in the Post-CMOS Era: A Perspective from In-Memory Computing Journal of Low Power Electronics and Applications ·John Reuben	2020	22
8	Binary Addition in Resistance Switching Memory Array by Sensing Majority Micromachines ·John Reuben	2020	17
9	A Parallel-friendly Majority Gate to Accelerate In-memory Computation ERef Bayreuth (University of Bayreuth) ·John Reuben, Stefan Pechmann	2020	13
10	A Time-based Sensing Scheme for Multi-level Cell (MLC) Resistive RAM John Reuben, Dietmar Fey	2019	12
11	Direct state transfer in MLC based memristive ReRAM devices for ternary computing Dietmar Fey, John Reuben	2020	9
12	Low power, high speed hybrid clock divider circuit John Reuben, Zackriya. V Mohammed, Harish M. Kittur	2013	8
13	Design of In-Memory Parallel-Prefix Adders Journal of Low Power Electronics and Applications ·John Reuben	2021	8
14	Capacitance driven clock mesh synthesis to minimize skew and power dissipation IEICE Electronics Express ·John Reuben, V. Mohammed Zackriya, Salma Nashit, Harish M. Kittur	2013	5
15	A Low-Power Ternary Adder Using Ferroelectric Tunnel Junctions Electronics ·John Reuben, Dietmar Fey, Suzanne Lancaster, Stefan Slesazeck	2023	4
16	Clock frequency doubler circuit for multiple frequencies and its application in a CDN to reduce power John Reuben, Abishek Anuroop, Harish M. Kittur	2012	4
17	Minimal Buffer Insertion Based Low Power Clock Tree Synthesis for 3D Integrated Circuits Journal of Circuits Systems and Computers ·Kamineni Sumanth Kumar, John Reuben	2016	4
18	A novel clock generation algorithm for system-on-chip based on least common multiple Computers & Electrical Engineering ·John Reuben, Harish M. Kittur, Mohd Shoaib	2014	3
19	A low power dual modulus prescaler for fractional-N PLL synthesizer V. Mohammed Zackriya, John Reuben, Harish M. Kittur	2014	3
20	Communication Centric Floorplanning of NoC Based System on Chip Procedia Computer Science ·Jyothi Thomas John, Nikhil Dahare, B N Chaithanya, John Reuben	2016	3

About John Reuben

John Reuben is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Hardware and Architecture, Computer Networks and Communications and Computational Theory and Mathematics, having authored 32 papers that have together received 371 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (20 papers), Ferroelectric and Negative Capacitance Devices (19 papers), Semiconductor materials and devices (12 papers), Low-power high-performance VLSI design (9 papers), Neuroscience and Neural Engineering (6 papers), VLSI and FPGA Design Techniques (4 papers), Advancements in PLL and VCO Technologies (4 papers) and Parallel Computing and Optimization Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (50 citations), Electrical and Electronic Engineering (350 citations), Cellular and Molecular Neuroscience (102 citations), Computational Theory and Mathematics (25 citations) and Computer Networks and Communications (31 citations). John Reuben has collaborated with scholars based in Germany, India and Israel. Frequent co-authors include Dietmar Fey, Christian Wenger, Vikramkumar Pudi, Shahar Kvatinsky, Harish M. Kittur, Pierre‐Emmanuel Gaillardon, Nishil Talati, Nimrod Wald, Rotem Ben-Hur and Rocío Romero‐Zaliz. Their work appears in journals such as IEEE Transactions on Circuits and Systems I Regular Papers, Electronics, IEEE Transactions on Nanotechnology, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and Computers & Electrical Engineering.

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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