Demo Data from EDBT 2026 / reviewers in the wild / expert
Mehdi Kabir
dblp:71/9547
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2014
0009-0006-9606-2231ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Emerging computing paradigms · 67% Integrated circuit design · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Integrated circuit design › analog and mixed-signal circuits
mixed-signal circuit design |
0.2 | 1 | 2014 | Computing with Hybrid CMOS/STO Circuits · DAC 2014 |
Emerging computing paradigms
neuromorphic computing |
0.2 | 1 | 2014 | Computing with Hybrid CMOS/STO Circuits · DAC 2014 |
Emerging computing paradigms › analog computing
oscillator-based computing |
0.2 | 1 | 2014 | Computing with Hybrid CMOS/STO Circuits · DAC 2014 |
Methods — techniques the papers use, named apart from their topics
pattern recognition · 0.2kuramoto oscillator model · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Computing with Hybrid CMOS/STO CircuitsabstractRecent research in spin torque nano-oscillators (STNO) have opened the possibility of using electron spin to generate sustained microwave oscillations. Furthermore, the experimental verification of synchronization of STNOs could allow communication and computation with nanoscaled oscillators. In this paper, we propose a hybrid MOSFET/STNO array which can be used for pattern recognition applications. First, we show that an array of electrically coupled STNOs obey the dynamics of Kuramoto's weakly coupled oscillators [1]. This behavior allows us to use the STNO array to implement the oscillatory neurocomputer proposed by Hoppensteadt et. al. [2]. Mehdi Kabir, Mircea R. Stan |
DAC | 1 |
| 2012 | Self-assembled multiferroic magnetic QCA structures for low power systemsabstractThe discovery of multiferroic materials has lead to a great interest in creating logic circuits which exploit both the magnetic and electrical properties of these materials. In this work we focus on self-assembled array structures of Magnetic Quantum Cellular Automata (MQCA) composed of multiferroic nanopillars which can be configured and clocked using solely electric fields. Furthermore, due to the switching nature of these nanopillars, the arrays can be reconfigured to implement read/write memory or multiple logic circuits in a similar fashion to FPGAs. Finally, we develop a SPICE model for the multiferroic nanopillars and demonstrate the functionality of the array. Mircea R. Stan, Mehdi Kabir, Jiwei Lu, Stuart A. Wolf |
ISCAS | 2 |
| 2011 | RAMA: a self-assembled multiferroic magnetic QCA for low power systemsabstractRecently, with the discovery of multiferroic materials, there has been a great interest in creating logic devices which exploit both magnetic and electric properties of these materials. This paper proposes a reconfigurable array of magnetic automata (RAMA) made of multiferroic nanopillars which can be operated using electric fields. Furthermore, due to the switching nature of these nanopillars, the array can be reconfigured to implement multiple logic circuits in a similar fashion to FPGAs. The paper proposes a compact model of the multiferroic switching mechanism which can be used to describe the behavior of the nanopillars in a circuit simulator. In addition, results from micromagnetic simulations of the MQCA bits indicate that it can operate with energy consumptions that are magnitudes lower than conventional CMOS technologies. Finally, the paper discusses the reliability of the nanopillar switching and suggests ways to optimize the error rates. Mehdi Kabir, Mircea R. Stan, Stuart A. Wolf, Ryan B. Comes, Jiwei Lu |
ACM Great Lakes Symposium on VLSI | 1 |