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Vaibhav Vyas

dblp:232/4536 · DBLP profile ↗
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3ranked-venue papers
2as first author
3since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 2 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021

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
Electronic design automation · 62% Emerging computing paradigms · 38%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation
logic synthesis
0.512021
Karnaugh Map Method for Memristive and Spintronic Asymmetric Basis Logic Functions · IEEE Trans. Computers 2021
Emerging computing paradigms
memristive computing
0.112021
Karnaugh Map Method for Memristive and Spintronic Asymmetric Basis Logic Functions · IEEE Trans. Computers 2021
Emerging computing paradigms › spintronics
spintronic computing
0.112021
Karnaugh Map Method for Memristive and Spintronic Asymmetric Basis Logic Functions · IEEE Trans. Computers 2021
YearPublicationVenuePosition
2026 Complete Boolean Algebra for Memristive and Spintronic Asymmetric Basis Logic Functions
abstract
The increasing advancement of emerging device technologies that provide alternative basis logic sets necessitates the exploration of innovative logic design automation methodologies. Specifically, emerging computing architectures based on the memristor and the bilayer avalanche spin-diode offer non-commutative or “asymmetric” operations, namely the inverted-input AND (IAND) and implication as basis logic gates. Existing logic design techniques inadequately leverage the unique characteristics of asymmetric logic functions, resulting in insufficiently optimized logic circuits. This article presents a complete Boolean algebraic framework specifically tailored to asymmetric logic functions, introducing fundamental identities, theorems, and canonical normal forms that lay the groundwork for efficient synthesis and minimization of such logic circuits without relying on conventional Boolean algebra. Further, this article establishes a logical relationship between implication and IAND operations. A previously proposed modified Karnaugh map method based on a subset of the presented algebraic principles demonstrated a 28% reduction in computational steps for an algorithmically designed memristive full adder; the presently proposed algebraic framework lays the foundation for much greater future improvements.
Vaibhav Vyas, Joseph S. Friedman
ACM J. Emerg. Technol. Comput. Syst.1
2026 Data privacy preserved student career prediction with deep learning and blockchain based mechanism
Mansi Agarwal, Vaibhav Vyas
Knowl. Based Syst.2
2021 Karnaugh Map Method for Memristive and Spintronic Asymmetric Basis Logic Functions
abstract
The development of beyond-CMOS technologies with alternative basis logic functions necessitates the introduction of novel design automation techniques. In particular, recently proposed computing systems based on memristors and bilayer avalanche spin-diodes both provide asymmetric functions as basis logic gates - the implication and inverted-input AND, respectively. This article therefore proposes a method by which Karnaugh maps can be directly applied to systems with asymmetric basis logic functions. A set of identities is defined for these memristor and spintronic logic functions, enabling the formal demonstration of the Karnaugh map method and an explanation of the proposed technique. This method thus, enables the direct minimization of spintronic and memristive logic circuits without translation to conventional Boolean algebra, facilitating the further development of these novel computing paradigms. Preliminary analyses demonstrate that this Karnaugh map minimization approach can provide a 28 percent reduction in step count as compared to previous manual optimization.
Vaibhav Vyas, Lucian Jiang-Wei, Peng Zhou 0025, Xuan Hu 0002, Joseph S. Friedman
IEEE Trans. Computers1