The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Lloyd J. Whitman sits on this spectrum.
This scientist: 167 publications — 19th percentile
19% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 1,163 publications or more.
The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Lloyd J. Whitman sits on this spectrum.
This scientist: 54 D-Index — 32nd percentile
32% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 165 D-Index or more.
Lloyd J. Whitman is affiliated with the United States Naval Research Laboratory in the United States. Their research spans several areas within computer science and engineering, with a particular focus on computing architectures and memory technologies.
Their publication record includes work on advanced computing methods that diverge from traditional silicon-based and von Neumann architectures. A notable recent paper is titled Nonsilicon, Non-von Neumann Computing-Part II, published in 2020 in the Proceedings of the IEEE. This paper has been cited five times and explores alternative computing paradigms beyond classical semiconductor technologies.
Whitman frequently collaborates with researchers including:
Their work appears primarily in the Proceedings of the IEEE, a venue known for disseminating research in electrical engineering, computer science, and related fields.
Main fields of study for Whitman cover broad disciplines, such as:
Diving deeper into specific subfields, their research engages with:
Whitman's contributions focus on several advanced topics, particularly regarding computation and memory, including:
Their emphasis on quantum-dot cellular automata and quantum computing architectures indicates a strong interest in emerging technologies that could redefine computing hardware paradigms. The integration of neural computing and advanced memory concepts reflects multidisciplinary expertise bridging theoretical and applied aspects of computer science and engineering.
Paul E. Sheehan;Lloyd J. Whitman
R. L. Edelstein;C. R. Tamanaha;P. E. Sheehan;M. M. Miller
Hiromi Kimura-Suda;Dmitri Y. Petrovykh;Michael J. Tarlov;Lloyd J. Whitman
J.C. Rife;M.M. Miller;P.E. Sheehan;C.R. Tamanaha
Dmitri Y. Petrovykh;Hiromi Kimura-Suda;Lloyd J. Whitman;Michael J. Tarlov
L Whitman;Joseph A. Stroscio;Robert A. Dragoset;Robert Celotta
M.M. Miller;P.E. Sheehan;R.L. Edelstein;C.R. Tamanaha
A.A. Baski;S.C. Erwin;L.J. Whitman
E. M. Kneedler;B. T. Jonker;P. M. Thibado;R. J. Wagner
Aric Opdahl;Dmitri Y. Petrovykh;Hiromi Kimura-Suda;Michael J. Tarlov
C.R. Tamanaha;S.P. Mulvaney;J.C. Rife;L.J. Whitman
P. E. Sheehan;L. J. Whitman
D Y. Petrovykh;H Y. Kimura-Suda;Michael J. Tarlov;L J. Whitman
L Whitman;Joseph A. Stroscio;Robert A. Dragoset;Robert Celotta
P. E. Sheehan;L. J. Whitman;William Paul King;Brent A. Nelson
A. S. Bracker;M. Scheibner;M. F. Doty;E. A. Stinaff
L.J Whitman;S.A Joyce;J.A Yarmoff;F.R McFeely
T. M. Mayer;R. A. Barker;L. J. Whitman
D.Y. Petrovykh;D.Y. Petrovykh;M.J. Yang;L.J. Whitman
A. A. Baski;L. J. Whitman;S. C. Erwin
S.P. Mulvaney;C.L. Cole;M.D. Kniller;M. Malito
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