2018 - Member of the National Academy of Engineering For contributions to digital storage and nanopositioning technologies, as implemented in hard disk-, tape-, and phase-change memory storage systems.
2002 - IEEE Fellow For contributions to equalization and coding, and for noise-predictive maximum likelihood detection in magnetic recording.
Evangelos Eleftheriou spends much of his time researching Electronic engineering, Phase-change memory, Algorithm, Decoding methods and Equalization. His Electronic engineering research integrates issues from Modulation, Actuator, Microelectromechanical systems, Servo control and Reliability. His Phase-change memory study integrates concerns from other disciplines, such as Artificial neural network, Neuromorphic engineering, Spiking neural network and Computer architecture.
His work on Serial concatenated convolutional codes and Sequential decoding as part of general Algorithm research is often related to Memory cell, thus linking different fields of science. Equalization is a subfield of Communication channel that Evangelos Eleftheriou tackles. His research integrates issues of Discrete mathematics and Binary code in his study of Low-density parity-check code.
The scientist’s investigation covers issues in Electronic engineering, Algorithm, Communication channel, Computer hardware and Computer data storage. His Electronic engineering research incorporates elements of Equalization, Modulation, Phase-change memory, Microelectromechanical systems and Cantilever. The Phase-change memory study which covers Artificial neural network that intersects with Deep learning, Resistive random-access memory and Crossbar switch.
In his study, which falls under the umbrella issue of Algorithm, Metric and Process is strongly linked to Detector. His biological study spans a wide range of topics, including Noise, Signal and Control theory. The various areas that Evangelos Eleftheriou examines in his Low-density parity-check code study include Discrete mathematics, Combinatorics, Block code, Linear code and Turbo code.
Artificial intelligence, Artificial neural network, Phase-change memory, Neuromorphic engineering and Resistive random-access memory are his primary areas of study. His research in Artificial neural network intersects with topics in Computer architecture, Key, Chip and Crossbar switch. His work carried out in the field of Phase-change memory brings together such families of science as Process, Scalability, Parallel computing, Von Neumann architecture and Realization.
He interconnects Feature extraction and Electronic engineering, Memristor in the investigation of issues within Neuromorphic engineering. Many of his studies on Electronic engineering involve topics that are commonly interrelated, such as Electrical engineering. Evangelos Eleftheriou combines subjects such as State, Signal generator, Signal, Task and Topology with his study of Resistive random-access memory.
His primary scientific interests are in Phase-change memory, Artificial neural network, Von Neumann architecture, Neuromorphic engineering and Resistive random-access memory. His Phase-change memory study integrates concerns from other disciplines, such as Process, Data stream mining, State and Key. His study in Artificial neural network is interdisciplinary in nature, drawing from both Computer architecture and Deep learning.
His studies deal with areas such as Scalability, Memristor, Computational science, Parallel computing and Computation as well as Von Neumann architecture. The Neuromorphic engineering study combines topics in areas such as Supervised training, Randomness, Electronic engineering and Statistical model. Evangelos Eleftheriou connects Electronic engineering with Amorphous phase in his study.
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Regular and irregular progressive edge-growth tanner graphs
Xiao-Yu Hu;E. Eleftheriou;D.M. Arnold.
IEEE Transactions on Information Theory (2005)
A Survey of Control Issues in Nanopositioning
S. Devasia;E. Eleftheriou;S.O.R. Moheimani.
IEEE Transactions on Control Systems and Technology (2007)
Reduced-complexity decoding of LDPC codes
Jinghu Chen;A. Dholakia;E. Eleftheriou;M.P.C. Fossorier.
IEEE Transactions on Communications (2005)
Progressive edge-growth Tanner graphs
Xiao-Yu Hu;E. Eleftheriou;D.-M. Arnold.
global communications conference (2001)
Stochastic phase-change neurons
Tomas Tuma;Angeliki Pantazi;Manuel Le Gallo;Manuel Le Gallo;Abu Sebastian.
Nature Nanotechnology (2016)
Efficient implementations of the sum-product algorithm for decoding LDPC codes
Xiao-Yu Hu;E. Eleftheriou;D.-M. Arnold;A. Dholakia.
global communications conference (2001)
Tracking properties and steady-state performance of RLS adaptive filter algorithms
E. Eleftheriou;D. Falconer.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1986)
Write amplification analysis in flash-based solid state drives
Xiao-Yu Hu;Evangelos Eleftheriou;Robert Haas;Ilias Iliadis.
Proceedings of SYSTOR 2009: The Israeli Experimental Systems Conference (2009)
Filtered multitone modulation for very high-speed digital subscriber lines
G. Cherubini;E. Eleftheriou;S. Olcer.
IEEE Journal on Selected Areas in Communications (2002)
"Millipede": a MEMS-based scanning-probe data-storage system
E. Eleftheriou;T. Antonakopoulos;G.K. Binnig;G. Cherubini.
asia pacific magnetic recording conference (2002)
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