H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 70 Citations 16,631 255 World Ranking 269 National Ranking 149
Computer Science H-index 74 Citations 18,551 296 World Ranking 616 National Ranking 377

Research.com Recognitions

Awards & Achievements

2010 - IEEE Fellow For contributions to the design of low-power and secure systems on chip

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Artificial intelligence
  • Central processing unit

His primary areas of study are Embedded system, Electronic circuit, Electronic engineering, Software and Efficient energy use. He studies Embedded system, focusing on System on a chip in particular. His work carried out in the field of Electronic circuit brings together such families of science as Logic synthesis, Power optimization and Algorithm.

The Electronic engineering study combines topics in areas such as Non-volatile memory and Integrated circuit. His Software study integrates concerns from other disciplines, such as System testing, Computer engineering and Fault coverage. Anand Raghunathan interconnects Algorithm design, Key, Static random-access memory and Cache in the investigation of issues within Efficient energy use.

His most cited work include:

  • Security in embedded systems: Design challenges (404 citations)
  • Low-Power Digital Signal Processing Using Approximate Adders (403 citations)
  • A study of the energy consumption characteristics of cryptographic algorithms and security protocols (340 citations)

What are the main themes of his work throughout his whole career to date?

Anand Raghunathan focuses on Embedded system, Electronic engineering, Software, Efficient energy use and Parallel computing. Speedup is closely connected to Instruction set in his research, which is encompassed under the umbrella topic of Embedded system. His Electronic engineering research includes themes of Power management, Electronic circuit and Reduction.

His studies deal with areas such as Logic synthesis, Logic gate and Algorithm as well as Electronic circuit. His research investigates the connection with Efficient energy use and areas like Energy consumption which intersect with concerns in Computer engineering and High-level synthesis. Parallel computing is frequently linked to Scheduling in his study.

He most often published in these fields:

  • Embedded system (25.22%)
  • Electronic engineering (14.47%)
  • Software (13.38%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial neural network (6.80%)
  • Artificial intelligence (6.36%)
  • Computer engineering (10.53%)

In recent papers he was focusing on the following fields of study:

Anand Raghunathan mainly investigates Artificial neural network, Artificial intelligence, Computer engineering, Efficient energy use and Parallel computing. His Artificial neural network study combines topics from a wide range of disciplines, such as Energy consumption, Computation, Xeon and Crossbar switch. His Computer engineering study incorporates themes from Electronic circuit, Key and SIMD.

His Efficient energy use research includes elements of NOR logic, Electronic engineering, CMOS and Data transmission. His studies in Parallel computing integrate themes in fields like Random access memory, Reduction and Memory controller. As a part of the same scientific study, Anand Raghunathan usually deals with the Wearable computer, concentrating on State and frequently concerns with Embedded system.

Between 2015 and 2021, his most popular works were:

  • ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks (128 citations)
  • Spin-Transfer Torque Devices for Logic and Memory: Prospects and Perspectives (128 citations)
  • Computing in Memory With Spin-Transfer Torque Magnetic RAM (103 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Artificial intelligence
  • Central processing unit

Anand Raghunathan mainly focuses on Artificial neural network, Computer engineering, Efficient energy use, Artificial intelligence and Electronic engineering. The concepts of his Computer engineering study are interwoven with issues in Time delay neural network, Types of artificial neural networks, Multiplication and Approximation algorithm. His research integrates issues of Natural computing, Embedded system and Unconventional computing in his study of Approximation algorithm.

His Efficient energy use research is multidisciplinary, relying on both Energy consumption and Artificial neuron. His research in Electronic engineering intersects with topics in Electronic circuit and System on a chip. His work on Register-transfer level as part of general Electronic circuit study is frequently connected to Kernel, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Security in embedded systems: Design challenges

Srivaths Ravi;Anand Raghunathan;Paul Kocher;Sunil Hattangady.
ACM Transactions in Embedded Computing Systems (2004)

658 Citations

Low-Power Digital Signal Processing Using Approximate Adders

V. Gupta;D. Mohapatra;A. Raghunathan;K. Roy.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2013)

553 Citations

Security as a new dimension in embedded system design

Paul Kocher;Ruby Lee;Gary McGraw;Anand Raghunathan.
design automation conference (2004)

546 Citations

Battery-Driven System Design: A New Frontier in Low Power Design

K. Lahiri;A. Raghunathan;S. Dey;D. Panigrahi.
asia and south pacific design automation conference (2002)

545 Citations

A study of the energy consumption characteristics of cryptographic algorithms and security protocols

N.R. Potlapally;S. Ravi;A. Raghunathan;N.K. Jha.
IEEE Transactions on Mobile Computing (2006)

475 Citations

IMPACT: imprecise adders for low-power approximate computing

Vaibhav Gupta;Debabrata Mohapatra;Sang Phill Park;Anand Raghunathan.
international symposium on low power electronics and design (2011)

432 Citations

Analysis and characterization of inherent application resilience for approximate computing

Vinay K. Chippa;Srimat T. Chakradhar;Kaushik Roy;Anand Raghunathan.
design automation conference (2013)

404 Citations

Analyzing the energy consumption of security protocols

Nachiketh R. Potlapally;Srivaths Ravi;Anand Raghunathan;Niraj K. Jha.
international symposium on low power electronics and design (2003)

362 Citations

High-Level Power Analysis and Optimization

Anand Raghunathan;Niraj K. Jha;Sujit Dey.
(1997)

341 Citations

Tarazu: optimizing MapReduce on heterogeneous clusters

Faraz Ahmad;Srimat T. Chakradhar;Anand Raghunathan;T. N. Vijaykumar.
architectural support for programming languages and operating systems (2012)

338 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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