World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
82
Citations
23930
World Ranking
466
National Ranking
215

Computer Science

D-Index
86
Citations
25605
World Ranking
780
National Ranking
421

Anand Raghunathan publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Anand Raghunathan sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 431 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Anand Raghunathan D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Anand Raghunathan sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 82 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

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

Overview

Anand Raghunathan is affiliated with Purdue University West Lafayette in the United States. Their research primarily spans the fields of Engineering and Computer Science, with a strong focus on Electrical and Electronic Engineering and specialized interests in Artificial Intelligence, Computer Vision and Pattern Recognition, and Computer Networks and Communications.

Their main research topics include:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Advanced Neural Network Applications
  • Adversarial Robustness in Machine Learning
  • Semiconductor materials and devices
  • Low-power high-performance VLSI design
  • Anomaly Detection Techniques and Applications

Raghunathan has contributed to various publication venues, frequently publishing in:

  • arXiv (Cornell University)
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • ACM Transactions on Embedded Computing Systems
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • Proceedings of the 59th ACM/IEEE Design Automation Conference

Some of the recent papers authored or co-authored by Anand Raghunathan include:

  • "Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges," 2020, Proceedings of the IEEE
  • "Compute in-Memory with Non-Volatile Elements for Neural Networks: A Review from a Co-Design Perspective," 2022, Advanced Materials
  • "X-Former: In-Memory Acceleration of Transformers," 2023, IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • "Gradual Channel Pruning While Training Using Feature Relevance Scores for Convolutional Neural Networks," 2020, IEEE Access
  • "Compute-in-Memory Technologies and Architectures for Deep Learning Workloads," 2022, IEEE Transactions on Very Large Scale Integration (VLSI) Systems

Raghunathan's frequent collaborators include Sourjya Roy, Kaushik Roy, Sanchari Sen, R. Elangovan, and Jacob R. Stevens.

In recognition of contributions to the field, Anand Raghunathan was named an IEEE Fellow in 2010 for work on the design of low-power and secure systems on chip.

Best Publications

  • Low-Power Digital Signal Processing Using Approximate Adders

    V. Gupta;D. Mohapatra;A. Raghunathan;K. Roy

  • Security in embedded systems: Design challenges

    Srivaths Ravi;Anand Raghunathan;Paul Kocher;Sunil Hattangady

  • Analysis and characterization of inherent application resilience for approximate computing

    Vinay K. Chippa;Srimat T. Chakradhar;Kaushik Roy;Anand Raghunathan

  • Security as a new dimension in embedded system design

    Paul Kocher;Ruby Lee;Gary McGraw;Anand Raghunathan

  • On the competitiveness of on-line real-time task scheduling

    S. Baruah;G. Koren;D. Mao;B. Mishra

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

    N.R. Potlapally;S. Ravi;A. Raghunathan;N.K. Jha

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

    K. Lahiri;A. Raghunathan;S. Dey;D. Panigrahi

  • IMPACT: imprecise adders for low-power approximate computing

    Vaibhav Gupta;Debabrata Mohapatra;Sang Phill Park;Anand Raghunathan

  • Hijacking an insulin pump: Security attacks and defenses for a diabetes therapy system

    Chunxiao Li;Anand Raghunathan;Niraj K. Jha

  • SALSA: systematic logic synthesis of approximate circuits

    Swagath Venkataramani;Amit Sabne;Vivek Kozhikkottu;Kaushik Roy

  • Analyzing the energy consumption of security protocols

    Nachiketh R. Potlapally;Srivaths Ravi;Anand Raghunathan;Niraj K. Jha

  • Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare

    Mehran Mozaffari-Kermani;Susmita Sur-Kolay;Anand Raghunathan;Niraj K. Jha

  • High-Level Power Analysis and Optimization

    Anand Raghunathan;Niraj K. Jha;Sujit Dey

  • Computing in Memory With Spin-Transfer Torque Magnetic RAM

    Shubham Jain;Ashish Ranjan;Kaushik Roy;Anand Raghunathan

  • Tarazu: optimizing MapReduce on heterogeneous clusters

    Faraz Ahmad;Srimat T. Chakradhar;Anand Raghunathan;T. N. Vijaykumar

  • Quality programmable vector processors for approximate computing

    Swagath Venkataramani;Vinay K. Chippa;Srimat T. Chakradhar;Kaushik Roy

  • Tamper resistance mechanisms for secure embedded systems

    S. Ravi;A. Raghunathan;S. Chakradhar

  • Approximate computing and the quest for computing efficiency

    Swagath Venkataramani;Srimat T. Chakradhar;Kaushik Roy;Anand Raghunathan

  • AxNN: energy-efficient neuromorphic systems using approximate computing

    Swagath Venkataramani;Ashish Ranjan;Kaushik Roy;Anand Raghunathan

  • Optimizing public-key encryption for wireless clients

    N.R. Potlapally;S. Ravi;A. Raghunathan;G. Lakshminarayana

  • MACACO: modeling and analysis of circuits for approximate computing

    Rangharajan Venkatesan;Amit Agarwal;Kaushik Roy;Anand Raghunathan

Frequent Co-Authors

Niraj K. Jha
Niraj K. Jha Princeton University
Kaushik Roy
Kaushik Roy Purdue University West Lafayette
Sujit Dey
Sujit Dey University of California, San Diego
Srimat T. Chakradhar
Srimat T. Chakradhar NEC (United States)
Swagath Venkataramani
Swagath Venkataramani IBM (United States)
Vijay Raghunathan
Vijay Raghunathan Purdue University West Lafayette
Ruby B. Lee
Ruby B. Lee Princeton University
Charles A. Bouman
Charles A. Bouman Purdue University West Lafayette
Lin Zhong
Lin Zhong Yale University
Sumeet Kumar Gupta
Sumeet Kumar Gupta Purdue University West Lafayette

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