2026 Anand Raghunathan: Electronics and Electrical Engineering Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	86	780	753	420	404	444	25605
Electronics and Electrical Engineering	82	466	449	214	202	431	23930

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

975
Citations
Security in embedded systems: Design challenges

Srivaths Ravi;Anand Raghunathan;Paul Kocher;Sunil Hattangady

702
Citations
Analysis and characterization of inherent application resilience for approximate computing

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

647
Citations
Security as a new dimension in embedded system design

Paul Kocher;Ruby Lee;Gary McGraw;Anand Raghunathan

584
Citations
On the competitiveness of on-line real-time task scheduling

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

572
Citations
A study of the energy consumption characteristics of cryptographic algorithms and security protocols

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

552
Citations
Battery-Driven System Design: A New Frontier in Low Power Design

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

549
Citations
IMPACT: imprecise adders for low-power approximate computing

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

517
Citations
Hijacking an insulin pump: Security attacks and defenses for a diabetes therapy system

Chunxiao Li;Anand Raghunathan;Niraj K. Jha

409
Citations
SALSA: systematic logic synthesis of approximate circuits

Swagath Venkataramani;Amit Sabne;Vivek Kozhikkottu;Kaushik Roy

398
Citations
Analyzing the energy consumption of security protocols

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

390
Citations
Systematic Poisoning Attacks on and Defenses for Machine Learning in Healthcare

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

374
Citations
High-Level Power Analysis and Optimization

Anand Raghunathan;Niraj K. Jha;Sujit Dey

373
Citations
Computing in Memory With Spin-Transfer Torque Magnetic RAM

Shubham Jain;Ashish Ranjan;Kaushik Roy;Anand Raghunathan

349
Citations
Tarazu: optimizing MapReduce on heterogeneous clusters

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

347
Citations
Quality programmable vector processors for approximate computing

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

329
Citations
Tamper resistance mechanisms for secure embedded systems

S. Ravi;A. Raghunathan;S. Chakradhar

310
Citations
Approximate computing and the quest for computing efficiency

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

298
Citations
AxNN: energy-efficient neuromorphic systems using approximate computing

Swagath Venkataramani;Ashish Ranjan;Kaushik Roy;Anand Raghunathan

295
Citations
Optimizing public-key encryption for wireless clients

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

292
Citations
MACACO: modeling and analysis of circuits for approximate computing

Rangharajan Venkatesan;Amit Agarwal;Kaushik Roy;Anand Raghunathan

285
Citations

Frequent Co-Authors

Niraj K. Jha Princeton University

Kaushik Roy Purdue University West Lafayette

Sujit Dey University of California, San Diego

Srimat T. Chakradhar NEC (United States)

Swagath Venkataramani IBM (United States)

Vijay Raghunathan Purdue University West Lafayette

Ruby B. Lee Princeton University

Charles A. Bouman Purdue University West Lafayette

Lin Zhong Yale University

Sumeet Kumar Gupta Purdue University West Lafayette

External Links

Personal website of Anand Raghunathan Google Scholar page

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