2026 Lizy K. John: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	55	4365	4243	2040	1968	359	10541

Lizy K. John publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Lizy K. John sits on this spectrum.

32 publications 991+

This scientist: 359 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Lizy K. John D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Lizy K. John sits on this spectrum.

30 D-Index 131+

This scientist: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2020 - Fellow, National Academy of Inventors
2020 - ACM Fellow For contributions to the design, modeling and benchmarking of computer architectures
2009 - IEEE Fellow For contributions to power modeling and performance evaluation of microprocessors

Overview

Lizy K. John is affiliated with The University of Texas at Austin in the United States. Their research primarily focuses on computer science, with specializations in hardware and architecture, electrical and electronic engineering, computer networks and communications, artificial intelligence, and computer vision and pattern recognition.

Their work encompasses a range of topics including:

Parallel Computing and Optimization Techniques
Advanced Memory and Neural Computing
Embedded Systems Design Techniques
Advanced Data Storage Technologies
Interconnection Networks and Systems
VLSI and FPGA Design Techniques
Low-power high-performance VLSI design

Frequent co-authors in their publications include Aman Arora, Zachary Susskind, Felipe M. G. França, Alan T. L. Bacellar, and Bagus Hanindhito.

Lizy K. John's research contributions have appeared in various publication venues, notably:

IEEE Micro
arXiv (Cornell University)
ACM Transactions on Architecture and Code Optimization
Zenodo (CERN European Organization for Nuclear Research)
ACM Transactions on Reconfigurable Technology and Systems

Selected recent papers by Lizy K. John include:

Neuro-Symbolic AI: An Emerging Class of AI Workloads and their Characterization, 2021, arXiv (Cornell University)
Koios 2.0: Open-Source Deep Learning Benchmarks for FPGA Architecture and CAD Research, 2023, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Thermal-Aware Design Space Exploration of 3-D Systolic ML Accelerators, 2021, IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
CoMeFa: Deploying Compute-in-Memory on FPGAs for Deep Learning Acceleration, 2023, ACM Transactions on Reconfigurable Technology and Systems
Tensor Slices: FPGA Building Blocks For The Deep Learning Era, 2022, ACM Transactions on Reconfigurable Technology and Systems

Their research career includes recognition as an ACM Fellow (2020) for contributions to the design, modeling, and benchmarking of computer architectures, and being named a Fellow of the National Academy of Inventors in 2020. Earlier, in 2009, they were honored as an IEEE Fellow for contributions to power modeling and performance evaluation of microprocessors.

Best Publications

Scaling to the end of silicon with EDGE architectures

D. Burger;S.W. Keckler;K.S. McKinley;M. Dahlin

529
Citations
Digital Systems Design Using VHDL

Charles H. Roth;Lizy K. John

364
Citations
Run-time modeling and estimation of operating system power consumption

Tao Li;Lizy Kurian John

355
Citations
A novel low power energy recovery full adder cell

R. Shalem;E. John;L.K. John

315
Citations
Using complete machine simulation for software power estimation: the SoftWatt approach

S. Gurumurthi;A. Sivasubramaniam;M.J. Irwin;N. Vijaykrishnan

303
Citations
Complete System Power Estimation Using Processor Performance Events

W. L. Bircher;L. K. John

286
Citations
Analysis of redundancy and application balance in the SPEC CPU2006 benchmark suite

Aashish Phansalkar;Ajay Joshi;Lizy K. John

273
Citations
Complete System Power Estimation: A Trickle-Down Approach Based on Performance Events

W.L. Bircher;L.K. John

253
Citations
Minimalist open-page: a DRAM page-mode scheduling policy for the many-core era

Dimitris Kaseridis;Jeffrey Stuecheli;Lizy Kurian John

216
Citations
Measuring Program Similarity: Experiments with SPEC CPU Benchmark Suites

Aashish Phansalkar;Ajay Joshi;L. Eeckhout;L.K. John

212
Citations
Performance prediction based on inherent program similarity

Kenneth Hoste;Aashish Phansalkar;Lieven Eeckhout;Andy Georges

185
Citations
Measuring benchmark similarity using inherent program characteristics

Ajay Joshi;Aashish Phansalkar;L. Eeckhout;L.K. John

172
Citations
Control Flow Modeling in Statistical Simulation for Accurate and Efficient Processor Design Studies

Lieven Eeckhout;Robert H. Bell;Bastiaan Stougie;Koen De Bosschere

166
Citations
The virtual write queue: coordinating DRAM and last-level cache policies

Jeffrey Stuecheli;Dimitris Kaseridis;David Daly;Hillery C. Hunter

164
Citations
Bottlenecks in multimedia processing with SIMD style extensions and architectural enhancements

D. Talla;L.K. John;D. Burger

162
Citations
Runtime identification of microprocessor energy saving opportunities

W. L. Bircher;M. Valluri;J. Law;L. K. John

150
Citations
Evaluating MMX technology using DSP and multimedia applications

Ravi Bhargava;Lizy K. John;Brian L. Evans;Ramesh Radhakrishnan

150
Citations
Elastic Refresh: Techniques to Mitigate Refresh Penalties in High Density Memory

Jeffrey Stuecheli;Dimitris Kaseridis;Hillery C.Hunter;Lizy K. John

149
Citations
Is Compiling for Performance — Compiling for Power?

Madhavi Valluri;Lizy K. John

131
Citations
Efficient program scheduling for heterogeneous multi-core processors

Jian Chen;Lizy K. John

118
Citations
Performance Evaluation and Benchmarking

Lizy Kurian John;Lieven Eeckhout

106
Citations

Frequent Co-Authors

Andreas Gerstlauer The University of Texas at Austin

Lieven Eeckhout Ghent University

Tao Li University of Florida

Anand Sivasubramaniam Pennsylvania State University

David J. Lilja University of Minnesota

Hai Jin Huazhong University of Science and Technology

N. Vijaykrishnan Pennsylvania State University

Michael J. Schulte Advanced Micro Devices (United States)

Koen De Bosschere Ghent University

Brian L. Evans The University of Texas at Austin

External Links

Wikipedia of Lizy K. John Personal website of Lizy K. John Google Scholar page

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