World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
42
Citations
8036
World Ranking
4071
National Ranking
1457

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to low-power circuits and devices in scaled CMOS technologies

Overview

Ali Keshavarzi is affiliated with Stanford University in the United States. Their research primarily focuses on environmental science, with a significant concentration in environmental engineering, soil science, artificial intelligence applications, management and policy related to the environment, and ecology.

The scientist's main topics of study include:

  • Soil Geostatistics and Mapping
  • Geochemistry and Geologic Mapping
  • Soil and Land Suitability Analysis
  • Soil erosion and sediment transport
  • Soil Carbon and Nitrogen Dynamics
  • Soil and Unsaturated Flow
  • Remote Sensing in Agriculture

Frequent publication venues for their work are:

  • CATENA
  • Geoderma Regional
  • Land
  • SSRN Electronic Journal
  • Environmental Geochemistry and Health

Coauthors who have regularly collaborated with Ali Keshavarzi include:

  • Fuat Kaya
  • Jesús Rodrigo-Comino
  • Vinod Kumar
  • Rosa Francaviglia
  • Levent Başayığıt

Notable recent papers authored or coauthored by the scientist include:

  • Ecological risk assessment and source apportionment of heavy metals contamination: an appraisal based on the Tellus soil survey (2021), Environmental Geochemistry and Health
  • Assessing Machine Learning-Based Prediction under Different Agricultural Practices for Digital Mapping of Soil Organic Carbon and Available Phosphorus (2022), Agriculture
  • Combination of MIR spectroscopy and environmental covariates to predict soil organic carbon in a semi-arid region (2020), CATENA
  • Using fuzzy-AHP and parametric technique to assess soil fertility status in Northeast of Iran (2020), Journal of Mountain Science
  • Machine learning for cation exchange capacity prediction in different land uses (2022), CATENA

Ali Keshavarzi's work integrates advanced techniques from artificial intelligence to enhance environmental and soil science investigations. This interdisciplinary approach reflects an emphasis on applying digital tools and machine learning to address soil properties and contamination issues.

An award linked with their career is the IEEE Fellow distinction granted in 2021, recognizing contributions to low-power circuits and devices in scaled CMOS technologies.

Best Publications

  • Parameter variations and impact on circuits and microarchitecture

    Shekhar Borkar;Tanay Karnik;Siva Narendra;Jim Tschanz

  • The future of ferroelectric field-effect transistor technology

    Asif Islam Khan;Ali Keshavarzi;Suman Datta

  • Floating-body dynamic random access memory and method of fabrication in tri-gate technology

    Stephen H. Tang;Ali Keshavarzi;Dinesh Somasekhar;Fabrice Paillet

  • Intrinsic leakage in low power deep submicron CMOS ICs

    A. Keshavarzi;K. Roy;C.F. Hawkins

  • Effectiveness of reverse body bias for leakage control in scaled dual Vt CMOS ICs

    A. Keshavarzi;S. Ma;S. Narendra;B. Bloechel

  • Multiple well transistor circuits having forward body bias

    Vivek K. De;Ali Keshavarzi;Siva G. Narendra;Shekhar Y. Borkar

  • Differential circuits employing forward body bias

    Krishnamurthy Soumyanath;Ali Keshavarzi;Vivek K. De;Shekhar Y. Borkar

  • Forward body bias for microprocessors in 130-nm technology generation and beyond

    S. Narendra;A. Keshavarzi;B.A. Bloechel;S. Borkar

  • Technology scaling behavior of optimum reverse body bias for standby leakage power reduction in CMOS IC's

    A. Keshavarzi;S. Narendra;S. Borkar;C. Hawkins

  • Circuit including forward body bias from supply voltage and ground nodes

    Vivek K. De;Ali Keshavarzi;Siva G. Narendra;Shekhar Y. Borkar

  • Floating-body memory cell write

    Stephen H. Tang;Ali Keshavarzi;Dinesh Somasekhar;Fabrice Paillet

  • Software control of transistor body bias in controlling chip parameters

    Shekhar Y. Borkar;Vivek K. De;Ali Keshavarzi;Siva G. Narendra

  • Floating-body dram using write word line for increased retention time

    Stephen Tang;Ali Keshavarzi;Dinesh Somasekhar;Fabrice Paillet

  • Ultra-low voltage circuits and processor in 180nm to 90nm technologies with a swapped-body biasing technique

    S. Narendra;J. Tschanz;J. Hofsheier;B. Bloechel

  • OTP antifuse cell and cell array

    Fabrice Paillet;Ali Keshavarzi;Muhammad M. Khellah;Dinesh Somasekhar

  • Floating-body dynamic random access memory with purge line

    Stephen H. Tang;Ali Keshavarzi;Dinesh Somasekhar;Fabrice Paillet

  • Method and apparatus to generate a reference value in a memory array

    Dinesh Somasekhar;Yibin Ye;Muhammad M. Khellah;Fabrice Paillet

  • Purge-based floating body memory

    Ali Keshavarzi;Stephen H Tang;Dinesh Somasekhar;Fabrice Paillet

  • Floating-body DRAM with two-phase write

    Stephen H. Tang;Ali Keshavarzi;Dinesh Somasekhar;Fabrice Paillet

  • 2 GHz 2 Mb 2T Gain Cell Memory Macro With 128 GBytes/sec Bandwidth in a 65 nm Logic Process Technology

    D. Somasekhar;Yibin Ye;P. Aseron;Shih-Lien Lu

  • Dual-V/sub T/ SRAM cells with full-swing single-ended bit line sensing for high-performance on-chip cache in 0.13 /spl mu/m technology generation

    Fatih Hamzaoglu;Yibin Te;Ali Keshavarzi;Kevin Zhang

Frequent Co-Authors

Vivek De
Vivek De Intel (United States)
Dinesh Somasekhar
Dinesh Somasekhar Intel (United States)
Siva G. Narendra
Siva G. Narendra Tyfone, Inc.
Muhammad M. Khellah
Muhammad M. Khellah Intel (United States)
Shekhar Borkar
Shekhar Borkar Qualcomm (United States)
Shih-Lien Lu
Shih-Lien Lu Washington State University
Tanay Karnik
Tanay Karnik Intel (United States)
Manoj Sachdev
Manoj Sachdev University of Waterloo
Kaushik Roy
Kaushik Roy Purdue University West Lafayette
Arijit Raychowdhury
Arijit Raychowdhury Georgia Institute of Technology

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