World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
7289
World Ranking
10124
National Ranking
108

Overview

Sparsh Mittal is affiliated with the Indian Institute of Technology Roorkee in India. Their research spans multiple fields with a strong focus on Computer Science and Engineering, reflected in a substantial body of work.

The scientist has contributed extensively to the following main fields of study:

  • Computer Science
  • Engineering

Within these fields, their research covers several subfields, including:

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Hardware and Architecture
  • Computer Networks and Communications

Their main topics of research focus on technological and computational advancements such as:

  • Advanced Memory and Neural Computing
  • Advanced Neural Network Applications
  • Parallel Computing and Optimization Techniques
  • Low-power high-performance VLSI design
  • Graphene research and applications
  • Ferroelectric and Negative Capacitance Devices
  • AI in cancer detection

Sparsh Mittal's frequent co-authors include Onkar Susladkar, Dhruv Makwana, Gayatri Deshmukh, Mubashir A. Kharadi, and Farooq Ahmad Khanday, reflecting collaborative research efforts.

The scientist has a significant presence in various publication venues, with a notable number of papers appearing in:

  • arXiv (Cornell University)
  • Journal of Systems Architecture
  • IEEE Transactions on Electron Devices
  • ACM Transactions on Embedded Computing Systems
  • SSRN Electronic Journal

Examples of recent research papers published by Sparsh Mittal include:

  • "A survey of deep learning techniques for vehicle detection from UAV images," 2021, Journal of Systems Architecture
  • "Review-Silicene: From Material to Device Applications," 2020, ECS Journal of Solid State Science and Technology
  • "A Survey of Deep Learning Techniques for Underwater Image Classification," 2022, IEEE Transactions on Neural Networks and Learning Systems
  • "A survey of techniques for optimizing transformer inference," 2023, Journal of Systems Architecture
  • "A survey of SRAM-based in-memory computing techniques and applications," 2021, Journal of Systems Architecture

Best Publications

  • A Survey of Techniques for Approximate Computing

    Unknown

  • A Survey of CPU-GPU Heterogeneous Computing Techniques

    Sparsh Mittal;Jeffrey S. Vetter

  • A Survey of Software Techniques for Using Non-Volatile Memories for Storage and Main Memory Systems

    Sparsh Mittal;Jeffrey S. Vetter

  • A Survey on optimized implementation of deep learning models on the NVIDIA Jetson platform

    Unknown

  • A survey of techniques for optimizing deep learning on GPUs

    Unknown

  • A survey of techniques for improving energy efficiency in embedded computing systems

    Unknown

  • A survey of deep learning techniques for vehicle detection from UAV images

    Unknown

  • DESTINY: a tool for modeling emerging 3D NVM and eDRAM caches

    Matt Poremba;Sparsh Mittal;Dong Li;Jeffrey S. Vetter

  • A survey of architectural techniques for improving cache power efficiency

    Unknown

  • Opportunities for Nonvolatile Memory Systems in Extreme-Scale High-Performance Computing

    Jeffrey S. Vetter;Sparsh Mittal

  • A Survey of Recent Prefetching Techniques for Processor Caches

    Unknown

  • A Survey of Techniques for Modeling and Improving Reliability of Computing Systems

    Sparsh Mittal;Jeffrey S. Vetter

  • A Survey of Techniques for Architecting and Managing Asymmetric Multicore Processors

    Unknown

  • Power Management Techniques for Data Centers: A Survey

    Unknown

  • A survey of architectural techniques for DRAM power management

    Unknown

  • A survey of SRAM-based in-memory computing techniques and applications

    Sparsh Mittal;Gaurav Verma;Brajesh Kumar Kaushik;Farooq Ahmad Khanday

  • A Survey of Deep Learning on CPUs: Opportunities and Co-Optimizations

    Unknown

  • A survey On hardware accelerators and optimization techniques for RNNs

    Unknown

  • A survey of accelerator architectures for 3D convolution neural networks

    Unknown

  • DESTINY: A Comprehensive Tool with 3D and Multi-Level Cell Memory Modeling Capability

    Sparsh Mittal;Rujia Wang;Jeffrey Vetter

  • A Survey Of Techniques for Architecting DRAM Caches

    Sparsh Mittal;Jeffrey S. Vetter

  • A Survey of Techniques for Cache Partitioning in Multicore Processors

    Sparsh Mittal

  • AYUSH: A Technique for Extending Lifetime of SRAM-NVM Hybrid Caches

    Sparsh Mittal;Jeffrey S. Vetter

  • A Survey of Techniques for Architecting Processor Components Using Domain-Wall Memory

    Sparsh Mittal

  • Algorithm-Directed Data Placement in Explicitly Managed Non-Volatile Memory

    Panruo Wu;Dong Li;Zizhong Chen;Jeffrey S. Vetter

  • Quantitatively modeling application resilience with the data vulnerability factor

    Li Yu;Dong Li;Sparsh Mittal;Jeffrey S. Vetter

  • FlexiWay: A cache energy saving technique using fine-grained cache reconfiguration

    Sparsh Mittal;Zhao Zhang;Jeffrey S. Vetter

  • A Survey of Techniques for Architecting TLBs

    Sparsh Mittal

  • WriteSmoothing: improving lifetime of non-volatile caches using intra-set wear-leveling

    Sparsh Mittal;Jeffrey S. Vetter;Dong Li

  • LastingNVCache: A Technique for Improving the Lifetime of Non-volatile Caches

    Sparsh Mittal;Jeffrey S. Vetter;Dong Li

  • EqualWrites: Reducing Intra-Set Write Variations for Enhancing Lifetime of Non-Volatile Caches

    Sparsh Mittal;Jeffrey S. Vetter

  • A survey of techniques for architecting SLC/MLC/TLC hybrid Flash memory–based SSDs

    Ahmed Izzat Alsalibi;Sparsh Mittal;Mohammed Azmi Al-Betar;Putra Bin Sumari

  • The Ramifications of Making Deep Neural Networks Compact

    Nandan Kumar Jha;Sparsh Mittal;Govardhan Mattela

  • Addressing Read-Disturbance Issue in STT-RAM by Data Compression and Selective Duplication

    Sparsh Mittal;Jeffrey S. Vetter;Lei Jiang

Frequent Co-Authors

Jeffrey S. Vetter
Jeffrey S. Vetter Oak Ridge National Laboratory
Lei Jiang
Lei Jiang Chinese Academy of Sciences
Mehdi B. Tahoori
Mehdi B. Tahoori Karlsruhe Institute of Technology
Mohammed Azmi Al-Betar
Mohammed Azmi Al-Betar Ajman University of Science and Technology
Youtao Zhang
Youtao Zhang University of Pittsburgh
Jun Yang
Jun Yang University of Pittsburgh

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