World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
14701
World Ranking
4021
National Ranking
1916

Overview

Moinuddin K. Qureshi is affiliated with the Georgia Institute of Technology in the United States. Their research primarily focuses on computer science, with a significant emphasis on artificial intelligence, quantum computing, and electronic engineering.

The main fields of study they have contributed to include:

  • Computer Science

Within this broad area, their research touches on several subfields such as:

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Information Systems
  • Hardware and Architecture

Their work primarily explores topics related to:

  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Security and Verification in Computing
  • Parallel Computing and Optimization Techniques
  • Quantum-Dot Cellular Automata
  • Cloud Computing and Resource Management
  • Quantum Mechanics and Applications

Moinuddin K. Qureshi has published extensively in various venues, with frequent publications in:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Computer Architecture Letters
  • Research Square (Research Square)
  • IEEE Transactions on Electron Devices

Among their recent papers are:

  • Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training (2021), IEEE Transactions on Electron Devices
  • A Scalable Decoder Micro-architecture for Fault-Tolerant Quantum Computing (2020), arXiv (Cornell University)
  • MIRAGE: Mitigating Conflict-Based Cache Attacks with a Practical Fully-Associative Design (2020), arXiv (Cornell University)
  • A Day In the Life of a Quantum Error (2020), IEEE Computer Architecture Letters

Frequent collaborators include:

  • Poulami Das
  • Ramin Ayanzadeh
  • Narges Alavisamani
  • Suhas Vittal
  • Sanjay Kariyappa

Best Publications

  • Scalable high performance main memory system using phase-change memory technology

    Moinuddin K. Qureshi;Vijayalakshmi Srinivasan;Jude A. Rivers

  • Utility-Based Cache Partitioning: A Low-Overhead, High-Performance, Runtime Mechanism to Partition Shared Caches

    Moinuddin K. Qureshi;Yale N. Patt

  • Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling

    Moinuddin K. Qureshi;John Karidis;Michele Franceschini;Vijayalakshmi Srinivasan

  • Adaptive insertion policies for high performance caching

    Moinuddin K. Qureshi;Aamer Jaleel;Yale N. Patt;Simon C. Steely

  • Adaptive insertion policies for managing shared caches

    Aamer Jaleel;William Hasenplaugh;Moinuddin Qureshi;Julien Sebot

  • A Case for MLP-Aware Cache Replacement

    Moinuddin K. Qureshi;Daniel N. Lynch;Onur Mutlu;Yale N. Patt

  • Accelerating critical section execution with asymmetric multi-core architectures

    M. Aater Suleman;Onur Mutlu;Moinuddin K. Qureshi;Yale N. Patt

  • Improving read performance of Phase Change Memories via Write Cancellation and Write Pausing

    Moinuddin K. Qureshi;Michele M. Franceschini;Luis A. Lastras-Montano

  • Not All Qubits Are Created Equal: A Case for Variability-Aware Policies for NISQ-Era Quantum Computers

    Swamit S. Tannu;Moinuddin K. Qureshi

  • Fundamental Latency Trade-off in Architecting DRAM Caches: Outperforming Impractical SRAM-Tags with a Simple and Practical Design

    Moinuddin K. Qureshi;Gabe H. Loh

  • The V-Way Cache: Demand Based Associativity via Global Replacement

    Moinuddin K. Qureshi;David Thompson;Yale N. Patt

  • Low-Cost Inter-Linked Subarrays (LISA): Enabling fast inter-subarray data movement in DRAM

    Kevin K. Chang;Prashant J. Nair;Donghyuk Lee;Saugata Ghose

  • Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPs

    M. Aater Suleman;Moinuddin K. Qureshi;Yale N. Patt

  • AVATAR: A Variable-Retention-Time (VRT) Aware Refresh for DRAM Systems

    Moinuddin K. Qureshi;Dae-Hyun Kim;Samira Khan;Prashant J. Nair

  • Morphable memory system: a robust architecture for exploiting multi-level phase change memories

    Moinuddin K. Qureshi;Michele M. Franceschini;Luis A. Lastras-Montaño;John P. Karidis

  • CEASER: mitigating conflict-based cache attacks via encrypted-address and remapping

    Moinuddin K. Qureshi

  • ArchShield: architectural framework for assisting DRAM scaling by tolerating high error rates

    Prashant J. Nair;Dae-Hyun Kim;Moinuddin K. Qureshi

  • PreSET: improving performance of phase change memories by exploiting asymmetry in write times

    Moinuddin K. Qureshi;Michele M. Franceschini;Ashish Jagmohan;Luis A. Lastras

  • A tagless coherence directory

    Jason Zebchuk;Moinuddin K. Qureshi;Vijayalakshmi Srinivasan;Andreas Moshovos

  • NVRAM-aware logging in transaction systems

    Jian Huang;Karsten Schwan;Moinuddin K. Qureshi

  • Utility-Based Cache Partitioning

    Moinuddin K. Qureshi;Yale N. Patt

Frequent Co-Authors

Yale N. Patt
Yale N. Patt The University of Texas at Austin
Aamer Jaleel
Aamer Jaleel Nvidia (United States)
Vijayalakshmi Srinivasan
Vijayalakshmi Srinivasan IBM (United States)
Onur Mutlu
Onur Mutlu ETH Zurich
Alper Buyuktosunoglu
Alper Buyuktosunoglu IBM (United States)
John P. Karidis
John P. Karidis IBM (United States)
Jian Huang
Jian Huang University of Iowa
Pradip Bose
Pradip Bose IBM (United States)
Karsten Schwan
Karsten Schwan Georgia Institute of Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As you explore studying Computer Science in the USA, it's worth considering related online degrees and career pathways that can diversify your skillset and open up new job opportunities. Fields such as data science and electrical engineering are closely aligned with computer science and offer excellent prospects.

If you have a keen interest in analytics, a data science degree can prepare you for high-demand careers in data analysis, artificial intelligence, and machine learning. Alternatively, those drawn to hardware and systems design may want to explore institutions with a strong online electrical engineering degree ranking for a reputable program.

For students who want to enhance their resumes even further, there are plenty of easy certifications to get online that offer a quick pathway to higher salaries and technical specialization. If your goal is to advance rapidly, you may also consider earning one of the quick masters degrees online to accelerate your career growth.

Exploring these related disciplines and credentials can significantly broaden your career options both within and beyond computer science.

Best Scientists Citing Moinuddin K. Qureshi

Trending Scientists