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Computer Science

D-Index
35
Citations
5890
World Ranking
11615
National Ranking
4765

Overview

Craig Zilles is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research primarily focuses on computer science, with a notable emphasis on applications within this field.

The key areas of study for Craig Zilles include:

  • Computer Science Applications
  • Artificial Intelligence
  • Software
  • Information Systems
  • Cognitive Neuroscience

The main topics covered in their research encompass:

  • Teaching and Learning Programming
  • Online Learning and Analytics
  • Machine Learning and Algorithms
  • Software Testing and Debugging Techniques
  • Memory Processes and Influences
  • Intelligent Tutoring Systems and Adaptive Learning
  • Genetics, Bioinformatics, and Biomedical Research

Recent publications by Craig Zilles include:

  • "Reevaluating the relationship between explaining, tracing, and writing skills in CS1 in a replication study" (2022), published in Computer Science Education
  • "Are We Fair?" (2022), published in Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
  • "Students' Perceptions and Behavior Related to Second-Chance Testing" (2021), published in 2021 IEEE Frontiers in Education Conference (FIE)
  • "On Students' Ability to Resolve their own Tracing Errors through Code Execution" (2022), published in Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
  • "Peer-grading 'Explain in Plain English'" (2022), published in Proceedings of the 53rd ACM Technical Symposium on Computer Science Education

Frequent co-authors in their work include:

  • Matthew West
  • David H. Smith
  • Binglin Chen
  • Max Fowler
  • Chinedu Emeka

Craig Zilles has contributed publications to several professional venues, with multiple papers presented at the Proceedings of the 53rd ACM Technical Symposium on Computer Science Education. Other publication venues include Computer Science Education, the 2021 IEEE Frontiers in Education Conference (FIE), the 2020 ASEE Virtual Annual Conference Content Access Proceedings, and arXiv (Cornell University).

Best Publications

  • A constraint-based god-object method for haptic display

    C.B. Zilles;J.K. Salisbury

  • Haptic rendering: programming touch interaction with virtual objects

    K. Salisbury;D. Brock;T. Massie;N. Swarup

  • Execution-based prediction using speculative slices

    Craig Zilles;Gurindar Sohi

  • Method and apparatus for determining forces to be applied to a user through a haptic interface

    Craig B. Zilles;J. Kenneth Salisbury;Thomas H. Massie;David Lawrence Brock

  • Master/Slave Speculative Parallelization

    Craig Zilles;Gurindar Sohi

  • Identifying important and difficult concepts in introductory computing courses using a delphi process

    Ken Goldman;Paul Gross;Cinda Heeren;Geoffrey Herman

  • Method and apparatus to quiesce a portion of a simultaneous multithreaded central processing unit

    Joel S. Emer;Rebecca L. Stamm;Bruce E. Edwards;Matthew H. Reilly

  • Using Hardware Memory Protection to Build a High-Performance, Strongly-Atomic Hybrid Transactional Memory

    Lee Baugh;Naveen Neelakantam;Craig Zilles

  • Blueshift: Designing processors for timing speculation from the ground up.

    Brian Greskamp;Lu Wan;Ulya R. Karpuzcu;Jeffrey J. Cook

  • Setting the Scope of Concept Inventories for Introductory Computing Subjects

    Ken Goldman;Paul Gross;Cinda Heeren;Geoffrey L. Herman

  • The use of multithreading for exception handling

    Craig B. Zilles;Joel S. Emer;Gurindar S. Sohi

  • Creating the digital logic concept inventory

    Geoffrey L. Herman;Michael C. Loui;Craig Zilles

  • PrairieLearn: Mastery-based Online Problem Solving with Adaptive Scoring and Recommendations Driven by Machine Learning

    Matthew West;Geoffrey L. Herman;Craig Zilles

  • A programmable co-processor for profiling

    C.B. Zilles;G.S. Sohi

  • Execution-based prediction using speculative slices

    Unknown

  • Hardware atomicity for reliable software speculation

    Naveen Neelakantam;Ravi Rajwar;Suresh Srinivas;Uma Srinivasan

  • Extending Hardware Transactional Memory to Support Non-busy Waiting and Non-transactional Actions

    Craig Zilles;Lee Baugh

  • Understanding the backward slices of performance degrading instructions

    Craig B. Zilles;Gurindar S. Sohi

  • Using hardware checkpoints to support software based speculation

    Naveen Neelakantam;Craig Zilles;Uma Srinivasan;Suresh Srinivas

  • Benchmark health considered harmful

    Craig B. Zilles

  • Using Hardware Memory Protection to Build a High-Performance, Strongly-Atomic Hybrid Transactional Memory

    Unknown

  • Targeted path profiling: lower overhead path profiling for staged dynamic optimization systems

    Rahul Joshi;Michael D. Bond;Craig Zilles

  • Describing the What and Why of Students’ Difficulties in Boolean Logic

    Geoffrey L. Herman;Michael C. Loui;Lisa Kaczmarczyk;Craig Zilles

Frequent Co-Authors

Ravi Rajwar
Ravi Rajwar Google (United States)
Gurindar S. Sohi
Gurindar S. Sohi University of Wisconsin–Madison
Timothy Bretl
Timothy Bretl University of Illinois at Urbana-Champaign
James W. Hicks
James W. Hicks University of Southern California
Darko Marinov
Darko Marinov University of Illinois at Urbana-Champaign
Grigore Rosu
Grigore Rosu University of Illinois at Urbana-Champaign
David Brooks
David Brooks Harvard University
Deming Chen
Deming Chen University of Illinois at Urbana-Champaign
Charles L. Tucker
Charles L. Tucker University of Illinois at Urbana-Champaign

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