Yonghong Yan
Scholar

Yonghong Yan

Google Scholar ID: 5gWChxIAAAAJ
University of North Carolina at Charlotte
Parallel and High Performance ComputingParallel Programming Languages and CompilersComputer Architecture and SystemsDistri
Citations & Impact
All-time
Citations
374
 
H-index
12
 
i10-index
14
 
Publications
20
 
Co-authors
14
list available
Resume (English only)
Academic Achievements
  • Publications: Details can be found on the website of his research group; Awards: Not specified; Patents: Not specified; Projects: Involved in multiple research projects related to parallel and high-performance computing.
Research Experience
  • Work Experience: Associate Professor in the Department of Computer Science at the University of North Carolina at Charlotte; Research Projects: Developing parallel programming systems (APIs, compilers, and runtime systems) based on OpenMP for heterogeneous systems; creating performance tools to measure, analyze, and visualize the execution of parallel applications to identify performance bottlenecks; developing machine learning and deep learning algorithms for 3D medical image processing, such as image registration and segmentation.
Education
  • Degree: Ph.D.; School: Not specified; Advisor: Not specified; Time: Not specified; Major: Not specified.
Background
  • Research Interests: Parallel and high-performance computing, parallel programming models and compiler techniques, computer architecture and systems. Professional Field: Computer science systems, with a focus on applications using multi-core CPUs, many-core GPUs, and clusters. Background: Associate Professor in the Department of Computer Science at the University of North Carolina at Charlotte, teaching both undergraduate and graduate courses including data structures, parallel programming, computer architecture, etc.
Miscellany
  • Personal Interests: Not specified; Hobbies: Not specified; Other: Member of the OpenMP Architectural Review Board (ARB) and the OpenMP language subcommittee, also serves as the director of the High Performance Computing and Systems Lab.