Jun
Shirako

General Information

Email:
shirako@gatech.edu
Phone:
404-385-4746
Location - Building:
KACB
Location - Room:
2366
Roles:
Research Faculty
Primary Unit:
College of Computing
Website URL
LinkedIn

Details

Degrees with subject and Postdoc Experience:
Degree Type
Postdoctoral Scholar
Subject
Computer Science
Year
2008-2010
Institution
Rice University
Location
Houston
Degree Type
Postdoctoral Scholar
Subject
Computer Science
Year
2007-2008
Institution
Waseda University
Location
Tokyo
Degree Type
Ph.D
Subject
Computer Science
Year
2007
Institution
Waseda University
Location
Tokyo
Degree Type
M.S
Subject
Electrical Engineering
Year
2004
Institution
Waseda University
Location
Tokyo
Degree Type
B.S
Subject
Electrical Engineering
Year
2002
Institution
Waseda University
Location
Tokyo
Statement of Research Interests:

Dr. Shirako's research focuses on parallel programming languages, optimizing compilers, and synchronization runtimes. This includes high-productivity programming languages, system-agnostic parallelism specifications, performance- and productivity-oriented programming systems, hybrid compiler-driven and AI-assisted code optimizations, and efficient synchronization and coordination algorithms for parallel programs.

Statement of Teaching Interests:

Dr. Shirako's teaching is focused on fundamental parallel computing at the undergraduate and graduate levels, including parallel programming, compiler optimizations, and parallel computer architectures. As a research faculty member, Dr. Shirako mentors both undergraduate and graduate students through their research projects.

Selection of recent research, scholarly, and creative activities:

"Automatic Generation of Actor-based Parallelism from Shared Memory Parallel Programs." J. Shirako and V. Sarkar. November 2025. doi: 10.1109/PACT65351.2025.00030
"Intrepydd: Toward Performance, Productivity, and Portability for Massive Heterogeneous Parallelism." J. Shirako, T. Zhou, and A. Hayashi. October 2024. doi: 10.1007/978-3-031-97492-2_7
"APPy: Annotated Parallelism for Python on GPUs." T. Zhou, J. Shirako, and V. Sarkar. March 2024. doi: 10.1145/3640537.3641575
"Concrete Type Inference for Code Optimization Using Machine Learning with SMT Solving." F. Ye, J. Zhao, J. Shirako, and V. Sarkar. October 2023. doi: 10.1145/3622825
"Dynamic Determinacy Race Detection for Task-Parallel Programs with Promises." F. Jin, L. Yu, T. Cogumbreiro, J. Shirako, and V. Sarkar. July 2023. doi: 10.4230/LIPIcs.ECOOP.2023.13
"Automatic Parallelization of Python programs for Distributed Heterogeneous Computing." J. Shirako, A. Hayashi, S. Paul, A. Tumanov, and V. Sarkar. August 2022. doi: 10.1007/978-3-031-12597-3_22