Ariful Khan
Biography
Dr. Arif Khan joined Pacific Northwest National Laboratory in August 2017. His research interest includes graph algorithm, high performance computing, approximation algorithm along with their applications in bioinformatics, social network and machine learning. His goal is to explore how approximation algorithms can solve big graph problems using leadership class supercomputers.
Arif graduated in 2017 with a Ph.D. in Computer Science from the Purdue University, West Lafayette, Indiana. His doctoral research was in the intersection between high performance computing and combinatorial scientific computing (CSC). He developed new approximation algorithms for b-Matching and b-Edgec Covers which are fundamental combinatorial problems with numerous applications in science and engineering. He also developed scalable software for these graph problems and demonstrated scalability across tens of thousands of processors on the DOE leadership class machines.
Arif graduated in 2017 with a Ph.D. in Computer Science from the Purdue University, West Lafayette, Indiana. His doctoral research was in the intersection between high performance computing and combinatorial scientific computing (CSC). He developed new approximation algorithms for b-Matching and b-Edgec Covers which are fundamental combinatorial problems with numerous applications in science and engineering. He also developed scalable software for these graph problems and demonstrated scalability across tens of thousands of processors on the DOE leadership class machines.
Presentations
Paper
Algorithms
TP
Best Paper Finalist
Best Student Paper Finalist
