Rate My Professor Apan Qasem

Apan Qasem is a Professor of Computer Science and Associate Chair in the Department of Computer Science at Texas State University, where he leads the Compilers Research Lab (CRL). His research specializes in high-performance computing, focusing on machine-learning compilers and runtime systems designed to improve programmer productivity, application performance, and energy efficiency on heterogeneous high-performance computing architectures. Qasem also works on computer science education, developing pedagogical tools and techniques to integrate emerging topics into the CS curriculum, make concepts accessible to non-majors, and increase participation, retention, and success of underrepresented groups in computing. He directs key projects such as STEM-CLEAR: Creating Contextualized Learning Pathways across cultural and academic boundaries, ToUCH: Teaching Undergraduates Collaborative and Heterogeneous Computing, Zeus DataScience Pathways, Intersectional Data Collection for Inclusive Computing, Meta Engineer in Residence Program, and TXST-TUES: Integrating Parallelism into the Undergraduate Curriculum.

Qasem earned his PhD from Rice University in 2007, with his dissertation supervised by Ken Kennedy and John Mellor-Crummey. His career includes serving as Visiting Scholar at AMD Research in Austin from 2016 to 2019 as a member of the PathForward team in the Exascale Computing Project, and as Visiting Professor at the University of Edinburgh School of Informatics in 2015. He has received the National Science Foundation CAREER Award in 2013 and the IBM Faculty Award in 2008, along with research funding from the Department of Energy, Department of Health and Human Services, Semiconductor Research Consortium, AMD, NVIDIA, and Intel. Key publications include "Profitable Loop Fusion and Tiling Using Model-Driven Empirical Search" (2006), "Automatic Tuning of Whole Applications Using Direct Search and a Performance-Based Transformation System" (2006), "Understanding Stencil Code Performance on Multicore Architectures" (2011), "Maximizing Hardware Prefetch Effectiveness with Machine Learning" (2015), and "Automatic Restructuring of GPU Kernels for Exploiting Inter-Thread Data Locality" (2012). His teaching record encompasses CS1428: Foundations of Computer Science (2007-2019), CS3339: Computer Architecture (2010-present), CS4318: Program Translators and CS5331: Crafting Compilers (2008-2017), CS4350: Unix Systems Programming (2008, 2010-2012), and CS7331: High-Performance Computing (2017-present).