| 2026 | COMPSAC | Building Flexible, Scalable AI + X Pathways for STEM-Adjacent Disciplines. | Apan Qasem, Cindy Royal, Barbara Hewitt, Elise V. Lambert, Pratheesh Omana Sudhakaran |
| 2026 | COMPSAC | Does Semantic Heterogeneity Matter? Investigating Multi-Modal Feature Fusion for HPC Performance Modeling. | Alex Ford Schneider, Apan Qasem |
| 2025 | COMPSAC | Improving Energy Efficiency of Irregular Workloads with Transformers and Tabular Data Diffusion. | Mohammad Ali, Zarif Sadman, Apan Qasem |
| 2025 | COMPSAC | Autotuning CNN Workloads on the Edge: A Hybrid Approach with Cross-Domain Embeddings. | Trevor Hanz, Mohammad Ali, Zarif Sadman, Apan Qasem |
| 2025 | COMPSAC | A Multi-Tiered Autotuner for Portable Heterogeneous-Compute Interfaces. | Shahriar Ahmed Zisan, Mohammad Nooruddin, Apan Qasem |
| 2025 | HPCC | Accelerated Autotuning of Deep Learning Workloads with Pretrained Performance Models. | Trevor Hanz, Apan Qasem |
| 2023 | HiPC | ToUCH Virtual Faculty Development Workshops: Going Beyond a Webinar. | David P. Bunde, Apan Qasem |
| 2023 | HiPC | Workshop Invited Talks. | David P. Bunde, Apan Qasem, Prasun Dewan, Bayyapu Neelima |
| 2022 | SIGCSE | YODA: A Pedagogical Tool for Teaching Systems Concepts. | Apan Qasem |
| 2022 | SIGCSE | Heterogeneous Computing for Undergraduates: Introducing the ToUCH Module Repository. | Apan Qasem, David P. Bunde |
| 2021 | CCGRID | Characterizing Input-sensitivity in Tightly-Coupled Collaborative Graph Algorithms. | Jacob M. Hope, Mikel Gjergji, Johana Di Girolamo, Marco A. Alvarez, Apan Qasem |
| 2021 | SIGCSE | Teaching about Heterogeneous Computing. | David P. Bunde, Apan Qasem, Philip J. Schielke |
| 2019 | HPCC | Accelerating HotSpots in Deep Neural Networks on a CAPI-Based FPGA. | Md Syadus Sefat, Semih Aslan, Jeffrey W. Kellington, Apan Qasem |
| 2019 | SC | A Gentle Introduction to Heterogeneous Computing for CS1 Students. | Apan Qasem |
| 2017 | CGO | Characterizing data organization effects on heterogeneous memory architectures. | Apan Qasem, Ashwin M. Aji, Gregory Rodgers |
| 2017 | HPCC | Automatically Selecting Profitable Thread Block Sizes for Accelerated Kernels. | Tiffany A. Connors, Apan Qasem |
| 2017 | HPCC | A Machine Learning Approach to Automatic Creation of Architecture-Sensitive Performance Heuristics. | Biplab Kumar Saha, Tiffany A. Connors, Saami Rahman, Apan Qasem |
| 2015 | HPCC | Autotuning GPU-Accelerated QAP Solvers for Power and Performance. | Abhilash Chaparala, Clara Novoa, Apan Qasem |
| 2015 | HPCC | Maximizing Hardware Prefetch Effectiveness with Machine Learning. | Saami Rahman, Martin Burtscher, Ziliang Zong, Apan Qasem |
| 2015 | SIGCSE | A Module-based Approach to Adopting the 2013 ACM Curricular Recommendations on Parallel Computing. | Martin Burtscher, Wuxu Peng, Apan Qasem, Hongchi Shi, Dan E. Tamir, Heather Thiry |
| 2012 | CC | Automatic Restructuring of GPU Kernels for Exploiting Inter-thread Data Locality. | Swapneela Unkule, Christopher Shaltz, Apan Qasem |
| 2012 | PPoPP | Efficient execution of time-step computations with pipelined parallelism and inter-thread data locality optimizaitions. | Apan Qasem |
| 2011 | SC | Poster: register pressure aware code transformations on GPU. | Swapneela Unkule, Apan Qasem |
| 2010 | NPC | Exposing Tunable Parameters in Multi-threaded Numerical Code. | Apan Qasem, Jichi Guo, Faizur Rahman, Qing Yi |
| 2009 | HPCC | Balancing Locality and Parallelism on Shared-cache Mulit-core Systems. | Michael Jason Cade, Apan Qasem |
| 2008 | PDPTA | Evaluating an Early-stop Criterion and a Statistical Pruning Strategy of the Optimization Search Space. | Apan Qasem |
| 2006 | ICS | Profitable loop fusion and tiling using model-driven empirical search. | Apan Qasem, Ken Kennedy |
| 2001 | EuroPar | Using a Swap Instruction to Coalesce Loads and Stores. | Apan Qasem, David B. Whalley, Xin Yuan, Robert van Engelen |