| 2026 | ISPASS | Situla: Studying the Interplay of Sparse Formats and CPU/GPU Libraries. | Amirmahdi Namjoo, Sanjali Yadav, Helya Hosseini, Bahar Asgari |
| 2025 | DAC | Pipirima: Predicting Patterns in Sparsity to Accelerate Matrix Algebra. | Ubaid Bakhtiar, Donghyeon Joo, Bahar Asgari |
| 2025 | ISPASS | La Superba: Leveraging a Self-Comparison Method to Understand the Performance Benefits of Sparse Acceleration Optimizations. | Nebil Ozer, Gregory Kollmer, Ramyad Hadidi, Bahar Asgari |
| 2025 | MICRO | Chasoň: Supporting Cross HBM Channel Data Migration to Enable Efficient Sparse Algebraic Acceleration. | Ubaid Bakhtiar, Amirmahdi Namjoo, Bahar Asgari |
| 2025 | MICRO | Coruscant: Co-Designing GPU Kernel and Sparse Tensor Core to Advocate Unstructured Sparsity in Efficient LLM Inference. | Donghyeon Joo, Helya Hosseini, Ramyad Hadidi, Bahar Asgari |
| 2025 | MICRO | Bootes: Boosting the Efficiency of Sparse Accelerators Using Spectral Clustering. | Sanjali Yadav, Bahar Asgari |
| 2025 | MICRO | Misam: Machine Learning Assisted Dataflow Selection in Accelerators for Sparse Matrix Multiplication. | Sanjali Yadav, Amirmahdi Namjoo, Bahar Asgari |
| 2024 | ASPLOS | GUST: Graph Edge-Coloring Utilization for Accelerating Sparse Matrix Vector Multiplication. | Armin Gerami, Bahar Asgari |
| 2024 | MICRO | Acamar: A Dynamically Reconfigurable Scientific Computing Accelerator for Robust Convergence and Minimal Resource Underutilization. | Ubaid Bakhtiar, Helya Hosseini, Bahar Asgari |
| 2022 | FPL | Maia: Matrix Inversion Acceleration Near Memory. | Bahar Asgari, Dheeraj Ramchandani, Amaan Marfatia, Hyesoon Kim |
| 2021 | ASPLOS | Quantifying the design-space tradeoffs in autonomous drones. | Ramyad Hadidi, Bahar Asgari, Sam Jijina, Adriana Amyette, Nima Shoghi, Hyesoon Kim |
| 2021 | HPCA | FAFNIR: Accelerating Sparse Gathering by Using Efficient Near-Memory Intelligent Reduction. | Bahar Asgari, Ramyad Hadidi, Jiashen Cao, Da Eun Shim, Sung Kyu Lim, Hyesoon Kim |
| 2020 | DAC | PISCES: Power-Aware Implementation of SLAM by Customizing Efficient Sparse Algebra. | Bahar Asgari, Ramyad Hadidi, Nima Shoghi Ghaleshahi, Hyesoon Kim |
| 2020 | DATE | ASCELLA: Accelerating Sparse Computation by Enabling Stream Accesses to Memory. | Bahar Asgari, Ramyad Hadidi, Hyesoon Kim |
| 2020 | FCCM | Proposing a Fast and Scalable Systolic Array for Matrix Multiplication. | Bahar Asgari, Ramyad Hadidi, Hyesoon Kim |
| 2020 | HPCA | ALRESCHA: A Lightweight Reconfigurable Sparse-Computation Accelerator. | Bahar Asgari, Ramyad Hadidi, Tushar Krishna, Hyesoon Kim, Sudhakar Yalamanchili |
| 2020 | ICCD | MEISSA: Multiplying Matrices Efficiently in a Scalable Systolic Architecture. | Bahar Asgari, Ramyad Hadidi, Hyesoon Kim |
| 2019 | DAC | LODESTAR: Creating Locally-Dense CNNs for Efficient Inference on Systolic Arrays. | Bahar Asgari, Ramyad Hadidi, Hyesoon Kim, Sudhakar Yalamanchili |
| 2019 | DSN | SuDoku: Tolerating High-Rate of Transient Failures for Enabling Scalable STTRAM. | Prashant J. Nair, Bahar Asgari, Moinuddin K. Qureshi |
| 2019 | FPL | Capella: Customizing Perception for Edge Devices by Efficiently Allocating FPGAs to DNNs. | Younmin Bae, Ramyad Hadidi, Bahar Asgari, Jiashen Cao, Hyesoon Kim |
| 2018 | ISPASS | Performance Implications of NoCs on 3D-Stacked Memories: Insights from the Hybrid Memory Cube. | Ramyad Hadidi, Bahar Asgari, Jeffrey S. Young, Burhan Ahmad Mudassar, Kartikay Garg, Tushar Krishna, Hyesoon Kim |