| 2025 | ISPASS | Understanding the Performance Horizon of the Latest ML Workloads with NonGEMM Workloads. | Rachid Karami, Sheng-Chun Kao, Hyoukjun Kwon |
| 2023 | ASPLOS | FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. | Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, Tushar Krishna |
| 2022 | DATE | DiGamma: Domain-aware Genetic Algorithm for HW-Mapping Co-optimization for DNN Accelerators. | Sheng-Chun Kao, Michael Pellauer, Angshuman Parashar, Tushar Krishna |
| 2022 | HPCA | MAGMA: An Optimization Framework for Mapping Multiple DNNs on Multiple Accelerator Cores. | Sheng-Chun Kao, Tushar Krishna |
| 2022 | SIGMETRICS | A Formalism of DNN Accelerator Flexibility. | Sheng-Chun Kao, Hyoukjun Kwon, Michael Pellauer, Angshuman Parashar, Tushar Krishna |
| 2021 | ISPASS | E3: A HW/SW Co-design Neuroevolution Platform for Autonomous Learning in Edge Device. | Sheng-Chun Kao, Tushar Krishna |
| 2020 | ICCAD | GAMMA: Automating the HW Mapping of DNN Models on Accelerators via Genetic Algorithm. | Sheng-Chun Kao, Tushar Krishna |
| 2020 | MICRO | ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning. | Sheng-Chun Kao, Geonhwa Jeong, Tushar Krishna |