| 2020 | ACSSC | Block-LMS and RLS adaptive filters using in-memory architectures. | Chandrasekhar Radhakrishnan, Sujan K. Gonugondla |
| 2020 | ICCAD | SWIPE: Enhancing Robustness of ReRAM Crossbars for In-memory Computing. | Sujan K. Gonugondla, Ameya D. Patil, Naresh R. Shanbhag |
| 2020 | ICCAD | Fundamental Limits on the Precision of In-memory Architectures. | Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag |
| 2019 | ACSSC | Adaptive Filtering in In-Memory-Based Architectures. | Chandrasekhar Radhakrishnan, Sujan K. Gonugondla |
| 2019 | ISCAS | An MRAM-Based Deep In-Memory Architecture for Deep Neural Networks. | Ameya D. Patil, Haocheng Hua, Sujan K. Gonugondla, Mingu Kang, Naresh R. Shanbhag |
| 2018 | ISCA | PROMISE: An End-to-End Design of a Programmable Mixed-Signal Accelerator for Machine-Learning Algorithms. | Prakalp Srivastava, Mingu Kang, Sujan K. Gonugondla, Sungmin Lim, Jungwook Choi, Vikram S. Adve, Nam Sung Kim, Naresh R. Shanbhag |
| 2018 | ISCAS | Energy-Efficient Deep In-memory Architecture for NAND Flash Memories. | Sujan K. Gonugondla, Mingu Kang, Yongjune Kim, Mark Helm, Sean Eilert, Naresh R. Shanbhag |
| 2016 | ICASSP | Perfect error compensation via algorithmic error cancellation. | Sujan K. Gonugondla, Byonghyo Shim, Naresh R. Shanbhag |
| 2015 | ICASSP | An energy-efficient memory-based high-throughput VLSI architecture for convolutional networks. | Mingu Kang, Sujan K. Gonugondla, Min-Sun Keel, Naresh R. Shanbhag |