VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis. - Hadi Esmaeilzadeh; Soroush Ghodrati; Jie Gu 003; Shiyu Guo; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Rohan Mahapatra; Susmita Dey Manasi; Edwin Mascarenhas; Sachin S. Sapatnekar; Ravi Varadarajan; et al. (ICCAD, 2021)

Only Buffer When You Need To: Reducing On-chip GPU Traffic with Reconfigurable Local Atomic Buffers. - Preyesh Dalmia; Rohan Mahapatra; Matthew D. Sinclair (HPCA, 2022)

Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (MLCAD, 2022)

Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration. - Joon Kyung Kim; Byung Hoon Ahn; Sean Kinzer; Soroush Ghodrati; Rohan Mahapatra; Brahmendra Reddy Yatham; Shu-Ting Wang; Dohee Kim; Parisa Sarikhani; Babak Mahmoudi; Divya Mahajan 001; Jongse Park; et al. (IEEE Micro, 2022)

MESA: Microarchitecture Extensions for Spatial Architecture Generation. - Dong Kai Wang; Jiaqi Lou; Naiyin Jin; Edwin Mascarenhas; Rohan Mahapatra; Sean Kinzer; Soroush Ghodrati; Amir Yazdanbakhsh; Hadi Esmaeilzadeh; Nam Sung Kim (ISCA, 2023)

Domain-Specific Computational Storage for Serverless Computing. - Rohan Mahapatra; Soroush Ghodrati; Byung Hoon Ahn; Sean Kinzer; Shu-Ting Wang; Hanyang Xu 002; Lavanya Karthikeyan; Hardik Sharma; Amir Yazdanbakhsh; Mohammad Alian; Hadi Esmaeilzadeh (CoRR, 2023)

Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators. - Sean Kinzer; Soroush Ghodrati; Rohan Mahapatra; Byung Hoon Ahn; Edwin Mascarenhas; Xiaolong Li; Janarbek Matai; Liang Zhang; Hadi Esmaeilzadeh (CoRR, 2023)

Improving the Scalability of GPU Synchronization Primitives. - Preyesh Dalmia; Rohan Mahapatra; Jeremy Intan; Dan Negrut; Matthew D. Sinclair (IEEE Trans. Parallel Distributed Syst., 2023)

Tandem Processor: Grappling with Emerging Operators in Neural Networks. - Soroush Ghodrati; Sean Kinzer; Hanyang Xu 002; Rohan Mahapatra; Yoonsung Kim; Byung Hoon Ahn; Dong Kai Wang; Lavanya Karthikeyan; Amir Yazdanbakhsh; Jongse Park; Nam Sung Kim; Hadi Esmaeilzadeh (ASPLOS (2), 2024)

In-Storage Domain-Specific Acceleration for Serverless Computing. - Rohan Mahapatra; Soroush Ghodrati; Byung Hoon Ahn; Sean Kinzer; Shu-Ting Wang; Hanyang Xu 002; Lavanya Karthikeyan; Hardik Sharma; Amir Yazdanbakhsh; Mohammad Alian; Hadi Esmaeilzadeh (ASPLOS (2), 2024)

Data Motion Acceleration: Chaining Cross-Domain Multi Accelerators. - Shu-Ting Wang; Hanyang Xu 002; Amin Mamandipoor; Rohan Mahapatra; Byung Hoon Ahn; Soroush Ghodrati; Krishnan Kailas; Mohammad Alian; Hadi Esmaeilzadeh (HPCA, 2024)

An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (ACM Trans. Design Autom. Electr. Syst., 2024)

In-Storage Acceleration of Retrieval Augmented Generation as a Service. - Rohan Mahapatra; Harsha Santhanam; Christopher Priebe; Hanyang Xu 002; Hadi Esmaeilzadeh (ISCA, 2025)

Compiler Optimization via LLM Reasoning for Efficient Model Serving. - Sujun Tang; Christopher Priebe; Rohan Mahapatra; Lianhui Qin; Hadi Esmaeilzadeh (CoRR, 2025)