Navigating the maze of graph analytics frameworks using massive graph datasets. - Nadathur Satish; Narayanan Sundaram; Md. Mostofa Ali Patwary; Jiwon Seo 002; Jongsoo Park; Muhammad Amber Hassaan; Shubho Sengupta; Zhaoming Yin; Pradeep Dubey (SIGMOD Conference, 2014)

Deep Speech: Scaling up end-to-end speech recognition. - Awni Y. Hannun; Carl Case; Jared Casper; Bryan Catanzaro; Greg Diamos; Erich Elsen; Ryan Prenger; Sanjeev Satheesh; Shubho Sengupta; Adam Coates 002; Andrew Y. Ng (CoRR, 2014)

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Rishita Anubhai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; Erich Elsen; Jesse H. Engel; et al. (CoRR, 2015)

Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. - Dario Amodei; Sundaram Ananthanarayanan; Rishita Anubhai; Jingliang Bai; Eric Battenberg; Carl Case; Jared Casper; Bryan Catanzaro; Jingdong Chen; Mike Chrzanowski; Adam Coates 002; Greg Diamos; et al. (ICML, 2016)

Persistent RNNs: Stashing Recurrent Weights On-Chip. - Greg Diamos; Shubho Sengupta; Bryan Catanzaro; Mike Chrzanowski; Adam Coates 002; Erich Elsen; Jesse H. Engel; Awni Y. Hannun; Sanjeev Satheesh (ICML, 2016)

Exploring Sparsity in Recurrent Neural Networks. - Sharan Narang; Greg Diamos; Shubho Sengupta; Erich Elsen (ICLR (Poster), 2017)

Deep Voice: Real-time Neural Text-to-Speech. - Sercan Ömer Arik; Mike Chrzanowski; Adam Coates 002; Gregory Frederick Diamos; Andrew Gibiansky; Yongguo Kang; Xian Li; John Miller 001; Andrew Y. Ng; Jonathan Raiman; Shubho Sengupta; Mohammad Shoeybi (ICML, 2017)

Deep Voice: Real-time Neural Text-to-Speech. - Sercan Ömer Arik; Mike Chrzanowski; Adam Coates 002; Greg Diamos; Andrew Gibiansky; Yongguo Kang; Xian Li; John Miller 001; Jonathan Raiman; Shubho Sengupta; Mohammad Shoeybi (CoRR, 2017)

ELF OpenGo: an analysis and open reimplementation of AlphaZero. - Yuandong Tian; Jerry Ma; Qucheng Gong; Shubho Sengupta; Zhuoyuan Chen; James Pinkerton; Larry Zitnick (ICML, 2019)

Privacy-Preserving Contextual Bandits. - Awni Y. Hannun; Brian Knott; Shubho Sengupta; Laurens van der Maaten (CoRR, 2019)

Private Matching for Compute. - Prasad Buddhavarapu; Andrew Knox; Payman Mohassel; Shubho Sengupta; Erik Taubeneck; Vlad Vlaskin (IACR Cryptol. ePrint Arch., 2020)

Privacy-Preserving Randomized Controlled Trials: A Protocol for Industry Scale Deployment. - Mahnush Movahedi; Benjamin M. Case; James Honaker; Andrew Knox; Li Li; Yiming Paul Li; Sanjay Saravanan; Shubho Sengupta; Erik Taubeneck (CCSW, 2021)

CrypTen: Secure Multi-Party Computation Meets Machine Learning. - Brian Knott; Shobha Venkataraman; Awni Y. Hannun; Shubho Sengupta; Mark Ibrahim; Laurens van der Maaten (NeurIPS, 2021)

Private Randomized Controlled Trials: A Protocol for Industry Scale Deployment. - Mahnush Movahedi; Benjamin M. Case; Andrew Knox; Li Li; Yiming Paul Li; Sanjay Saravanan; Shubho Sengupta; Erik Taubeneck (CoRR, 2021)

Multi-key Private Matching for Compute. - Prasad Buddhavarapu; Benjamin M. Case; Logan Gore; Andrew Knox; Payman Mohassel; Shubho Sengupta; Erik Taubeneck; Min Xue (IACR Cryptol. ePrint Arch., 2021)

Parallel Composition of Weighted Finite-State Transducers. - Shubho Sengupta; Vineel Pratap; Awni Y. Hannun (ICASSP, 2022)

Large Language Models for Software Engineering: Survey and Open Problems. - Angela Fan; Beliz Gokkaya; Mark Harman; Mitya Lyubarskiy; Shubho Sengupta; Shin Yoo; Jie M. Zhang (ICSE-FoSE, 2023)

Assured LLM-Based Software Engineering. - Nadia Alshahwan; Mark Harman; Inna Harper; Alexandru Marginean; Shubho Sengupta; Eddy Wang (InteNSE, 2024)

Automated Unit Test Improvement using Large Language Models at Meta. - Nadia Alshahwan; Jubin Chheda; Anastasia Finogenova; Beliz Gokkaya; Mark Harman; Inna Harper; Alexandru Marginean; Shubho Sengupta; Eddy Wang (SIGSOFT FSE Companion, 2024)

Curl: Private LLMs through Wavelet-Encoded Look-Up Tables. - Manuel B. Santos; Dimitris Mouris; Mehmet Ugurbil; Stanislaw Jarecki; José Reis; Shubho Sengupta; Miguel de Vega (IACR Cryptol. ePrint Arch., 2024)

Delegated Private Matching For Compute. - Dimitris Mouris; Daniel Masny; Ni Trieu; Shubho Sengupta; Prasad Buddhavarapu; Benjamin M. Case (Proc. Priv. Enhancing Technol., 2024)

Revisiting Reliability in Large-Scale Machine Learning Research Clusters. - Apostolos Kokolis; Michael Kuchnik; John Hoffman; Adithya Kumar; Parth Malani; Faye Ma; Zachary DeVito; Shubho Sengupta; Kalyan Saladi; Carole-Jean Wu (HPCA, 2025)

Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges. - Mark Harman; Peter W. O'Hearn; Shubho Sengupta (SIGSOFT FSE Companion, 2025)

Mutation-Guided LLM-based Test Generation at Meta. - Mark Harman; Jillian Ritchey; Inna Harper; Shubho Sengupta; Ke Mao; Abhishek Gulati; Christopher Foster; Hervé Robert (SIGSOFT FSE Companion, 2025)

Fission: Distributed Privacy-Preserving Large Language Model Inference. - Mehmet Ugurbil; Dimitris Mouris; Manuel B. Santos; José Cabrero-Holgueras; Miguel de Vega; Shubho Sengupta (IACR Cryptol. ePrint Arch., 2025)