Real time emulations: foundation and applications. - Azalia Mirhoseini; Yousra Alkabani; Farinaz Koushanfar (DAC, 2010)

A Unified Submodular Framework for Multimodal IC Trojan Detection. - Farinaz Koushanfar; Azalia Mirhoseini; Yousra Alkabani (Information Hiding, 2010)

HypoEnergy. Hybrid supercapacitor-battery power-supply optimization for Energy efficiency. - Azalia Mirhoseini; Farinaz Koushanfar (DATE, 2011)

Hybrid heterogeneous energy supply networks. - Farinaz Koushanfar; Azalia Mirhoseini (ISCAS, 2011)

Learning to manage combined energy supply systems. - Azalia Mirhoseini; Farinaz Koushanfar (ISLPED, 2011)

A Unified Framework for Multimodal Submodular Integrated Circuits Trojan Detection. - Farinaz Koushanfar; Azalia Mirhoseini (IEEE Trans. Inf. Forensics Secur., 2011)

Coding-based energy minimization for phase change memory. - Azalia Mirhoseini; Miodrag Potkonjak; Farinaz Koushanfar (DAC, 2012)

Automated checkpointing for enabling intensive applications on energy harvesting devices. - Azalia Mirhoseini; Ebrahim M. Songhori; Farinaz Koushanfar (ISLPED, 2013)

Idetic: A high-level synthesis approach for enabling long computations on transiently-powered ASICs. - Azalia Mirhoseini; Ebrahim M. Songhori; Farinaz Koushanfar (PerCom, 2013)

AHEAD: automated framework for hardware accelerated iterative data analysis. - Ebrahim M. Songhori; Azalia Mirhoseini; Xuyang Lu; Farinaz Koushanfar (DATE, 2015)

SSketch: An Automated Framework for Streaming Sketch-Based Analysis of Big Data on FPGA. - Bita Darvish Rouhani; Ebrahim M. Songhori; Azalia Mirhoseini; Farinaz Koushanfar (FCCM, 2015)

DA Systemization of Knowledge: A Catalog of Prior Forward-Looking Initiatives. - Farinaz Koushanfar; Azalia Mirhoseini; Gang Qu 001; Zhiru Zhang (ICCAD, 2015)

Flexible Transformations For Learning Big Data. - Azalia Mirhoseini; Ebrahim M. Songhori; Bita Darvish Rouhani; Farinaz Koushanfar (SIGMETRICS, 2015)

RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets. - Azalia Mirhoseini; Eva L. Dyer; Ebrahim M. Songhori; Richard G. Baraniuk; Farinaz Koushanfar (CoRR, 2015)

oASIS: Adaptive Column Sampling for Kernel Matrix Approximation. - Raajen Patel; Thomas A. Goldstein; Eva L. Dyer; Azalia Mirhoseini; Richard G. Baraniuk (CoRR, 2015)

Phase Change Memory Write Cost Minimization by Data Encoding. - Azalia Mirhoseini; Miodrag Potkonjak; Farinaz Koushanfar (IEEE J. Emerg. Sel. Topics Circuits Syst., 2015)

Going deeper than deep learning for massive data analytics under physical constraints. - Bita Darvish Rouhani; Azalia Mirhoseini; Farinaz Koushanfar (CODES+ISSS, 2016)

Perform-ML: performance optimized machine learning by platform and content aware customization. - Azalia Mirhoseini; Bita Darvish Rouhani; Ebrahim M. Songhori; Farinaz Koushanfar (DAC, 2016)

CryptoML: Secure outsourcing of big data machine learning applications. - Azalia Mirhoseini; Ahmad-Reza Sadeghi; Farinaz Koushanfar (HOST, 2016)

DeLight: Adding Energy Dimension To Deep Neural Networks. - Bita Darvish Rouhani; Azalia Mirhoseini; Farinaz Koushanfar (ISLPED, 2016)

Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition. - Raajen Patel; Tom Goldstein; Eva L. Dyer; Azalia Mirhoseini; Richard G. Baraniuk (SDM, 2016)

Chime: Checkpointing Long Computations on Interm ittently Energized IoT Devices. - Azalia Mirhoseini; Bita Darvish Rouhani; Ebrahim M. Songhori; Farinaz Koushanfar (IEEE Trans. Multi Scale Comput. Syst., 2016)

Automated Real-Time Analysis of Streaming Big and Dense Data on Reconfigurable Platforms. - Bita Darvish Rouhani; Azalia Mirhoseini; Ebrahim M. Songhori; Farinaz Koushanfar (ACM Trans. Reconfigurable Technol. Syst., 2016)

Deep3: Leveraging Three Levels of Parallelism for Efficient Deep Learning. - Bita Darvish Rouhani; Azalia Mirhoseini; Farinaz Koushanfar (DAC, 2017)

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. - Noam Shazeer; Azalia Mirhoseini; Krzysztof Maziarz; Andy Davis; Quoc V. Le; Geoffrey E. Hinton; Jeff Dean (ICLR (Poster), 2017)

Device Placement Optimization with Reinforcement Learning. - Azalia Mirhoseini; Hieu Pham 001; Quoc V. Le; Benoit Steiner; Rasmus Larsen 002; Yuefeng Zhou; Naveen Kumar; Mohammad Norouzi 002; Samy Bengio; Jeff Dean (ICML, 2017)

ExtDict: Extensible Dictionaries for Data- and Platform-Aware Large-Scale Learning. - Azalia Mirhoseini; Bita Darvish Rouhani; Ebrahim M. Songhori; Farinaz Koushanfar (IPDPS Workshops, 2017)

TinyDL: Just-in-time deep learning solution for constrained embedded systems. - Bita Darvish Rouhani; Azalia Mirhoseini; Farinaz Koushanfar (ISCAS, 2017)

RISE: An Automated Framework for Real-Time Intelligent Video Surveillance on FPGA. - Bita Darvish Rouhani; Azalia Mirhoseini; Farinaz Koushanfar (ACM Trans. Embed. Comput. Syst., 2017)

A Hierarchical Model for Device Placement. - Azalia Mirhoseini; Anna Goldie; Hieu Pham 001; Benoit Steiner; Quoc V. Le; Jeff Dean (ICLR (Poster), 2018)

Introduction to ParLearning 2018. - Henri E. Bal; Arindam Pal 001; Azalia Mirhoseini; Thomas P. Parnell (IPDPS Workshops, 2018)

ParLearning 2018 Invited Talk 2. - Azalia Mirhoseini (IPDPS Workshops, 2018)

Deep Mixture of Experts via Shallow Embedding. - Xin Wang 066; Fisher Yu 001; Ruth Wang; Yi-An Ma; Azalia Mirhoseini; Trevor Darrell; Joseph E. Gonzalez (CoRR, 2018)

RankMap: A Framework for Distributed Learning From Dense Data Sets. - Azalia Mirhoseini; Eva L. Dyer; Ebrahim M. Songhori; Richard G. Baraniuk; Farinaz Koushanfar (IEEE Trans. Neural Networks Learn. Syst., 2018)

Deep Mixture of Experts via Shallow Embedding. - Xin Wang 066; Fisher Yu 001; Lisa Dunlap; Yi-An Ma; Ruth Wang; Azalia Mirhoseini; Trevor Darrell; Joseph E. Gonzalez (UAI, 2019)

GAP: Generalizable Approximate Graph Partitioning Framework. - Azade Nazi; Will Hang; Anna Goldie; Sujith Ravi; Azalia Mirhoseini (CoRR, 2019)

Reinforcement Learning Driven Heuristic Optimization. - Qingpeng Cai 001; Will Hang; Azalia Mirhoseini; George Tucker; Jingtao Wang; Wei Wei (CoRR, 2019)

GDP: Generalized Device Placement for Dataflow Graphs. - Yanqi Zhou; Sudip Roy 002; AmirAli Abdolrashidi; Daniel Lin-Kit Wong; Peter C. Ma; Qiumin Xu; Ming Zhong; Hanxiao Liu; Anna Goldie; Azalia Mirhoseini; James Laudon (CoRR, 2019)

Generalized Clustering by Learning to Optimize Expected Normalized Cuts. - Azade Nazi; Will Hang; Anna Goldie; Sujith Ravi; Azalia Mirhoseini (CoRR, 2019)

Placement Optimization with Deep Reinforcement Learning. - Anna Goldie; Azalia Mirhoseini (ISPD, 2020)

Transferable Graph Optimizers for ML Compilers. - Yanqi Zhou; Sudip Roy 002; AmirAli Abdolrashidi; Daniel Wong 001; Peter C. Ma; Qiumin Xu; Hanxiao Liu; Mangpo Phitchaya Phothilimtha; Shen Wang; Anna Goldie; Azalia Mirhoseini; James Laudon (NeurIPS, 2020)

Chip Placement with Deep Reinforcement Learning. - Azalia Mirhoseini; Anna Goldie; Mustafa Yazgan; Joe W. J. Jiang; Ebrahim M. Songhori; Shen Wang; Young-Joon Lee; Eric Johnson; Omkar Pathak; Sungmin Bae; Azade Nazi; Jiwoo Pak; et al. (CoRR, 2020)

A Single-Shot Generalized Device Placement for Large Dataflow Graphs. - Yanqi Zhou; Sudip Roy 002; AmirAli Abdolrashidi; Daniel Lin-Kit Wong; Peter C. Ma; Qiumin Xu; Azalia Mirhoseini; James Laudon (IEEE Micro, 2020)

Reinforcement Learning for Placement Optimization. - Anna Goldie; Azalia Mirhoseini (ISPD, 2021)

Delving into Macro Placement with Reinforcement Learning. - Zixuan Jiang; Ebrahim M. Songhori; Shen Wang; Anna Goldie; Azalia Mirhoseini; Joe W. J. Jiang; Young-Joon Lee; David Z. Pan (MLCAD, 2021)

Representing Long-Range Context for Graph Neural Networks with Global Attention. - Zhanghao Wu; Paras Jain 001; Matthew A. Wright; Azalia Mirhoseini; Joseph E. Gonzalez; Ion Stoica (NeurIPS, 2021)

A Full-stack Accelerator Search Technique for Vision Applications. - Dan Zhang 004; Safeen Huda; Ebrahim M. Songhori; Quoc V. Le; Anna Goldie; Azalia Mirhoseini (CoRR, 2021)

SAFELearn: Secure Aggregation for private FEderated Learning. - Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Helen Möllering; Thien Duc Nguyen; Phillip Rieger; Ahmad-Reza Sadeghi; Thomas Schneider 003; Hossein Yalame; Shaza Zeitouni (IACR Cryptol. ePrint Arch., 2021)

FLGUARD: Secure and Private Federated Learning. - Thien Duc Nguyen; Phillip Rieger; Hossein Yalame; Helen Möllering; Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Ahmad-Reza Sadeghi; Thomas Schneider 003; Shaza Zeitouni (IACR Cryptol. ePrint Arch., 2021)

A graph placement methodology for fast chip design. - Azalia Mirhoseini; Anna Goldie; Mustafa Yazgan; Joe Wenjie Jiang; Ebrahim M. Songhori; Shen Wang; Young-Joon Lee; Eric Johnson; Omkar Pathak; Azade Nazi; Jiwoo Pak; Andy Tong; et al. (Nat., 2021)

Reinforcement Learning for Electronic Design Automation: Case Studies and Perspectives: (Invited Paper). - Ahmet Faruk Budak; Zixuan Jiang; Keren Zhu 001; Azalia Mirhoseini; Anna Goldie; David Z. Pan (ASP-DAC, 2022)

A full-stack search technique for domain optimized deep learning accelerators. - Dan Zhang 004; Safeen Huda; Ebrahim M. Songhori; Kartik Prabhu; Quoc V. Le; Anna Goldie; Azalia Mirhoseini (ASPLOS, 2022)

Learning to Design Accurate Deep Learning Accelerators with Inaccurate Multipliers. - Paras Jain 001; Safeen Huda; Martin Maas 001; Joseph E. Gonzalez; Ion Stoica; Azalia Mirhoseini (DATE, 2022)

Scalability and Generalization of Circuit Training for Chip Floorplanning. - Summer Yue; Ebrahim M. Songhori; Joe Wenjie Jiang; Toby Boyd; Anna Goldie; Azalia Mirhoseini; Sergio Guadarrama (ISPD, 2022)

A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules. - Xinfeng Xie; Prakash Prabhu; Ulysse Beaugnon; Phitchaya Mangpo Phothilimthana; Sudip Roy 002; Azalia Mirhoseini; Eugene Brevdo; James Laudon; Yanqi Zhou (MLSys, 2022)

FLAME: Taming Backdoors in Federated Learning. - Thien Duc Nguyen; Phillip Rieger; Huili Chen; Hossein Yalame; Helen Möllering; Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Shaza Zeitouni; Farinaz Koushanfar; Ahmad-Reza Sadeghi; et al. (USENIX Security Symposium, 2022)

Measuring Progress on Scalable Oversight for Large Language Models. - Samuel R. Bowman; Jeeyoon Hyun; Ethan Perez; Edwin Chen; Craig Pettit; Scott Heiner; Kamile Lukosiute; Amanda Askell; Andy Jones; Anna Chen; Anna Goldie; Azalia Mirhoseini; et al. (CoRR, 2022)

Constitutional AI: Harmlessness from AI Feedback. - Yuntao Bai; Saurav Kadavath; Sandipan Kundu; Amanda Askell; Jackson Kernion; Andy Jones; Anna Chen; Anna Goldie; Azalia Mirhoseini; Cameron McKinnon; Carol Chen; Catherine Olsson; et al. (CoRR, 2022)

Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. - Neel Guha; Mayee F. Chen; Kush Bhatia; Azalia Mirhoseini; Frederic Sala; Christopher Ré (NeurIPS, 2023)

The Capacity for Moral Self-Correction in Large Language Models. - Deep Ganguli; Amanda Askell; Nicholas Schiefer; Thomas I. Liao; Kamile Lukosiute; Anna Chen; Anna Goldie; Azalia Mirhoseini; Catherine Olsson; Danny Hernandez; Dawn Drain; Dustin Li; et al. (CoRR, 2023)

Specific versus General Principles for Constitutional AI. - Sandipan Kundu; Yuntao Bai; Saurav Kadavath; Amanda Askell; Andrew Callahan; Anna Chen; Anna Goldie; Avital Balwit; Azalia Mirhoseini; Brayden McLean; Catherine Olsson; Cassie Evraets; et al. (CoRR, 2023)

Hydragen: High-Throughput LLM Inference with Shared Prefixes. - Jordan Juravsky; Bradley C. A. Brown; Ryan Ehrlich; Daniel Y. Fu; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models. - Je-Yong Lee; Donghyun Lee; Genghan Zhang; Mo Tiwari; Azalia Mirhoseini (CoRR, 2024)

CHESS: Contextual Harnessing for Efficient SQL Synthesis. - Shayan Talaei; Mohammadreza Pourreza; Yu-Chen Chang; Azalia Mirhoseini; Amin Saberi (CoRR, 2024)

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. - Bradley C. A. Brown; Jordan Juravsky; Ryan Ehrlich; Ronald Clark; Quoc V. Le; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

Archon: An Architecture Search Framework for Inference-Time Techniques. - Jon Saad-Falcon; Adrian Gamarra Lafuente; Shlok Natarajan; Nahum Maru; Hristo Todorov; Etash Kumar Guha; Estefany Kelly Buchanan; Mayee F. Chen; Neel Guha; Christopher Ré; Azalia Mirhoseini (CoRR, 2024)

That Chip Has Sailed: A Critique of Unfounded Skepticism Around AI for Chip Design. - Anna Goldie; Azalia Mirhoseini; Jeff Dean (CoRR, 2024)

CodeMonkeys: Scaling Test-Time Compute for Software Engineering. - Ryan Ehrlich; Bradley C. A. Brown; Jordan Juravsky; Ronald Clark; Christopher Ré; Azalia Mirhoseini (CoRR, 2025)

KernelBench: Can LLMs Write Efficient GPU Kernels? - Anne Ouyang; Simon Guo 004; Simran Arora; Alex L. Zhang; William Hu; Christopher Ré; Azalia Mirhoseini (CoRR, 2025)

How Do Large Language Monkeys Get Their Power (Laws)? - Rylan Schaeffer; Joshua Kazdan; John Hughes; Jordan Juravsky; Sara Price; Aengus Lynch; Erik Jones; Robert Kirk; Azalia Mirhoseini; Sanmi Koyejo (CoRR, 2025)

Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL. - Mohammadreza Pourreza; Shayan Talaei; Ruoxi Sun 002; Xingchen Wan; Hailong Li; Azalia Mirhoseini; Amin Saberi; Sercan Ö. Arik (CoRR, 2025)

Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use. - Anna Goldie; Azalia Mirhoseini; Hao Zhou; Irene Cai; Christopher D. Manning (CoRR, 2025)

Think, Prune, Train, Improve: Scaling Reasoning without Scaling Models. - Caia Costello; Simon Guo 004; Anna Goldie; Azalia Mirhoseini (CoRR, 2025)

Exploring Diffusion Transformer Designs via Grafting. - Keshigeyan Chandrasegaran; Michael Poli; Daniel Y. Fu; Dongjun Kim; Lea M. Hadzic; Manling Li; Agrim Gupta; Stefano Massaroli; Azalia Mirhoseini; Juan Carlos Niebles; Stefano Ermon; Li Fei-Fei 001 (CoRR, 2025)

SPRINT: Enabling Interleaved Planning and Parallelized Execution in Reasoning Models. - Emil Biju; Shayan Talaei; Zhemin Huang; Mohammadreza Pourreza; Azalia Mirhoseini; Amin Saberi (CoRR, 2025)

Cartridges: Lightweight and general-purpose long context representations via self-study. - Sabri Eyuboglu; Ryan Ehrlich; Simran Arora; Neel Guha; Dylan Zinsley; Emily Liu; Will Tennien; Atri Rudra; James Zou 001; Azalia Mirhoseini; Christopher Ré (CoRR, 2025)

RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models. - Jacky Kwok; Christopher Agia; Rohan Sinha; Matthew Foutter; Shulu Li; Ion Stoica; Azalia Mirhoseini; Marco Pavone 001 (CoRR, 2025)

Shrinking the Generation-Verification Gap with Weak Verifiers. - Jon Saad-Falcon; Estefany Kelly Buchanan; Mayee F. Chen; Tzu-Heng Huang; Brendan McLaughlin; Tanvir Bhathal; Shang Zhu; Ben Athiwaratkun; Frederic Sala; Scott W. Linderman; Azalia Mirhoseini; Christopher Ré (CoRR, 2025)

Training of physical neural networks. - Ali Momeni 002; Babak Rahmani; Benjamin Scellier; Logan G. Wright; Peter L. McMahon; Clara C. Wanjura; Yuhang Li; Anas Skalli; Natalia G. Berloff; Tatsuhiro Onodera; Ilker Oguz; Francesco Morichetti; et al. (Nat., 2025)