| 2025 | ICDE | Agentic Workflows for Extraction of Access Control Matrices from Policy Documents. | Pranav Subramaniam, Sanjay Krishnan |
| 2024 | CIDR | Towards Resource-adaptive Query Execution in Cloud Native Databases. | Rui Liu, Jun Hyuk Chang, Riki Otaki, Zhe Heng Eng, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan |
| 2024 | ICDE | Riveter: Adaptive Query Suspension and Resumption Framework for Cloud Native Databases. | Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan |
| 2024 | ICDE | Compression and In-Situ Query Processing for Fine-Grained Array Lineage. | Jinjin Zhao, Sanjay Krishnan |
| 2024 | ICDT | Range Entropy Queries and Partitioning. | Sanjay Krishnan, Stavros Sintos |
| 2023 | ICDE | Rotary: A Resource Arbitration Framework for Progressive Iterative Analytics. | Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan |
| 2023 | ICDE | JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. | Xi Liang, Stavros Sintos, Sanjay Krishnan |
| 2022 | SIGMOD | Towards causal physical error discovery in video analytics systems. | Ted Shaowang, Jinjin Zhao, Stavros Sintos, Sanjay Krishnan |
| 2021 | CIDR | VergeDB: A Database for IoT Analytics on Edge Devices. | John Paparrizos, Chunwei Liu, Bruno Barbarioli, Johnny Hwang, Ikraduya Edian, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan |
| 2021 | CLOUD | Version Reconciliation for Collaborative Databases. | Nalin Ranjan, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore |
| 2021 | ICDE | CIAO: An Optimization Framework for Client-Assisted Data Loading. | Cong Ding, Dixin Tang, Xi Liang, Aaron J. Elmore, Sanjay Krishnan |
| 2021 | SIGMOD | Understanding and optimizing packed neural network training for hyper-parameter tuning. | Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin |
| 2021 | SIGMOD | Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. | Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan |
| 2021 | SIGMOD | Resource-efficient Shared Query Execution via Exploiting Time Slackness. | Dixin Tang, Zechao Shang, William W. Ma, Aaron J. Elmore, Sanjay Krishnan |
| 2020 | CIDR | CrocodileDB: Efficient Database Execution through Intelligent Deferment. | Zechao Shang, Xi Liang, Dixin Tang, Cong Ding, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin |
| 2020 | SIGMOD | Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. | Xi Liang, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin |
| 2020 | SIGMOD | Thrifty Query Execution via Incrementability. | Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin |
| 2019 | CIDR | DeepLens: Towards a Visual Data Management System. | Sanjay Krishnan, Adam Dziedzic, Aaron J. Elmore |
| 2019 | ICML | Band-limited Training and Inference for Convolutional Neural Networks. | Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin |
| 2018 | ICLR | Parametrized Hierarchical Procedures for Neural Programming. | Roy Fox, Richard Shin, Sanjay Krishnan, Ken Goldberg, Dawn Song, Ion Stoica |
| 2018 | ICRA | Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. | Daniel Seita, Sanjay Krishnan, Roy Fox, Stephen McKinley, John F. Canny, Ken Goldberg |
| 2018 | WAFR | Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models. | Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon |
| 2017 | CIDR | RLEX: Saftey and Data Quality in Reinforcement Learning-based and Adaptive Systems. | Sanjay Krishnan |
| 2017 | CoRL | DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations. | Sanjay Krishnan, Roy Fox, Ion Stoica, Ken Goldberg |
| 2017 | ICRA | Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. | Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca D. Dragan, Ken Goldberg |
| 2017 | ICRA | Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning. | Brijen Thananjeyan, Animesh Garg, Sanjay Krishnan, Carolyn Chen, Lauren Miller, Ken Goldberg |
| 2017 | SIGMOD | PALM: Machine Learning Explanations For Iterative Debugging. | Sanjay Krishnan, Eugene Wu |
| 2017 | SIGITE | M-CAFE 2.0: A Scalable Platform with Comparative Plots and Topic Tagging for Ongoing Course Feedback. | Mo Zhou, Sanjay Krishnan, Jay Patel, Brandie Nonnecke, Camille Crittenden, Ken Goldberg |
| 2016 | ICRA | TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning. | Adithyavairavan Murali, Animesh Garg, Sanjay Krishnan, Florian T. Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg |
| 2016 | SIGMOD | Data Cleaning: Overview and Emerging Challenges. | Xu Chu, Ihab F. Ilyas, Sanjay Krishnan, Jiannan Wang |
| 2016 | SIGMOD | ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning. | Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Jiannan Wang, Eugene Wu |
| 2016 | SIGMOD | Towards reliable interactive data cleaning: a user survey and recommendations. | Sanjay Krishnan, Daniel Haas, Michael J. Franklin, Eugene Wu |
| 2016 | SIGMOD | PrivateClean: Data Cleaning and Differential Privacy. | Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska |
| 2016 | WAFR | SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards. | Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg |
| 2015 | ISRR | Transition State Clustering: Unsupervised Surgical Trajectory Segmentation for Robot Learning. | Sanjay Krishnan, Animesh Garg, Sachin Patil, Colin Lea, Gregory D. Hager, Pieter Abbeel, Ken Goldberg |
| 2015 | SIGITE | M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering. | Mo Zhou, Alison Cliff, Sanjay Krishnan, Brandie Nonnecke, Camille Crittenden, Kanji Uchino, Ken Goldberg |
| 2014 | RecSys | A methodology for learning, analyzing, and mitigating social influence bias in recommender systems. | Sanjay Krishnan, Jay Patel, Michael J. Franklin, Ken Goldberg |
| 2014 | SIGMOD | Fine-grained partitioning for aggressive data skipping. | Liwen Sun, Michael J. Franklin, Sanjay Krishnan, Reynold S. Xin |
| 2014 | SIGMOD | A sample-and-clean framework for fast and accurate query processing on dirty data. | Jiannan Wang, Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Tim Kraska, Tova Milo |