Sanjay Krishnan

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 107

Top Venues

University of California, Berkeley, USA (PHD)

Education History

University of California, Berkeley, USA

PHD

Publications

Jinjin Zhao, Avidgor Gal, Sanjay Krishnan
A System for Quantifying Data Science Workflows with Fine-Grained Procedural Logging and a Pilot Study. CoRR (2024)
Rui Liu, Jun Hyuk Chang, Riki Otaki, Zhe Heng Eng, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan
Towards Resource-adaptive Query Execution in Cloud Native Databases. CIDR (2024)
Shinan Liu, Ted Shaowang, Gerry Wan, Jeewon Chae, Jonatas Marques, Sanjay Krishnan, Nick Feamster
ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis. CoRR (2024)
Jinjin Zhao, Sanjay Krishnan
Compression and In-Situ Query Processing for Fine-Grained Array Lineage. CoRR (2024)
Jinjin Zhao, Avigdor Gal, Sanjay Krishnan
Data Makes Better Data Scientists. CoRR (2024)
Pranav Subramaniam, Sanjay Krishnan
Intent-Based Access Control: Using LLMs to Intelligently Manage Access Control. CoRR (2024)
Sanjay Krishnan, Stavros Sintos
Range Entropy Queries and Partitioning. ICDT (2024)
Jinjin Zhao, Sanjay Krishnan
Compression and In-Situ Query Processing for Fine-Grained Array Lineage. ICDE (2024)
Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan
Riveter: Adaptive Query Suspension and Resumption Framework for Cloud Native Databases. ICDE (2024)
Jinjin Zhao, Ted Shaowang, Stavros Sintos, Sanjay Krishnan
Towards Causal Physical Error Discovery in Video Analytics Systems. CoRR (2024)
Bruno Barbarioli, Gabriel Mersy, Stavros Sintos, Sanjay Krishnan
Hierarchical Residual Encoding for Multiresolution Time Series Compression. Proc. ACM Manag. Data 1 (1) (2023)
Ted Shaowang, Sanjay Krishnan
EdgeServe: An Execution Layer for Decentralized Prediction. CoRR (2023)
Jinjin Zhao, Avigdor Gal, Sanjay Krishnan
Data Makes Better Data Scientists. HILDA@SIGMOD (2023)
Siyuan Xia, Zhiru Zhu, Chris Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow. CoRR (2023)
Gabriel Mersy, Sanjay Krishnan
Toward a Life Cycle Assessment for the Carbon Footprint of Data. HotCarbon (2023)
Shinan Liu, Tarun Mangla, Ted Shaowang, Jinjin Zhao, John Paparrizos, Sanjay Krishnan, Nick Feamster
AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7 (1) (2023)
Raul Castro Fernandez, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan, Chenhao Tan
How Large Language Models Will Disrupt Data Management. Proc. VLDB Endow. 16 (11) (2023)
Deniz Turkcapar, Sanjay Krishnan
Quantifying Uncertainty in Aggregate Queries over Integrated Datasets. CoRR (2023)
Edward C. Williams, Grace Su, Sandra R. Schloen, Miller C. Prosser, Susanne Paulus, Sanjay Krishnan
DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep Learning. CoRR (2023)
Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan
Rotary: A Resource Arbitration Framework for Progressive Iterative Analytics. ICDE (2023)
Xi Liang, Stavros Sintos, Sanjay Krishnan
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. ICDE (2023)
Sanjay Krishnan, Stavros Sintos
Range Entropy Queries and Partitioning. CoRR (2023)
Siyuan Xia, Zhiru Zhu, Christopher Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow. Proc. VLDB Endow. 15 (11) (2022)
Xi Liang, Stavros Sintos, Sanjay Krishnan
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. CoRR (2022)
Ted Shaowang, Jinjin Zhao, Stavros Sintos, Sanjay Krishnan
Towards causal physical error discovery in video analytics systems. HILDA@SIGMOD (2022)
Ted Shaowang, Xi Liang, Sanjay Krishnan
Sensor fusion on the edge: initial experiments in the EdgeServe system. BiDEDE@SIGMOD (2022)
Nalin Ranjan, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore
Version Reconciliation for Collaborative Databases. SoCC (2021)
Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. SIGMOD Conference (2021)
Cong Ding, Dixin Tang, Xi Liang, Aaron J. Elmore, Sanjay Krishnan
CIAO: An Optimization Framework for Client-Assisted Data Loading. CoRR (2021)
Dixin Tang, Zechao Shang, William W. Ma, Aaron J. Elmore, Sanjay Krishnan
Resource-efficient Shared Query Execution via Exploiting Time Slackness. SIGMOD Conference (2021)
John Paparrizos, Chunwei Liu, Bruno Barbarioli, Johnny Hwang, Ikraduya Edian, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan
VergeDB: A Database for IoT Analytics on Edge Devices. CIDR (2021)
Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. CoRR (2021)
Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
Understanding and optimizing packed neural network training for hyper-parameter tuning. DEEM@SIGMOD (2021)
Ted Shaowang, Nilesh Jain, Dennis Matthews, Sanjay Krishnan
Declarative Data Serving: The Future of Machine Learning Inference on the Edge. Proc. VLDB Endow. 14 (11) (2021)
Nalin Ranjan, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan
Version Reconciliation for Collaborative Databases. CoRR (2021)
Cong Ding, Dixin Tang, Xi Liang, Aaron J. Elmore, Sanjay Krishnan
CIAO: An Optimization Framework for Client-Assisted Data Loading. ICDE (2021)
Dale Decatur, Sanjay Krishnan
VizExtract: Automatic Relation Extraction from Data Visualizations. CoRR (2021)
Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
Understanding and Optimizing Packed Neural Network Training for Hyper-Parameter Tuning. CoRR (2020)
Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster
The Data Station: Combining Data, Compute, and Market Forces. CoRR (2020)
Zechao Shang, Xi Liang, Dixin Tang, Cong Ding, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin
CrocodileDB: Efficient Database Execution through Intelligent Deferment. CIDR (2020)
Xi Liang, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. SIGMOD Conference (2020)
Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin
Thrifty Query Execution via Incrementability. SIGMOD Conference (2020)
Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman, Monisha Ghosh, Sanjay Krishnan
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios. CoRR (2020)
Xi Liang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. CoRR (2020)
Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin
CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness. Proc. VLDB Endow. 13 (12) (2020)
Vanlin Sathya, Adam Dziedzic, Monisha Ghosh, Sanjay Krishnan
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT. ICNC (2020)
Adam Dziedzic, Sanjay Krishnan
An Empirical Evaluation of Perturbation-based Defenses. CoRR (2020)
Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin, John Paparrizos, Zechao Shang, Adam Dziedzic, Rui Liu
Artificial Intelligence in Resource-Constrained and Shared Environments. ACM SIGOPS Oper. Syst. Rev. 53 (1) (2019)
Zisu Dong, Sanjay Krishnan, Sona Dolasia, Ashwin Balakrishna, Michael Danielczuk, Ken Goldberg
Automating Planar Object Singulation by Linear Pushing with Single-point and Multi-point Contacts. CASE (2019)
Sanjay Krishnan, Adam Dziedzic, Aaron J. Elmore
DeepLens: Towards a Visual Data Management System. CIDR (2019)
Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
Selectivity Estimation with Deep Likelihood Models. CoRR (2019)
Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg
SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards. Int. J. Robotics Res. 38 (2-3) (2019)
Brijen Thananjeyan, Ajay Kumar Tanwani, Jessica J. Ji, Danyal Fer, Vatsal Patel, Sanjay Krishnan, Ken Goldberg
Optimizing Robot-Assisted Surgery Suture Plans to Avoid Joint Limits and Singularities. ISMR (2019)
Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
Band-limited Training and Inference for Convolutional Neural Networks. ICML (2019)
Xi Liang, Aaron J. Elmore, Sanjay Krishnan
Opportunistic View Materialization with Deep Reinforcement Learning. CoRR (2019)
Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin
Band-limited Training and Inference for Convolutional Neural Networks. CoRR (2019)
Sanjay Krishnan, Eugene Wu
AlphaClean: Automatic Generation of Data Cleaning Pipelines. CoRR (2019)
Vanlin Sathya, Adam Dziedzic, Monisha Ghosh, Sanjay Krishnan
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT. CoRR (2019)
Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin
Intermittent Query Processing. Proc. VLDB Endow. 12 (11) (2019)
Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
Deep Unsupervised Cardinality Estimation. Proc. VLDB Endow. 13 (3) (2019)
Roy Fox, Richard Shin, Sanjay Krishnan, Ken Goldberg, Dawn Song, Ion Stoica
Parametrized Hierarchical Procedures for Neural Programming. ICLR (Poster) (2018)
Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Ken Goldberg
SPRK: A low-cost stewart platform for motion study in surgical robotics. ISMR (2018)
Sanjay Krishnan, Zongheng Yang, Ken Goldberg, Joseph M. Hellerstein, Ion Stoica
Learning to Optimize Join Queries With Deep Reinforcement Learning. CoRR (2018)
Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models. WAFR (2018)
Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Carolyn Chen, Walter Doug Boyd, Ken Goldberg
Using intermittent synchronization to compensate for rhythmic body motion during autonomous surgical cutting and debridement. ISMR (2018)
Daniel Seita, Sanjay Krishnan, Roy Fox, Stephen McKinley, John F. Canny, Ken Goldberg
Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. ICRA (2018)
Sanjay Krishnan, Adam Dziedzic, Aaron J. Elmore
DeepLens: Towards a Visual Data Management System. CoRR (2018)
Jessica J. Ji, Sanjay Krishnan, Vatsal Patel, Danyal Fer, Ken Goldberg
Learning 2D Surgical Camera Motion From Demonstrations. CASE (2018)
Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models. CoRR (2018)
Sanjay Krishnan, Roy Fox, Ion Stoica, Ken Goldberg
DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations. CoRL (2017)
Roy Fox, Sanjay Krishnan, Ion Stoica, Ken Goldberg
Multi-Level Discovery of Deep Options. CoRR (2017)
Brijen Thananjeyan, Animesh Garg, Sanjay Krishnan, Carolyn Chen, Lauren Miller, Ken Goldberg
Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning. ICRA (2017)
Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. CoRR (2017)
Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Ken Goldberg
SPRK: A Low-Cost Stewart Platform For Motion Study In Surgical Robotics. CoRR (2017)
Sanjay Krishnan, Animesh Garg, Sachin Patil, Colin Lea, Gregory D. Hager, Pieter Abbeel, Ken Goldberg
Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning. Int. J. Robotics Res. 36 (13-14) (2017)
Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, Ken Goldberg
Statistical data cleaning for deep learning of automation tasks from demonstrations. CASE (2017)
Mo Zhou, Sanjay Krishnan, Jay Patel, Brandie Nonnecke, Camille Crittenden, Ken Goldberg
M-CAFE 2.0: A Scalable Platform with Comparative Plots and Topic Tagging for Ongoing Course Feedback. SIGITE (2017)
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Ken Goldberg
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. ICRA (2017)
Daniel Seita, Sanjay Krishnan, Roy Fox, Stephen McKinley, John F. Canny, Ken Goldberg
Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. CoRR (2017)
Carolyn Chen, Sanjay Krishnan, Michael Laskey, Roy Fox, Ken Goldberg
An algorithm and user study for teaching bilateral manipulation via iterated best response demonstrations. CASE (2017)
Sanjay Krishnan, Roy Fox, Ion Stoica, Ken Goldberg
DDCO: Discovery of Deep Continuous Options forRobot Learning from Demonstrations. CoRR (2017)
Sanjay Krishnan, Eugene Wu
PALM: Machine Learning Explanations For Iterative Debugging. HILDA@SIGMOD (2017)
Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Eugene Wu
BoostClean: Automated Error Detection and Repair for Machine Learning. CoRR (2017)
Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Carolyn Chen, Walter Doug Boyd, Ken Goldberg
Using Intermittent Synchronization to Compensate for Rhythmic Body Motion During Autonomous Surgical Cutting and Debridement. CoRR (2017)
Sanjay Krishnan
RLEX: Saftey and Data Quality in Reinforcement Learning-based and Adaptive Systems. CIDR (2017)
Yeounoh Chung, Sanjay Krishnan, Tim Kraska
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets. Proc. VLDB Endow. 10 (10) (2017)
Brandie Nonnecke, Shrestha Mohanty, Andrew Lee, Jonathan Lee, Sequoia Beckman, Justin Mi, Sanjay Krishnan, Rachel Edita Roxas, Nathaniel Oco, Camille Crittenden, Ken Goldberg
Malasakit 1.0: A participatory online platform for crowdsourcing disaster risk reduction strategies in the philippines. GHTC (2017)
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Kenneth Y. Goldberg
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations. CoRR (2016)
Sanjay Krishnan, Animesh Garg, Richard Liaw, Lauren Miller, Florian T. Pokorny, Ken Goldberg
HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards. CoRR (2016)
Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Jiannan Wang, Eugene Wu
ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning. SIGMOD Conference (2016)
Adithyavairavan Murali, Animesh Garg, Sanjay Krishnan, Florian T. Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg
TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning. ICRA (2016)
Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska
PrivateClean: Data Cleaning and Differential Privacy. SIGMOD Conference (2016)
Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models. CoRR (2016)
Xu Chu, Ihab F. Ilyas, Sanjay Krishnan, Jiannan Wang
Data Cleaning: Overview and Emerging Challenges. SIGMOD Conference (2016)
Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg
ActiveClean: Interactive Data Cleaning For Statistical Modeling. Proc. VLDB Endow. 9 (12) (2016)
Yeounoh Chung, Sanjay Krishnan, Tim Kraska
A Data Quality Metric (DQM): How to Estimate The Number of Undetected Errors in Data Sets. CoRR (2016)
Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg
SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards. WAFR (2016)
Sanjay Krishnan, Daniel Haas, Michael J. Franklin, Eugene Wu
Towards reliable interactive data cleaning: a user survey and recommendations. HILDA@SIGMOD (2016)
Mo Zhou, Alison Cliff, Sanjay Krishnan, Brandie Nonnecke, Camille Crittenden, Kanji Uchino, Ken Goldberg
M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering. SIGITE (2015)
Brandie Nonnecke, Sanjay Krishnan, Jay Patel, Mo Zhou, Laura Byaruhanga, Dorothy Masinde, Maria Elena Meneses, Alejandro Martin del Campo, Camille Crittenden, Kenneth Y. Goldberg
DevCAFE 1.0: A participatory platform for assessing development initiatives in the field. GHTC (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sanjay Krishnan