Peter Bailis
I build data-intensive systems.
I am the CEO and Founder of Sisu Data.
Before Sisu, I was an assistant professor of CS at Stanford, where I founded the DAWN project.
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PhD Students and Postdocs
- Edward Gan (PhD 2020, software engineer at Databricks)
- Kexin Rong (PhD 2021, faculty at Georgia Tech; w/ Phil Levis)
- Kai Sheng Tai (PhD 2021, research scientist at Facebook AI; w/ Greg Valiant)
- Cody Coleman (PhD 2021, founder at Coactive AI; w/ Matei Zaharia)
- Firas Abuzaid (PhD 2022, founder at neo.tax; w/ Matei Zaharia)
- Daniel Kang (PhD 2022, faculty at UIUC; w/ Matei Zaharia)
- Fiodar Kazhamiaka (postdoc 2022, researcher at Microsoft Research; w/ Matei Zaharia)
- Peter Kraft (w/ Matei Zaharia)
- Sahaana Suri (PhD 2022, stealth startup)
Recent Publications
2023
- Epoxy: ACID Transactions Across Diverse Data Stores,
- Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations,
- Data Management for ML-based Analytics and Beyond,
2022
- TAOBench: An End-to-End Benchmark for Social Network Workloads,
- Semantic Indexes for Machine Learning-based Queries over Unstructured Data,
- Finding Label and Model Errors in Perception Data With Learned Observation Assertions,
- Data-Parallel Actors: A Programming Model for Scalable Query Serving Systems,
- The Seattle report on database research,
- VIVA: An End-to-End System for Interactive Video Analytics,
- Similarity search for efficient active learning and search of rare concepts,
2021
- Accelerating Approximate Aggregation Queries with Expensive Predicates,
- RAMP-TAO: Layering Atomic Transactions on Facebook's Online TAO Data Store,
- Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics,
- Finding Label and Model Errors in Perception Data With Learned Observation Assertions,
- Exploiting Proximity Search and Easy Examples to Select Rare Events,
- Contracting Wide-area Network Topologies to Solve Flow Problems Quickly,
- Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training,
- Challenges and Opportunities for Autonomous Vehicle Query Systems,
2020
- DIFF: A Relational Interface for Large-Scale Data Explanation,
- CoopStore: Optimizing Precomputed Summaries for Aggregation,
- Approximate Selection with Guarantees using Proxies,
- Leveraging Organizational Resources to Adapt Models to New Data
Modalities,
- Approximate Partition Selection for Big-Data Workloads using Summary Statistics,
- BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics,
- MLPerf Training Benchmark,
- Model Assertions for Monitoring and Improving ML Models,
- Willump: A Statistically-Aware End-to-end Optimizer for Machine
Learning Inference,
- Selection via Proxy: Efficient Data Selection for Deep Learning,
- An End-to-End Earthquake Monitoring Method for Joint Earthquake Detection and Association using Deep Learning,
2019
- DIFF: A Relational Interface for Large-Scale Data Explanation,
- DROP: A Workload-Aware Optimizer for Dimensionality Reduction,
- CrossTrainer: Practical Domain Adaptation with Loss Reweighting,
- Rehashing Kernel Evaluation in High Dimensions,
- Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data,
- Equivariant Transformer Networks,
- LIT: Block-wise Intermediate Representation Training for Model Compression,
- To Index or Not to Index: Optimizing Exact Maximum Inner Product Search,
- Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine,
2018
- Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries,
- Filter Before You Parse: Faster Analytics on Raw Data with Sparser,
- Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science,
- Sketching Linear Classifiers over Data Streams,
- Analysis of the Time-To-Accuracy Metric and Entries in the DAWNBench Deep Learning Benchmark,
- Model Assertions for Debugging Machine Learning,
- Exploring the Use of Learning Algorithms for Efficient Performance Profiling,
- MacroBase: Prioritizing Attention in Fast Data,
2017
- NoScope: Optimizing Neural Network Queries over Video at Scale,
- ASAP: Prioritizing Attention via Time Series Smoothing,
- ACIDRain: Concurrency-Related Attacks on Database-Backed Web Applications,
- Scalable Kernel Density Classification via Threshold-Based Pruning,
- MacroBase: Prioritizing Attention in Fast Data,
- DAWNBench: An End-to-End Deep Learning Benchmark and Competition,
- Prioritizing Attention in Fast Data: Principles and Promise,
2016
2015
- Coordination Avoidance in Database Systems,
- Feral Concurrency Control: An Empirical Investigation of Modern Application Integrity,
- The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox,
- Readings in Database Systems, 5th Edition,
- Coordination Avoidance in Distributed Databases,
2014
- Highly Available Transactions: Virtues and Limitations,
- Quantifying Eventual Consistency with PBS,
- Scalable Atomic Visibility with RAMP Transactions,
- The Network is Reliable: An Informal Survey of Real-World Communications Failures,
- Quantifying Eventual Consistency with PBS,
2013
- Consistency without Borders,
- PBS at Work: Advancing Data Management with Consistency Metrics,
- Bolt-on Causal Consistency,
- HAT, not CAP: Towards Highly Available Transactions,
- Eventual Consistency Today: Limitations, Extensions, and Beyond,
2012
- Probabilistically Bounded Staleness for Practical Partial Quorums,
- The Potential Dangers of Causal Consistency and an Explicit Solution,
2011
- Programming Micro-aerial Vehicle Swarms with Karma,
- Dimetrodon: Processor-level Preventive Thermal Management via Idle Cycle Injection,
2010
2023
- Epoxy: ACID Transactions Across Diverse Data Stores,
- Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations,
- Data Management for ML-based Analytics and Beyond,
2022
- TAOBench: An End-to-End Benchmark for Social Network Workloads,
- Semantic Indexes for Machine Learning-based Queries over Unstructured Data,
- Finding Label and Model Errors in Perception Data With Learned Observation Assertions,
- Data-Parallel Actors: A Programming Model for Scalable Query Serving Systems,
- The Seattle report on database research,
- VIVA: An End-to-End System for Interactive Video Analytics,
- Similarity search for efficient active learning and search of rare concepts,
2021
- Accelerating Approximate Aggregation Queries with Expensive Predicates,
- RAMP-TAO: Layering Atomic Transactions on Facebook's Online TAO Data Store,
- Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics,
- Finding Label and Model Errors in Perception Data With Learned Observation Assertions,
- Exploiting Proximity Search and Easy Examples to Select Rare Events,
- Contracting Wide-area Network Topologies to Solve Flow Problems Quickly,
- Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training,
- Challenges and Opportunities for Autonomous Vehicle Query Systems,
2020
- DIFF: A Relational Interface for Large-Scale Data Explanation,
- CoopStore: Optimizing Precomputed Summaries for Aggregation,
- Approximate Selection with Guarantees using Proxies,
- Leveraging Organizational Resources to Adapt Models to New Data Modalities,
- Approximate Partition Selection for Big-Data Workloads using Summary Statistics,
- BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics,
- MLPerf Training Benchmark,
- Model Assertions for Monitoring and Improving ML Models,
- Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference,
- Selection via Proxy: Efficient Data Selection for Deep Learning,
- An End-to-End Earthquake Monitoring Method for Joint Earthquake Detection and Association using Deep Learning,
2019
- DIFF: A Relational Interface for Large-Scale Data Explanation,
- DROP: A Workload-Aware Optimizer for Dimensionality Reduction,
- CrossTrainer: Practical Domain Adaptation with Loss Reweighting,
- Rehashing Kernel Evaluation in High Dimensions,
- Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data,
- Equivariant Transformer Networks,
- LIT: Block-wise Intermediate Representation Training for Model Compression,
- To Index or Not to Index: Optimizing Exact Maximum Inner Product Search,
- Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine,
2018
- Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries,
- Filter Before You Parse: Faster Analytics on Raw Data with Sparser,
- Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science,
- Sketching Linear Classifiers over Data Streams,
- Analysis of the Time-To-Accuracy Metric and Entries in the DAWNBench Deep Learning Benchmark,
- Model Assertions for Debugging Machine Learning,
- Exploring the Use of Learning Algorithms for Efficient Performance Profiling,
- MacroBase: Prioritizing Attention in Fast Data,
2017
- NoScope: Optimizing Neural Network Queries over Video at Scale,
- ASAP: Prioritizing Attention via Time Series Smoothing,
- ACIDRain: Concurrency-Related Attacks on Database-Backed Web Applications,
- Scalable Kernel Density Classification via Threshold-Based Pruning,
- MacroBase: Prioritizing Attention in Fast Data,
- DAWNBench: An End-to-End Deep Learning Benchmark and Competition,
- Prioritizing Attention in Fast Data: Principles and Promise,
2016
2015
- Coordination Avoidance in Database Systems,
- Feral Concurrency Control: An Empirical Investigation of Modern Application Integrity,
- The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox,
- Readings in Database Systems, 5th Edition,
- Coordination Avoidance in Distributed Databases,
2014
- Highly Available Transactions: Virtues and Limitations,
- Quantifying Eventual Consistency with PBS,
- Scalable Atomic Visibility with RAMP Transactions,
- The Network is Reliable: An Informal Survey of Real-World Communications Failures,
- Quantifying Eventual Consistency with PBS,
2013
- Consistency without Borders,
- PBS at Work: Advancing Data Management with Consistency Metrics,
- Bolt-on Causal Consistency,
- HAT, not CAP: Towards Highly Available Transactions,
- Eventual Consistency Today: Limitations, Extensions, and Beyond,
2012
- Probabilistically Bounded Staleness for Practical Partial Quorums,
- The Potential Dangers of Causal Consistency and an Explicit Solution,
2011
- Programming Micro-aerial Vehicle Swarms with Karma,
- Dimetrodon: Processor-level Preventive Thermal Management via Idle Cycle Injection,
2010