PETER BAILIS
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Photo credit: Hector Garcia-Molina
I study data and data-intensive systems as a member of DAWN and the Stanford Future Data Systems group.
🔥🔥🔥 DAWN is Data Analytics for What's Next. 🔥🔥🔥
Bio: Peter Bailis is an assistant professor of Computer Science at Stanford University. Peter's research in the Future Data Systems group focuses on the design and implementation of next-generation, post-database data-intensive systems. His work spans large-scale data management, distributed protocol design, and architectures for high-volume complex decision support. He is the recipient of an NSF Graduate Research Fellowship, a Berkeley Fellowship for Graduate Study, best-of-conference citations for research appearing in both SIGMOD and VLDB, and the CRA Outstanding Undergraduate Researcher Award. He received a Ph.D. from UC Berkeley in 2015 and an A.B. from Harvard College in 2011, both in Computer Science.
Teaching: CS245 (Winter 2017) | CS345 (Fall 2016)
Big bet: MacroBase represents the future of high-volume online analytics.
Contact:
Office:
410 Gates Hall
Stanford University
Stanford, CA 94305
Support

Our group's research is generously supported in part by Toyota, Intel, RWE AG, Visa, Keysight Technologies, Facebook, and VMWare.

Affiliations

I am a member of the Stanford DAWN project. Day-to-day, I am a professor in the Future Data Systems group and sit in the Stanford InfoLab.

News
ACIDRain and tKDC SIGMOD papers posted!
3/22/2017
DAWN Project site online!
3/11/2017
Three papers to appear at SIGMOD 2017: i) MacroBase architecture, ii) accelerated classification based on Kernel Density Estimation, iii) security vulnerabilities in transactional web applications!
3/9/2017
New preprint on optimizing CNN evaluation over video streams with students and Matei Zaharia—3200x YOLO evaluation (8500x real time)!
3/7/2017
ASAP demo and preprint posted!
3/6/2017
MacroBase demo to appear at SIGMOD 2017!
2/26/2017
Kexin is headed to Monitorama 2017 to talk about streaming time-series visualization
2/12/2017
Hitachi visiting scholar Masahito Togami joins Future Data for the year!
1/10/2017
Thanks to Keysight Technologies for supporting our research through the Stanford SystemX Alliance!
11/22/2016
Continued progress on an absolute ton of research in the pipeline. Many submissions in the works; please feel free to ping.
10/16/2016
Our paper on challenges and opportunities in prioritizing attention in fast data streams will appear at CIDR 2017 in January. See you in Santa Cruz!
10/11/2016
Thanks to Facebook for beginning to support our research in the Future Data Systems group!
10/6/2016
The third installment of Research for Practice is now online at ACM Queue!
10/4/2016
Our paper on MacroBase's core architecture will appear at SIGMOD 2017! Congratulations to the students on a first-round acceptance without revisions.
9/27/2016
Welcome to our fall quarter rotators! Exciting new projects on speeding up video classification and unsupervised anomaly detection in fast data streams.
9/26/2016
New post on MacroBase on the MIT ISTC Big Data blog.
9/16/2016
Honored to receive an inaugural Faculty Research Award from VISA! Thank you for supporting our research on MacroBase.
9/9/2016
Tentative schedule for CS345S: Data-Intensive Systems for the Next 1000x (1000x.io) (August 2016) posted!
8/24/2016
Professor Matei Zaharia and co-advisee Firas Abuzaid join Stanford CS and the Infolab. Welcome to campus, and here's to many more years of great research collaboration!
8/6/2016
More news

Selected Publications · Google Scholar

Preprint
Optimizing Deep CNN-Based Queries over Video Streams at Scale
2017
MacroBase: Prioritizing Attention in Fast Data
Prioritizing Attention in Fast Data: Principles and Promise
2016
Scalable Atomic Visibility with RAMP Transactions
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
Positional Communication and Private Information in Honeybee Foraging Models

You can follow me on Twitter at @pbailis.