PETER BAILIS
pdb
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 and DAWN project focuses on the design and implementation of post-database data-intensive systems. He is the recipient of the ACM SIGMOD Jim Gray Doctoral Dissertation Award, 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.