Conferences / CIDR (Conference on Innovative Data Systems Research)
CIDR 2019
Jan 13–16, 2019 · Asilomar Conference Grounds, Pacific Grove, CA, United States
- Conference
- CIDR (Conference on Innovative Data Systems Research) Academic
- Dates
- Jan 13, 2019 – Jan 16, 2019
- Venue
- Asilomar Conference Grounds
- Place
- Pacific Grove, CA, United States
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- cidrdb.org
- Recorded
- 0 sponsors · 32 speaker appearances
- Notes
- Speakers: every paper in the program, with the first listed author as speaker (presenting authors are not identified; CIDR tradition is that senior authors present). paper_url holds the paper PDF on cidrdb.org; slides_url only where the program links real slides. Program is in an iframe (CIDR-sessions.html). No sponsor list on the 2019 site. Registration via passkey; fee not stated (only a $100 cancellation fee).
Ticket prices
No ticket prices recorded
Sponsors 0
No sponsors recorded
Speakers and talks 32
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Karin Strauss | Microsoft | Keynote | DNA Data Storage and Near-Molecule Processing for the Yottabyte Era | — |
| Luis Ceze | University of Washington | Keynote | DNA Data Storage and Near-Molecule Processing for the Yottabyte Era | — |
| Mark Ramsey | GSK | Keynote | Using Bots, Machine Learning & Pipelines to create a modern data management environment | — |
| Alberto Lerner | eXascale Infolab | Paper | The Case for Network Accelerated Query Processing | Paper |
| Alexander J Ratner | Stanford University | Paper | The Role of Massively Multi-Task and Weak Supervision in Software 2.0 | Paper |
| Anastasios Arvanitis | Unravel Data | Paper | Automated Performance Management for the Big Data Stack | Paper |
| Andreas Kipf | Technical University of Munich | Paper | Learned Cardinalities: Estimating Correlated Joins with Deep Learning | Paper |
| Codi J Burley | The Ohio State University | Paper | ARQuery: Hallucinating Analytics over Real-World Data using Augmented Reality | Paper |
| Daniel Kang | Stanford University | Paper | Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine | Paper |
| Gustavo Alonso | ETHZ | Paper | DPI: The Data Processing Interface for Modern Networks | Paper |
| Holger Pirk | Imperial College London | Paper | Thriving in the No Man's Land between Compilers and Databases | Paper |
| Immanuel Trummer | Cornell University | Paper | Data Vocalization with CiceroDB | Paper |
| Ios Kotsogiannis | Duke University | Paper | Architecting a Differentially Private SQL Engine | Paper |
| Johannes Gehrke | Microsoft | Paper | Veritas: Shared Verifiable Databases and Tables in the Cloud | Paper |
| Joseph M Hellerstein | UC Berkeley | Paper | Serverless Computing: One Step Forward, Two Steps Back | Paper |
| Lennart Oldenburg | University of California, Santa Cruz | Paper | Fixed It For You: Protocol Repair Using Lineage Graphs | Paper |
| Martin Kersten | CWI | Paper | SQALPEL: A database performance platform | Paper |
| Michael J Freitag | TUM | Paper | Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates | Paper |
| Periklis Chrysogelos | EPFL | Paper | Hardware-conscious Query Processing in GPU-accelerated Analytical Engines | Paper |
| Raja Appuswamy | Eurecom | Paper | OligoArchive: Using DNA in the DBMS storage hierarchy | Paper |
| Rajesh Bordawekar | IBM T. J. Watson Research Center | Paper | Exploiting Latent Information in Relational Databases via Word Embedding and Application to Degrees of Disclosure | Paper |
| Ryan C Marcus | Brandeis University | Paper | Towards a Hands-Free Query Optimizer through Deep Learning | Paper |
| Sandeep Tata | Paper | ItemSuggest: A Data Management Platform for Machine Learned Ranking Services | Paper | |
| Sanjay Krishnan | U Chicago | Paper | DeepLens: Towards a Visual Data Management System | Paper |
| Shrainik Jain | University of Washington | Paper | Database-Agnostic Workload Management | Paper |
| Stratos Idreos | Harvard University | Paper | Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn | Paper |
| Tim Kraska | MIT | Paper | SageDB: A Learned Database System | Paper |
| Tobias Bleifuß | Hasso Plattner Institute | Paper | DBChEx: Interactive Exploration of Data and Schema Change | Paper |
| Wenbo Tao | MIT | Paper | Kyrix: Interactive Visual Data Exploration at Scale | Paper |
| Zack Ives | University of Pennsylvania | Paper | Dataset Relationship Management | Paper |
| Zhongjun Jin | University of Michigan | Paper | Demonstration of a Multiresolution Schema Mapping System | Paper |
| Zuyu Zhang | University of Wisconsin-Madison | Paper | Data Partitioning for In-Memory Systems: Myths, Challenges, and Opportunities | Paper |