Database Seminar (CS 7390)

The database seminar discusses recent research from the areas of data analysis and database management systems. 



We discuss recent papers from the area of database management systems (primarily VLDB, SIGMOD, and CIDR conferences). One to two papers (on related topics) are presented in each session. Alternatively, participants may choose to present their own, ongoing research if it connects to database systems. Beyond Cornell students, we will also have several external speakers presenting their work.

Presentations take up to 45 minutes (pure presentation time), allowing for at least 15 minutes of questions throughout the talk. After the talk, all participants summarize their impressions about the paper(s). All participants taking the seminar for credit are expected to read papers before the session to enable interesting discussions.


Date Speaker Topic
9/22 (Internal)  
9/29 Edward Gan (Stanford/Databricks) CoopStore: optimizing pre-computed summaries for aggregation and Moment-based quantile sketches for efficient high cardinality aggregation queries.
10/6  Jialin Ding (MIT) Learning multi-dimensional indexes and Tsunami: a learned multi-dimensional index for correlated data and skewed workloads.
10/13 Ji Sun, Xuanhe Zhou (Tsinghua) And end-to-end learning-based cost estimator, QTune: A query-aware database tuning system with deep reinforcement learning, and Query Performance Prediction for Concurrent Queries using Graph Embedding.
10/20 TBD
10/27 Abdul H. Quamar (IBM), Chuan Lei (IBM), Jaydeep Sen (IBM) Athena++: Natural language querying for complex nested SQL queries and Conversational BI: an ontology-driven conversation system for business intelligence applications.
11/3 Christina Christodoulakis (University of Toronto) Pytheas: Pattern-based Table Discovery in CSV Files
11/10 Internal Topic: automated fact checking.
11/24 (Break)
12/01 Internal Exact cardinality query optimization with bounded execution cost, SIGMOD 2019.
12/08 Internal Data vocalization with CiceroDB, CIDR 2019.
12/15 Internal Building an "Anti-Knowledge Base" from Wikipedia updates with applications to fact checking and beyond, VLDB 2020.

Topic Propositions