News & Events

Fall 2016 Open Student Positions

The Carnegie Mellon Database Group has several open positions for students in the 2016-2017 academic year. These positions are only available to current and recently graduated CMU students. The positions that are funded will be marked as "paid" and are only available to current CMU students. The unpaid positions are more research related, and thus can be part of an independent study or senior thesis project that could turn into a publication. We especially encourage students who are interested in Read More

[DB Seminar] Fall 2016: First Meeting + PKU/CMU Interns

This is the first meeting of the Database Group for Fall 2016. We will do the usual meet & greet, followed by two talks from PKU/CMU summer interns. Read More

Danai Koutra Wins 2016 SIGKDD Doctoral Dissertation Award

CS alumna Prof. Danai Koutra (now faculty at the University of Michigan Ann-Arbor) won the SIGKDD 2016 Dissertation award, for her thesis Exploring and Making Sense of Large Graphs The thesis contributes fast algorithms for summarizing large graphs, both static as well as time-evolving, and for contrasting two or more graphs, with applications to brain wiring, social networks, collaboration networks and more. SIGKDD is the premier conference for large-scale data mining. The competition for the dissertation award is fierce, with Read More

CMU Team Wins 2016 SIGKDD ‘Test of Time’ Award

CMU team wins the ‘Test of Time’ award at KDD 2016 for their 2005 paper: Graphs Over Time: Densification Laws, Shrinking Diameters and Possible Explanations Jure Leskovec, Jon Kleinberg, and Christos Faloutsos KDD is the flagship conference for large-scale data mining. Jure was a phd student at SCS/MLD (and currently a professor at Stanford). Jon was visiting CMU for his sabbatical. The paper made the surprising discoveries that real graphs become denser over time, following a power-law pattern, and that Read More

Vagelis and Leman win ‘best paper’ awards in SDM’16

SIAM SDM is one of the top conferences in data mining. Specifically, Vagelis  attracted the 'best student paper award', with his single-author paper on tensors   Evangelos E. Papalexakis, Automatic Unsupervised Tensor Mining with Quality Assessment There, Vagelis showed how to measure the goodness of a tensor decomposition, and how to automatically determine the correct rank of such a decomposition. Moreover, CMU/SCS alumna Prof. Leman Akoglu, and her student,  attracted the 'best  paper runner-up award' for their paper on anomaly Read More

Robson Cordeiro (University of Sao Paulo)

Given a data stream with many attributes and high frequency of events, how to cluster similar events? Can it be done in real time? For example, how to cluster decades of frequent measurements of tens of climatic attributes to aid real time alert systems in forecasting extreme climatic events, such as floods and hurricanes? The task of clustering data with many attributes is known as subspace clustering. Today, there exists a need for algorithms of this type well-suited to process Read More

[PDL Visit Day 2016] Shasank Chavan (Oracle)

The Database In-Memory (DBIM) Option by Oracle is an industry-first dual format in-memory database that maintains transactional consistent data in both row and columnar formats. This unique architecture enables analytic and OLTP workloads to coexist simultaneously, bringing together the best of both worlds. DBIM is the fastest growing database option since its release in 2014, achieving great success with customer adoption. The next release of DBIM is slated for the summer of 2016, and contains significant innovations in the areas Read More

[PDL Visit Day 2016] Thomas Baby (Oracle)

The IT industry today is undergoing a revolutionary change in how customers deploy and configure their compute resources. Driven by the demand to reduce costs, both in capital and operation expense, these customers are turning to CLOUD or HYBRID-CLOUD solutions. These customers span the spectrum from very small startup businesses to Fortune 500 companies across regions and industries. Oracle Corporation leverages innovative engineering to respond to that demand as both provider and consumer of cloud technology by providing highly secure, Read More

[PDL Visit Day 2016] Siying Dong (Facebook)

RocksDB is an embedded persistent key-value store for low-latency and high-throughput workload. It has been adapted to a wide range of workloads, including RocksDB as an embedded DBMS and as storage engines of other DBMS systems. Our benchmarks show RocksDB can achieve 126K random reads per second on flash and 7 million random reads per second on memory. RocksDB also uses half the space as InnoDB, writes out half the bytes to SSD with a similar read and write performance, Read More

Joy Arulraj Wins 2016 Samsung PhD Fellowship

CMU DB Ph.D. student and teenage heartthrob Joy Arulraj won a Samsung 2017 PhD Fellowship in the area of Software and Memory System Solutions for Data Centers. Joy's research is on developing the novel database management system architectures for emerging non-volatile memory technologies to support modern hybrid transactional/analytical processing (HTAP) applications. The Samsung PhD Fellowship program awards outstanding graduate students working on cutting-edge research for innovative solutions to their fields’ biggest problems. More information about the Samsung PhD Fellowship program. Read More