Demo Data from VLDB 2026 / reviewers in the wild / expert
Matei David
dblp:29/6126
· DBLP profile ↗
10ranked-venue papers
9as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 5 · 4 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 2 first-authorSystems, architecture and hardware · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Bioinformatics and computational biology · 100% | |
| Theoretical computer science
2 papers |
Computational complexity · 92% Coding theory · 8% | |
| Software engineering, system software, and programming languages
1 paper |
Concurrent programming · 100% |
Topics — the 12 heaviest of 12, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
sequence analysis |
0.4 | 2 | 2017 | Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017 SHRiMP2: Sensitive yet Practical Short Read Mapping · Bioinform. 2011 |
Bioinformatics and computational biology › sequence analysis
base calling |
0.3 | 1 | 2017 | Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017 |
Bioinformatics and computational biology › sequence analysis › base calling
nanopore base calling |
0.3 | 1 | 2017 | Nanocall: an open source basecaller for Oxford Nanopore sequencing data · Bioinform. 2017 |
Computational complexity
communication complexity |
0.2 | 2 | 2010 | Trade-Off Lower Bounds for Stack Machines · CCC 2010 Separating Deterministic from Nondeterministic NOF Multiparty Communication Complexity · ICALP 2007 |
Bioinformatics and computational biology › sequence analysis › read mapping
short read alignment |
0.1 | 1 | 2011 | SHRiMP2: Sensitive yet Practical Short Read Mapping · Bioinform. 2011 |
Computational complexity
space complexity |
0.1 | 1 | 2010 | Trade-Off Lower Bounds for Stack Machines · CCC 2010 |
Computational complexity › communication complexity
multiparty communication complexity |
0.1 | 1 | 2007 | Separating Deterministic from Nondeterministic NOF Multiparty Communication Complexity · ICALP 2007 |
Concurrent programming
concurrent data structures |
0.0 | 1 | 2004 | Brief announcement: a single enqueuer wait-free queue implementation · PODC 2004 |
Concurrent programming
shared memory |
0.0 | 1 | 2004 | Brief announcement: a single enqueuer wait-free queue implementation · PODC 2004 |
Concurrent programming › concurrent data structures › concurrent queue
wait-free queue |
0.0 | 1 | 2004 | Brief announcement: a single enqueuer wait-free queue implementation · PODC 2004 |
Computational complexity
circuit complexity |
0.0 | 1 | 2010 | Trade-Off Lower Bounds for Stack Machines · CCC 2010 |
Coding theory
network coding |
0.0 | 1 | 2010 | Trade-Off Lower Bounds for Stack Machines · CCC 2010 |
Methods — techniques the papers use, named apart from their topics
parallel computation · 0.4hidden markov model · 0.3paired-end alignment · 0.1number-in-hand protocol · 0.1communication complexity reduction · 0.1wait-free synchronization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Nanocall: an open source basecaller for Oxford Nanopore sequencing dataabstractMOTIVATION: The highly portable Oxford Nanopore MinION sequencer has enabled new applications of genome sequencing directly in the field. However, the MinION currently relies on a cloud computing platform, Metrichor (metrichor.com), for translating locally generated sequencing data into basecalls. RESULTS: To allow offline and private analysis of MinION data, we created Nanocall. Nanocall is the first freely available, open-source basecaller for Oxford Nanopore sequencing data and does not require an internet connection. Using R7.3 chemistry, on two E.coli and two human samples, with natural as well as PCR-amplified DNA, Nanocall reads have ∼68% identity, directly comparable to Metrichor '1D' data. Further, Nanocall is efficient, processing ∼2500 Kbp of sequence per core hour using the fastest settings, and fully parallelized. Using a 4 core desktop computer, Nanocall could basecall a MinION sequencing run in real time. Metrichor provides the ability to integrate the '1D' sequencing of template and complement strands of a single DNA molecule, and create a '2D' read. Nanocall does not currently integrate this technology, and addition of this capability will be an important future development. In summary, Nanocall is the first open-source, freely available, off-line basecaller for Oxford Nanopore sequencing data. AVAILABILITY AND IMPLEMENTATION: Nanocall is available at github.com/mateidavid/nanocall, released under the MIT license. CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online. Matei David, L. J. Dursi, Delia Yao, Paul C. Boutros, Jared T. Simpson |
Bioinform. | 1 |
| 2014 | Tradeoff lower lounds for stack machines
Matei David, Periklis A. Papakonstantinou |
Comput. Complex. | 1 |
| 2011 | SHRiMP2: Sensitive yet Practical Short Read MappingabstractAbstract Summary: We report on a major update (version 2) of the original SHort Read Mapping Program (SHRiMP). SHRiMP2 primarily targets mapping sensitivity, and is able to achieve high accuracy at a very reasonable speed. SHRiMP2 supports both letter space and color space (AB/SOLiD) reads, enables for direct alignment of paired reads and uses parallel computation to fully utilize multi-core architectures. Availability: SHRiMP2 executables and source code are freely available at: http://compbio.cs.toronto.edu/shrimp/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Matei David, Misko Dzamba, Dan Lister, Lucian Ilie, Michael Brudno |
Bioinform. | 1 |
| 2011 | How strong is Nisanʼs pseudo-random generator?
Matei David, Periklis A. Papakonstantinou, Anastasios Sidiropoulos |
Inf. Process. Lett. | 1 |
| 2010 | Trade-Off Lower Bounds for Stack MachinesabstractA space bounded Stack Machine is a regular Turing Machine with a read-only input tape, several space bounded read-write work tapes, and an unbounded stack. Stack Machines with a logarithmic space bound have been connected to other classical models of computation, such as polynomial time Turing Machines (P) (Cook; 1971) and polynomial size, polylogarithmic depth, bounded fan-in circuits (NC) e.g., (Borodin et al.; 1989). In this paper, we give the first known lower bound for Stack Machines. This comes in the form of a trade-off lower bound between space and number of passes over the input tape. Specifically, we give an explicit permuted inner product function such that any Stack Machine computing this function requires either sublinear polynomial space or sublinear polynomial number of passes. In the case of logarithmic space Stack Machines, this yields an unconditional sublinear polynomial lower bound for the number of passes. To put this result in perspective, we note that Stack Machines with logarithmic space and a single pass over the input can compute Parity, Majority, as well as certain languages outside NC. The latter follows from (Allender; 1989), conditional on the widely believed complexity assumption that EXP is different from PSPACE. Our technique is a novel communication complexity reduction, thereby extending the already wide range of models of computation for which communication complexity can be used to obtain lower bounds. Informally, we show that a k-player number-in-hand communication protocol for a base function f can efficiently simulate a space- and pass-bounded Stack Machine for a related function F, which consists of several permuted instances of f, bundled together by a combining function h. Trade-off lower bounds for Stack Machines then follow from known communication complexity lower bounds. The framework for this reduction was given by (Beame and Huynh-Ngoc; 2008), who used it to obtain similar trade-off lower bounds for Turing Machines with a constant number of pass-bounded external tapes. We also prove that the latter cannot efficiently simulate Stack Machines, conditional on the complexity assumption that E is not a subset of PSPACE. It is the treatment of an unbounded stack which constitutes the main technical novelty in our communication complexity reduction. Matei David, Periklis A. Papakonstantinou |
CCC | 1 |
| 2008 | Improved Separations between Nondeterministic and Randomized Multiparty Communication
Matei David, Toniann Pitassi, Emanuele Viola |
APPROX-RANDOM | 1 |
| 2007 | Separating Deterministic from Nondeterministic NOF Multiparty Communication Complexity
Paul Beame, Matei David, Toniann Pitassi, Philipp Woelfel |
ICALP | 2 |
| 2005 | Restricted Stack Implementations
Matei David, Alex Brodsky, Faith Ellen |
DISC | 1 |
| 2004 | Brief announcement: a single enqueuer wait-free queue implementationabstractNo abstract available. Matei David |
PODC | 1 |
| 2004 | A Single-Enqueuer Wait-Free Queue Implementation
Matei David |
DISC | 1 |