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Nesime Tatbul

Nesime Tatbul

D-Index & Metrics

Computer Science

D-Index
36
Citations
12385
World Ranking
10975
National Ranking
4563

Overview

Nesime Tatbul is affiliated with MIT in the United States and has contributed extensively to the field of computer science. Their research output includes 56 publications predominantly in computer science, with significant focus on subfields such as artificial intelligence, signal processing, computer networks and communications, information systems, and computer vision and pattern recognition.

Tatbul's work covers a range of topics, which include:

  • Data Stream Mining Techniques
  • Data Management and Algorithms
  • Advanced Database Systems and Queries
  • Time Series Analysis and Forecasting
  • Cloud Computing and Resource Management
  • Scientific Computing and Data Management
  • Anomaly Detection Techniques and Applications

Their recent published papers feature research in various areas of data and database systems. Some of the notable papers include:

  • "Exathlon," 2021, Proceedings of the VLDB Endowment
  • "Flow-loss," 2021, Proceedings of the VLDB Endowment
  • "Robust Query Driven Cardinality Estimation under Changing Workloads," 2023, Proceedings of the VLDB Endowment
  • "Towards Observability Data Management at Scale," 2021, ACM SIGMOD Record
  • "Bao," 2022, ACM SIGMOD Record

These publications demonstrate engagement with prominent venues in database and data management research. Their frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • ACM SIGMOD Record
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Information Systems

Collaboration forms an essential part of Tatbul's scholarly activity. Frequent co-authors have included:

  • Ryan Marcus
  • Tim Kraska
  • Parimarjan Negi
  • Mohammad Alizadeh
  • Samuel Madden

The scope of their research spans both theoretical and applied aspects of data science, with a focus on challenges related to managing and processing data streams, query optimization, and system observability at scale.

Best Publications

  • Aurora: a new model and architecture for data stream management

    Daniel J. Abadi;Don Carney;Ugur Çetintemel;Mitch Cherniack

  • The Design of the Borealis Stream Processing Engine

    Daniel J. Abadi;Yanif Ahmad;Magdalena Balazinska;Mitch Cherniack

  • Aurora: a data stream management system

    D. Abadi;D. Carney;U. Çetintemel;M. Cherniack

  • Monitoring streams: a new class of data management applications

    Don Carney;Uǧur Çetintemel;Mitch Cherniack;Christian Convey

  • Load shedding in a data stream manager

    Nesime Tatbul;Uğur Çetintemel;Stan Zdonik;Mitch Cherniack

  • Proceedings of the VLDB Endowment

    Gustavo Alonso;Juliana Freire;Ahmet Saçan;Nesime Tatbul

  • Neo: a learned query optimizer

    Ryan Marcus;Parimarjan Negi;Hongzi Mao;Chi Zhang

  • Staying FIT: efficient load shedding techniques for distributed stream processing

    Nesime Tatbul;Uǧur Çetintemel;Stan Zdonik

  • Window-aware load shedding for aggregation queries over data streams

    Nesime Tatbul;Stan Zdonik

  • Neo: A Learned Query Optimizer

    Ryan Marcus;Parimarjan Negi;Hongzi Mao;Chi Zhang

  • Retrospective on Aurora

    Hari Balakrishnan;Magdalena Balazinska;Don Carney;Uğur Çetintemel

  • Plan-based complex event detection across distributed sources

    Mert Akdere;Uǧur Çetintemel;Nesime Tatbul

  • Distributed operation in the Borealis stream processing engine

    Yanif Ahmad;Bradley Berg;Uǧur Cetintemel;Mark Humphrey

  • Bao: Making Learned Query Optimization Practical

    Ryan Marcus;Parimarjan Negi;Hongzi Mao;Nesime Tatbul

  • SECRET: a model for analysis of the execution semantics of stream processing systems

    Irina Botan;Roozbeh Derakhshan;Nihal Dindar;Laura Haas

  • A demonstration of the BigDAWG polystore system

    A. Elmore;J. Duggan;M. Stonebraker;M. Balazinska

  • Data Ingestion for the Connected World.

    John Meehan;Cansu Aslantas;Stan Zdonik;Nesime Tatbul

  • Streaming data integration: Challenges and opportunities

    Nesime Tatbul

  • Confidence-based data management for personal area sensor networks

    Nesime Tatbul;Mark Buller;Reed Hoyt;Steve Mullen

  • S-Store: streaming meets transaction processing

    John Meehan;Nesime Tatbul;Stan Zdonik;Cansu Aslantas

  • DejaVu: declarative pattern matching over live and archived streams of events

    Nihal Dindar;Baris Güç;Patrick Lau;Asli Ozal

  • Exathlon: a benchmark for explainable anomaly detection over time series

    Vincent Jacob;Fei Song;Arnaud Stiegler;Bijan Rad

  • Precision and Recall for Time Series

    Nesime Tatbul;Tae Jun Lee;Stan Zdonik;Mejbah Alam

  • Bao: Learning to Steer Query Optimizers.

    Ryan Marcus;Parimarjan Negi;Hongzi Mao;Nesime Tatbul

Frequent Co-Authors

Asuman Dogac
Asuman Dogac SRDC Software Research & Development and Consultancy Corp.
Daniel J. Abadi
Daniel J. Abadi University of Maryland, College Park
Anand Ranganathan
Anand Ranganathan Unscrambl Inc.
Gustavo Alonso
Gustavo Alonso ETH Zurich
David Maier
David Maier Portland State University
Laura M. Haas
Laura M. Haas University of Massachusetts Amherst

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