World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9627
World Ranking
7491
National Ranking
3259

Overview

Bugra Gedik is affiliated with Royal Caribbean Cruises in the United States and has contributed to research primarily in the field of Computer Science. Their work spans multiple subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, General Economics, Econometrics and Finance, and Social Psychology.

The scientist's research addresses topics such as Domain Adaptation and Few-Shot Learning, Multimodal Machine Learning Applications, and Advanced Image and Video Retrieval Techniques. They have also contributed to studies on Air Traffic Management and Optimization, Aviation Industry Analysis and Trends, Human-Automation Interaction and Safety, and Human Mobility and Location-Based Analysis.

Bugra Gedik has published in several venues, with frequent appearances in arXiv (Cornell University), the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), and the IEEE Transactions on Intelligent Transportation Systems.

  • Revisiting Weakly Supervised Pre-Training of Visual Perception Models, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Forecasting Flight Delays Using Clustered Models Based on Airport Networks, 2020, IEEE Transactions on Intelligent Transportation Systems
  • Revisiting Weakly Supervised Pre-Training of Visual Perception Models, 2022, arXiv (Cornell University)
  • SLIM: Scalable Linkage of Mobility Data, 2020, arXiv (Cornell University)

Co-authors who frequently collaborate with Bugra Gedik include Mannat Singh, Laura Gustafson, Aaron Adcock, Raj Prateek Kosaraju, and Dhruv Mahajan.

Best Publications

  • Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms

    B. Gedik;Ling Liu

  • Location Privacy in Mobile Systems: A Personalized Anonymization Model

    B. Gedik;Ling Liu

  • SPADE: the system s declarative stream processing engine

    Bugra Gedik;Henrique Andrade;Kun-Lung Wu;Philip S. Yu

  • A catalog of stream processing optimizations

    Martin Hirzel;Robert Soulé;Scott Schneider;Buğra Gedik

  • Elastic Scaling for Data Stream Processing

    Bugra Gedik;Scott Schneider;Martin Hirzel;Kun-Lung Wu

  • ASAP: An Adaptive Sampling Approach to Data Collection in Sensor Networks

    B. Gedik;Ling Liu;P.S. Yu

  • A Customizable k-Anonymity Model for Protecting Location Privacy

    Bugra Gedik;Ling Liu

  • MobiEyes: Distributed Processing of Continuously Moving Queries on Moving Objects in a Mobile System

    Buğra Gedik;Ling Liu

  • Streaming algorithms for k-core decomposition

    Ahmet Erdem Saríyüce;Buğra Gedik;Gabriela Jacques-Silva;Kun-Lung Wu

  • A distributed approach to node clustering in decentralized peer-to-peer networks

    Lakshmish Ramaswamy;B. Gedik;L. Liu

  • Elastic scaling of data parallel operators in stream processing

    Scott Schneider;Henrique Andrade;Bugra Gedik;Alain Biem

  • MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries

    B. Gedik;Ling Liu

  • PINCO: a pipelined in-network compression scheme for data collection in wireless sensor networks

    T. Arici;B. Gedik;Y. Altunbasak;L. Liu

  • Fundamentals of Stream Processing: Application Design, Systems, and Analytics

    Henrique C. M. Andrade;Bugra Gedik;Deepak S. Turaga

  • IBM streams processing language: analyzing big data in motion

    M. Hirzel;H. Andrade;B. Gedik;G. Jacques-Silva

  • Revisiting Weakly Supervised Pre-Training of Visual Perception Models

    Unknown

  • Partitioning functions for stateful data parallelism in stream processing

    Buğra Gedik

  • Failure recovery for stream processing applications

    Henrique Andrade;Bugra Gedik;Gabriela Jacques Da Silva;Kun-Lung Wu

  • COLA: optimizing stream processing applications via graph partitioning

    Rohit Khandekar;Kirsten Hildrum;Sujay Parekh;Deepak Rajan

  • Method for generating a distributed stream processing application

    Henrique Andrade;Bugra Gedik;Kun-Lung Wu

  • PeerCQ: a decentralized and self-configuring peer-to-peer information monitoring system

    B. Gedik;Ling Liu

Frequent Co-Authors

Kun-Lung Wu
Kun-Lung Wu IBM (United States)
Ling Liu
Ling Liu Georgia Institute of Technology
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Ümit V. Çatalyürek
Ümit V. Çatalyürek Georgia Institute of Technology
Rajesh Bordawekar
Rajesh Bordawekar IBM (United States)
Joel L. Wolf
Joel L. Wolf IBM (United States)
Ravishankar K. Iyer
Ravishankar K. Iyer University of Illinois at Urbana-Champaign
Mudhakar Srivatsa
Mudhakar Srivatsa IBM (United States)
Zbigniew Kalbarczyk
Zbigniew Kalbarczyk University of Illinois at Urbana-Champaign
Yucel Altunbasak
Yucel Altunbasak Georgia Institute of Technology

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