Cagri Ozcaglar
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Publications (Google Scholar)

[By year][By type]

2021

  1. Unsupervised Learning of Entity Representations Using Graphs
    R. Ramanath, G. Polatkan, Q. Guo, C. Ozcaglar, K. Kenthapadi, S. Geyik
    Patent Issued, 2021.

  2. Feature Selection Impact Analysis for Statistical Models
    C. Ozcaglar, V. Dialani, S. Smoot, S. Geyik, A. Nair
    Patent Issued, 2021.

  3. Entity-Level Search Models with Tree Interaction Features
    C. Ozcaglar, S. Geyik, P. Sharma, B. Schmitz, E. Buchanan
    Patent Issued, 2021.

2020

  1. Generalized Linear Mixed Models (GLMix) for Improving Search
    C. Ozcaglar, R. Wu, J. Yang, A. Gupta, A. Nair
    Patent Issued, 2020.

  2. Uplift Modeling with Importance Weighting
    C. Ozcaglar, R. Ranjan, V. Parimi
    Patent Issued, 2020.

  3. Techniques for querying user profiles using neural networks
    R. Ramanath, G. Polatkan, Q. Guo, C. Ozcaglar, K. Kenthapadi, S. Geyik
    Patent Issued, 2020.

  4. Generating Candidates for Search Using Scoring / Retrieval Architecture
    R. Ramanath, G. Polatkan, Q. Guo, C. Ozcaglar, K. Kenthapadi, S. Geyik
    Patent Issued, 2020.

2019

  1. Entity Personalized Talent Search Models with Tree Interaction Features
    C. Ozcaglar, S. Geyik, B. Schmitz, P. Sharma, A. Shelkovnykov, Y. Ma, E. Buchanan
    WWW, 2019.

  2. Detecting Anomalous Candidate Recommendations
    C. Ozcaglar, K. Kenthapadi
    Patent Filed, 2019.

  3. Feedback-based Update of Candidate Recommendations
    K. Kenthapadi, C. Ozcaglar
    Patent Filed, 2019.

  4. Contextual Search Ranking Using Entity Topic Representations
    C. Ozcaglar, G. Borje, S. Geyik, G. Gulati, K. Thakkar
    Patent Filed, 2019.

  5. Data Selection Based on Career Transition Embeddings
    S. Wakankar, M. Meng, C. Ozcaglar, V. Abdrashitov
    Patent Filed, 2019.

2018

  1. Towards Deep and Representation Learning for Talent Search at LinkedIn
    R. Ramanath, H. Inan, G. Polatkan, B. Hu, Q. Guo, C. Ozcaglar, R. Wu, K. Kenthapadi, S. Geyik
    CIKM, 2018.

  2. Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned
    S. Geyik, Q. Guo, B. Hu, C. Ozcaglar, R. Wu, K. Kenthapadi
    SIGIR, 2018.

  3. Utilizing Search Facets Based on Project Context
    P. Cheung, E. Buchanan, C. Liao, D. Boyd, G. Gulati, F. Or, C. Ozcaglar
    Patent Filed, 2018.

2014

  1. Hybrid Coexpression Link Similarity Graph Clustering for Mining Biological Modules from Multiple Gene Expression Datasets
    S. Salem, C. Ozcaglar
    BioData Mining, 2014.

2013

  1. MFMS: Maximal Frequent Module Set Mining from Multiple Human Gene Expression Datasets
    S. Salem, C. Ozcaglar
    ACM SIGKDD International Workshop on Data Mining in Bioinformatics (BIOKDD), Chicago, August 2013.

  2. TB-vis: Visualizing TB Patient-pathogen Relationships
    K. P. Bennett, C. Ozcaglar, J. Ranganathan, S. Raghavan, J. Katz, D. Croft, B. Yener, A. Shabbeer
    Tuberculosis, 2013.

2012

  1. Crossing Minimization within Graph Embeddings
    A. Shabbeer, C. Ozcaglar, K. P. Bennett
    arXiv, 2012.

  2. Inferred Spoligoforest Topology Unravels Spatially Bimodal Distribution of Mutations in the DR Region
    C. Ozcaglar, A. Shabbeer, N. Kurepina, N. Rastogi, B. Yener, K. P. Bennett
    IEEE Transactions on NanoBioscience, 2012.

  3. Algorithmic Data Fusion Methods for Tuberculosis
    Ph.D. thesis, 2012.

  4. Host-pathogen Association Analysis of Tuberculosis Patients via Unified Biclustering Framework
    C. Ozcaglar, B. Yener, K. P. Bennett
    Rensselaer Polytechnic Institute, TR-12-05, 2012.

  5. Epidemiological Models of Mycobacterium tuberculosis Complex Infections
    C. Ozcaglar, A. Shabbeer, S. Vandenberg, B. Yener, K. P. Bennett
    Mathematical Biosciences, 2012.
    Most accessed paper of Mathematical Biosciences journal between March 2012 and December 2012.

  6. TB-Lineage: An Online Tool for Classification and Analysis of Strains of Mycobacterium tuberculosis complex
    A. Shabbeer, L. S. Cowan, C. Ozcaglar, N. Rastogi, S. L. Vandenberg, B. Yener, K. P. Bennett
    Infection, Genetics and Evolution, 2012.

  7. Web Tools for Molecular Epidemiology of Tuberculosis
    A. Shabbeer, C. Ozcaglar, B. Yener, K. P. Bennett
    Infection, Genetics and Evolution, 2012.
    Most accessed paper of Infection, Genetics and Evolution journal between December 2011 and June 2012.

2011

  1. Data-driven Insights into Deletions of Mycobacterium tuberculosis complex Chromosomal DR Region Using Spoligoforests
    C. Ozcaglar, A. Shabbeer, N. Kurepina, B. Yener, K. P. Bennett
    IEEE BIBM, Atlanta, November 2011.

  2. Visualization of Tuberculosis Patient and Mycobacterium tuberculosis complex Genotype Data via Host-pathogen Maps
    K. P. Bennett, C. Ozcaglar, J. Ranganathan, S. Raghavan, J. Katz, D. Croft, B. Yener, A. Shabbeer
    IEEE BIBM Workshop on Computational Advances in Molecular Epidemiology, Atlanta, November 2011.

  3. Knowledge-based Bayesian network for the Classification of Mycobacterium tuberculosis complex Sublineages
    M. Aminian, A. Shabbeer, K. Hadley, C. Ozcaglar, S. Vandenberg, K. P. Bennett
    ACM BCB, Chicago, August 2011.

  4. Sublineage Structure Analysis of Mycobacterium tuberculosis complex Strains with Multiple-biomarker Tensors
    C. Ozcaglar, A. Shabbeer, S. Vandenberg, B. Yener, K. P. Bennett
    BMC Genomics, 2011.

2010

  1. Examining the Sublineage Structure of Mycobacterium tuberculosis complex Strains with Multiple-biomarker Tensors
    C. Ozcaglar, A. Shabbeer, S. Vandenberg, B. Yener, K. P. Bennett
    IEEE BIBM, Hong Kong, December 2010.

  2. Optimal Embedding of Heterogeneous Graph Data with Edge Crossing Constraints
    A. Shabbeer, C. Ozcaglar, M. Gonzalez, K. P. Bennett
    NIPS Workshop on Challenges of Data Visualization, Whistler, BC, Canada, 2010.

  3. Multiple-biomarker Tensor Analysis for Tuberculosis Lineage Identification
    C. Ozcaglar, A. Shabbeer, S. Vandenberg, B. Yener, K. P. Bennett
    NIPS Workshop on Tensors, Kernels and Machine Learning, Whistler, BC, Canada. 2010.

  4. A Clustering Framework for Mycobacterium tuberculosis complex Strains Using Multiple-biomarker Tensors
    C. Ozcaglar, A. Shabbeer, S. Vandenberg, B. Yener, K. P. Bennett
    Rensselaer Polytechnic Institute, TR-10-08, 2010.

2008

  1. Classification of Email Messages into Topics Using Latent Dirichlet Allocation
    M.S. thesis, 2008.

  2. MetPetDB: A Database for Metamorphic Geochemistry
    F. S. Spear, J. M. Pyle, S. Adali, B. Szymanski, A. Waters, Z. Linder, C. Ozcaglar, S. Pearce
    Rensselaer Polytechnic Institute, TR-08-14, 2008.

2007

  1. MetPetDB: The Unique Aspects of Metamorphic Geochemical Data and Their Influence on Data Model, User Interface and Collaborations
    J. M. Pyle, F. S. Spear, S. Adali, B. Szymanski, S. Pearce, A. Waters, Z. Linder, C. Ozcaglar
    Geological Society of America Abstracts with Programs, Denver, 2007