Shobeir Fakhraei

Shobeir Fakhraei, Ph.D.

I am a machine learning scientist at Amazon. Prior to Amazon, I have worked at various research institutes including Information Sciences Institute at University of Southern California (USC), Microsoft Research Redmond (MSR), Yahoo! Labs Sunnyvale, University of California Santa Cruz (UCSC), and Henry Ford Health System, and startup companies such as Turi (ex. Graphlab) and The Meet Group (ex. Tagged).
I received my Ph.D. from the Department of Computer Science, University of Maryland College Park (UMD) advised by Lise Getoor, Ph.D.
My research interests include Machine Learning and Data Science especially in areas related to applications of Deep Learning and Probabilistic Graphical Models in Multi-Relational and Heterogeneous Graph Mining, Information Extraction and Integration, Recommender Systems, Spam and Fraud Detection, Statistical Relational Learning, and Biomedical and Health Informatics. I have also received M.Sc. degrees in Bioinformatics and Software Engineering.
I have published papers, been the program committee, and organized workshops at conferences such as KDD, ICML, NIPS, WWW, SDM, ICDM, and WSDM.



2019: 2018: 2017:



Journal Articles

  • A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction
    Dhanya Sridhar, Shobeir Fakhraei, Lise Getoor
    Bioinformatics 2016
    [PDF] [BibTeX]

  • Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic
    Shobeir Fakhraei, Bert Huang, Louiqa Raschid, Lise Getoor
    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) 2014
    [PDF] [BibTeX] [Data and Code] [Featured on the cover]

  • Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Farshad Fotouhi
    Elsevier Expert Systems with Applications (ESWA) 2014
    [PDF] [BibTeX]

Conference Proceedings

  • NSEEN: Neural Semantic Embedding for Entity Normalization
    Shobeir Fakhraei, Joel Mathew, Jose Luis Ambite
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2019
    [PDF] [BibTeX]

  • HeteroNAM: International Workshop on Heterogeneous Networks Analysis and Mining
    Shobeir Fakhraei, Yanen Li, Yizhou Sun, Tim Weninger
    ACM International Conference on Web Search and Data Mining (WSDM) 2018
    [PDF] [BibTeX]

  • Collective Spammer Detection in Evolving Multi-Relational Social Networks
    Shobeir Fakhraei, James Foulds, Madhusudana Shashanka, Lise Getoor
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2015
    [PDF] [BibTeX] [Slides] [Poster] [Data and Code] [Dato Conf. Video]

  • HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems
    Pigi Kouki, Shobeir Fakhraei, James Foulds, Magdalini Eirinaki, Lise Getoor
    ACM Conference on Recommender Systems (RecSys) 2015
    [PDF] [BibTeX] [Code]

  • Predictable Dual-View Hashing
    Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Hal Daume III, Larry Davis
    International Conference on Machine Learning (ICML) 2013
    [PDF] [BibTeX] [Slides] [Poster] [Code] [Video]

  • Consensus Feature Ranking in Datasets with Missing Values
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Farshad Fotouhi, Kost Elisevich
    IEEE International Conference on Machine Learning and Applications (ICMLA) 2010
    [PDF] [BibTeX] [Poster]

  • Attribute Ranking for Lateralizing Focal Epileptogenicity in Temporal Lobe Epilepsy
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Kost Elisevich, Farshad Fotouhi,
    IEEE Iranian Conference of Biomedical Engineering (ICBME) 2010
    [PDF] [BibTeX] [Slides]

  • Aspect Extraction from Software Design Model
    Shobeir Fakhraei, Seyed-Hassan Mirian-Hosseinabadi
    International CSI Computer Conference (CSICC) 2007
    [PDF] [BibTeX]

Book Chapters

  • Data Analytics for Pharmaceutical Discoveries
    Shobeir Fakhraei, Eberechukwu Onukwugha, Lise Getoor
    Healthcare Data Analytics, CRC Press 2015
    [PDF] [BibTeX]

Workshop Proceedings

  • Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping
    Joel Mathew, Shobeir Fakhraei, Jose Luis Ambite
    ICML Workshop on Computational Biology 2019
    [PDF] [BibTeX]

  • Towards Automated Hypothesis Testing in Neuroscience
    Daniel Garijo*, Shobeir Fakhraei*, Varun Ratnakar, Qifan Yang, Hanna Endrias, Yibo Ma, Regina Wang, Michael Bornstein, Joanna Bright, Yolanda Gil, Neda Jahanshad (*equal contribution)
    VLDB Workshop on Data Management and Analytics for Medicine and Healthcare 2019
    [PDF] [BibTeX]

  • Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks
    Shobeir Fakhraei, Dhanya Sridhar, Jay Pujara, Lise Getoor
    KDD Workshop on Mining and Learning with Graphs (MLG) 2016
    [PDF] [BibTeX]

  • Collective Inference and Multi-Relational Learning for Drug-Target Interaction Prediction
    Shobeir Fakhraei, Bert Huang, Lise Getoor
    NIPS Workshop on Machine Learning in Computational Biology (MLCB) 2013
    [PDF] [BibTeX] [Poster] [Journal version]

  • Drug-Target Interaction Prediction for Drug Repurposing with Probabilistic Similarity Logic
    Shobeir Fakhraei, Louiqa Raschid, Lise Getoor
    ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD) 2013
    [PDF] [BibTeX] [Slides] [Journal version]

  • Confident Surgical Decision Making in Temporal Lobe Epilepsy by Heterogeneous Classifier Ensembles
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Kost Elisevich, Kourosh Jafari-Khouzani, Farshad Fotouhi
    IEEE ICDM Workshop on Biological Data Mining and its Applications in Healthcare (BIODM) 2011
    [PDF] [BibTeX] [Slides]

  • Confidence in Medical Decision Making: Application in Temporal Lobe Epilepsy Data Mining
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Farshad Fotouhi, Kost Elisevich
    ACM SIGKDD Workshop on Data Mining for Medicine and Healthcare (DMMH) 2011
    [PDF] [BibTeX] [Poster]

  • Effect of classifiers in consensus feature ranking for biomedical datasets
    Shobeir Fakhraei, Hamid Soltanian-Zadeh, Farshad Fotouhi, Kost Elisevich
    ACM CIKM Workshop on Data and Text Mining in Biomedical Informatics (DTMBIO) 2010
    [PDF] [BibTeX] [Slides]

Professional Experience


  • University of Southern California, Los Angeles CA
    Research Scientist, (Research: Deep Semantic Embedding and Information Extraction)
  • University of Maryland, College Park MD
    Research Assistant, (Research: Multi-Relational Graph Mining, Statistical Relational Learning)
  • University of California, Santa Cruz CA
    Visiting Research Scholar, (Research: Link Prediction and Recommender Systems, Collective Classification)
  • Wayne State University, Detroit MI
    Instructor, Research Assistant, Teaching Assistant, (Research: Feature Selection, Classification Uncertainty in Medical Applications)

Research Industry

  • Microsoft Research, Redmond WA
    Research Scientist Intern, (Research: Email to Meeting Transfer Patterns)
  • Yahoo! Research (Labs), Sunnyvale CA
    Research Scientist Intern, (Research: Context-aware Recommender Systems)
  • Turi (Dato) Inc. / Ifwe (Tagged) Inc., Seattle WA / San Francisco CA
    Data Science Research Intern, (Research: Heterogeneous Social Networks Spam Detection)
  • Henry Ford Health System, Detroit MI
    Visiting Researcher, (Research: Temporal Lobe Epilepsy Lateralization)


University of Southern California, CA

Wayne State University, MI

  • Fundamental Structures in Computer Science and Lab (CSC 1500-1501), Instructor
  • Data Mining Algorithms and Applications (CSC 7810), Teaching Assistant
  • Graduate Seminar (CSC 8990), Course Coordinator
  • Introduction to Computer Science (CSC 1000), Lab Instructor

Sharif University of Technology

  • Software Engineering Lab, Lab Instructor

University of Applied Science and Technology

  • Introduction to Computer Science, Instructor
  • Internet Fundamentals and Web Programming, Instructor
  • Multimedia Systems, Instructor
  • Computer Networks, Instructor
  • Database Systems and Lab, Instructor
  • Data Structures and Algorithms, Instructor
  • Information Storage and Retrieval, Instructor
  • Advanced Computer Programming (C++), Instructor
  • Computer Programming (Introduction to Algorithms), Instructor

Academic Services

Grant Proposal Panelist

  • National Science Foundation - CISE Review Panel 2018 (Panelist)

Conference and Workshop Organizer and Chair

  • ACM SIGKDD International Workshop on Mining and Learning with Graphs (MLG): 15th-2019 (Organizer), 14th-2018 (Organizer), 13th-2017 (Organizer), 12th-2016 (Organizer)
  • ACM WSDM International Workshop on Heterogeneous Networks Analysis and Mining (HeteroNAM): 1st-2018 (Founding Organizer)
  • International Conference on Very Large Data Bases (VLDB): 2019 (Volunteer Co-Chair)
  • SIAM International Conference on Data Mining (SDM): 2018 (Session Chair)
  • Graph Mining Reading Group at Information Science Institute, University of Southern California: 2018 (Founding Organizer)

Journal Editor

  • Applied Network Science, Machine Learning with Graphs Special Issue: 2018 (Lead Guest Editor)

Journal Reviewer

  • Journal of Machine Learning Research (JMLR): 2018, 2019
  • IEEE Transactions on Knowledge & Data Eng. (TKDE): 2013, 2014, 2015, 2016, 2017, 2018
  • Plos One: 2019
  • Springer Data Mining & Knowledge Discovery (DAMI): 2018
  • Bioinformatics (Oxford Academic): 2018
  • Briefings in Bioinformatics: 2017
  • IEEE Journal of Biomedical and Health Informatics (JBHI): 2015
  • Elsevier Journal of Theoretical Biology (JTB): 2015
  • PeerJ Open Access Biological and Medical Sciences Journal: 2015
  • Elsevier Expert Systems with Applications (ESWA): 2016, 2017
  • ACM Transactions on Intelligent Systems and Technology (TIST): 2012

Program Committee

  • Neural Information Processing Systems (NeurIPS): 2014, 2015, 2019
  • International Conference on Machine Learning (ICML): 2019
  • ACM International Conf. on Knowledge Discovery & Data Mining (KDD): 2018, 2019
  • The Web Conference (WWW): 2018, 2019
  • SIAM International Conference on Data Mining (SDM): 2018, 2019
  • Association for the Advancement of Artificial Intelligence Conference (AAAI): 2019
  • International Joint Conference on Artificial Intelligence (IJCAI): 2016
  • International Conf. on Advances in Social Networks Analysis & Mining (ASONAM): 2019
  • Complex Networks: 2018, 2019
  • IEEE Workshop at the Intersection of Graph Algorithms & Machine Learning (GraML): 2018
  • IEEE Workshop on High Performance Big Graph Data Analysis, & Mining (BigGraphs): 2017
  • ACM SIGKDD Workshop on Outlier Definition, Detection & Description (ODD): 2016
  • International Conf. on Pervasive Computing Technologies for Healthcare (PervasiveHealth): 2013





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