Houssam Nassif, PhD

Picture of Houssam Nassif
I am currently a Machine Learning Scientist at Amazon. I was also the Workflow Chair of AISTATS'15.


Peer Reviewed Publications

Below is a list of my peer-reviewed publications. You can check my Google Scholar page. I also have various additional public abstracts, posters, and talks.

    Journals
    • Rational Polypharmacology: Systematically Identifying and Engaging Multiple Drug Targets To Promote Axon Growth (Cover Article)
      Al-Ali H, Lee DH, Danzi MC, Nassif H, Gautam P, Wennerberg K, Zuercher B, Drewry DH, Lee JK, Lemmon VP, and Bixby JL
      ACS Chemical Biology, 10(8):1939-1951, 2015.
      (Paper, Cover graphic)

    • Predicting invasive breast cancer versus DCIS in different age groups
      Ayvaci M, Alagoz O, Chhatwal J, Munoz del Rio A, Sickles EA, Nassif H, Kerlikowske K, and Burnside ES
      BMC Cancer, 14:584, 2014.
      (Paper)

    • Automatic Classification of Mammography Reports by BI-RADS Breast Tissue Composition Class
      Percha B, Nassif H, Lipson J, Burnside E, and Rubin D
      Journal of the American Medical Informatics Association (JAMIA), 19(5):913-916, 2012.
      (Paper, Code)

    • Automated Identification of Protein-Ligand Interaction Features Using Inductive Logic Programming: A Hexose Binding Case Study
      Santos JCA, Nassif H, Page D, Muggleton SH, and Sternberg MJE
      BMC Bioinformatics, 13:162, 2012.
      (Paper, Code, Data, Input)

    • Prediction of Protein-Glucose Binding Sites Using Support Vector Machines
      Nassif H, Al-Ali H, Khuri S, and Keyrouz W
      Proteins: Structure, Function and Bioinformatics, 77(1):121-132, 2009.
      (Paper, Code, Data, Input)

    Conferences
    • Adaptive, Personalized Diversity for Visual Discovery (Best Paper Award)
      Teo CH, Nassif H, Hill D, Srinavasan S, Goodman M, Mohan V, and Vishwanathan SVN
      ACM Conference on Recommender Systems (RecSys'16), Boston, pp. 35-38, 2016.
      (Paper, Slides)

    • Diversifying Music Recommendations
      Nassif H, Cansizlar KO, Goodman M, and Vishwanathan SVN
      International Conference on Machine Learning (ICML'16) Workshops, New York, 2016.
      (Paper, Slides, Poster)

    • Support Vector Machines for Differential Prediction
      Kuusisto F, Santos Costa V, Nassif H, Burnside ES, Page D, and Shavlik J
      European Conference on Machine Learning (ECML'14), Nancy, France, pp. 50-65, 2014.
      (Paper, Slides, Poster, Code)

    • Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling
      Nassif H, Kuusisto F, Burnside ES, Page D, Shavlik J, and Santos Costa V
      European Conference on Machine Learning (ECML'13), Prague, pp. 595-611, 2013.
      (Paper, Slides, Poster, Code)

    • Uplift Modeling with ROC: An SRL Case Study
      Nassif H, Kuusisto F, Burnside ES, and Shavlik J
      International Conference on Inductive Logic Programming (ILP'13) Late Breaking Papers, Rio de Janeiro, Brazil, pp. 40-45, 2013.
      (Paper, Slides, Poster)

    • Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms
      Liu J, Page D, Nassif H, Shavlik J, Peissig P, McCarty C, Onitilo AA, and Burnside E
      American Medical Informatics Association Symposium (AMIA'13), Washington, DC, pp. 876-885, 2013.
      (Paper, Slides)

    • Using Machine Learning to Identify Benign Cases with Non-Definitive Biopsy
      Kuusisto F, Dutra I, Nassif H, Wu Y, Klein M, Neuman H, Shavlik J, and Burnside E
      IEEE International Conference on E-Health Networking, Application & Services (HealthCom'13), Lisbon, Portugal, pp. 283-285, 2013.
      (Paper, Poster)

    • Relational Differential Prediction
      Nassif H, Santos Costa V, Burnside ES, and Page D
      European Conference on Machine Learning (ECML'12), Bristol, UK, pp. 617-632, 2012.
      (Paper, Slides, Poster, Code, Michalski trains data)

    • Logical Differential Prediction Bayes Net, Improving Breast Cancer Diagnosis for Older Women
      Nassif H, Wu Y, Page D, and Burnside ES
      American Medical Informatics Association Symposium (AMIA'12), Chicago, pp. 1330-1339, 2012.
      (Paper, Slides, Logic code)

    • Extracting BI-RADS Features from Portuguese Clinical Texts
      Nassif H, Cunha F, Moreira IC, Cruz-Correia R, Sousa E, Page D, Burnside E, and Dutra I
      IEEE International Conference on Bioinformatics and Biomedicine (BIBM'12), Philadelphia, pp. 539-542, 2012.
      (Paper, Slides, Code)

    • Integrating Machine Learning and Physician Knowledge to Improve the Accuracy of Breast Biopsy
      Dutra I, Nassif H, Page D, Shavlik J, Strigel RM, Wu Y, Elezaby ME, and Burnside E
      American Medical Informatics Association Symposium (AMIA'11), Washington, DC, pp. 349-355, 2011.
      (Paper, Slides)

    • Uncovering Age-Specific Invasive and DCIS Breast Cancer Rules Using Inductive Logic Programming
      Nassif H, Page D, Ayvaci M, Shavlik J, and Burnside ES
      ACM International Health Informatics Symposium (IHI'10), Arlington, VA, USA, pp. 76-82, 2010.
      (Paper, Slides, Code)

    • Information Extraction for Clinical Data Mining: A Mammography Case Study
      Nassif H, Woods R, Burnside ES, Ayvaci M, Shavlik J, and Page D
      IEEE International Conference on Data Mining (ICDM'09) Workshops, Miami, pp. 37-42, 2009.
      (Paper, Slides, Code)

    • An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge
      Nassif H, Al-Ali H, Khuri S, Keyrouz W, and Page D
      International Conference on Inductive Logic Programming (ILP'09), Leuven, Belgium, pp. 149-165, 2009.
      (Paper, Slides, Feature extraction code, ILP code, Data, Input)

    Theses
    • Differential Relational Learning
      Nassif H
      PhD Dissertation, University of Wisconsin - Madison, 2012.
      (Thesis, Slides)

    • A Pattern Recognition Based Model for Characterizing and Predicting Glucose-Binding Sites
      Nassif H
      MS Thesis, American University of Beirut, 2006.
      (Thesis, Slides)

 
Website last updated: June 2016