Houssam Nassif, PhD

Picture of Houssam Nassif
Welcome to my research page. I am currently a Principal Applied Scientist at Amazon. Here is my Google Scholar page.

Below is a list of my peer-reviewed publications, including four award-winning papers. I also have various additional public abstracts, posters, and talks.

Peer Reviewed Publications

    • Bayesian Meta-Prior Learning Using Empirical Bayes
      Nabi S, Nassif H, Hong J, Mamani H, and Imbens G
      Management Science, accepted, 2021.
      (Paper, Slides, Video)

    • 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, Follow-up Poster, Follow-up Poster)

    • 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.

    • 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)

    • Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
      Jun KS, Jain L, Mason B, and Nassif H
      International Conference on Machine Learning (ICML'21), Virtual, pp. 5148-5157, 2021.
      (Paper, Slides, Extended slides, Video)

    • Deep PQR: Solving Inverse Reinforcement Learning using Anchor Actions
      Geng S, Nassif H, Manzanares C, Reppen M, and Sircar R
      International Conference on Machine Learning (ICML'20), Virtual, pp. 3431-3441, 2020.
      (Paper, Slides, Additional slides, Video, Additional video)

    • Seeker: Real-Time Interactive Search
      Biswas A, Pham TT, Vogelsong M, Snyder B, and Nassif H
      Knowledge Discovery in Databases Conference (KDD'19), Anchorage, Alaska, pp. 2867-2875, 2019.
      (Paper, Poster, Summary video, Slides, Video)

    • Contextual Multi-Armed Bandits for Causal Marketing (Amazon Research Scientist Summit Best Paper Award)
      Sawant N, Namballa CB, Sadagopan N, and Nassif H
      International Conference on Machine Learning (ICML'18) Workshops, Stockholm, Sweden, 2018.
      (Paper, Poster)

    • An efficient bandit algorithm for realtime multivariate optimization (Audience Appreciation Award)
      Hill D, Nassif H, Liu Y, Iyer A, and Vishwanathan SVN
      Knowledge Discovery in Databases Conference (KDD'17), Halifax, Canada, pp. 1813-1821, 2017.
      (Paper, Summary video, Poster, Additional slides)

    • Adaptive, Personalized Diversity for Visual Discovery (Best Short 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, Video, Additional 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), 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)

    • Artificial Intelligence System For Optimizing Network-Accessible Content
      Nassif H, Hill D, Hu T, Iyer AM, Liu J, Liu Y, Srinivasan S, and Swaminathan V
      US Patent 11126785, 2021.

    • Content Selection Algorithms
      Srinavasan S, Nassif H, Mohan V, Swaminathan V, and Goodman MH
      US Patent 9817846, 2017.

    • 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: September 2020