Houssam Nassif, PhD

Picture of Houssam Nassif
Welcome to my research page. Until 12/2022, I was a Principal Applied Scientist at Amazon. I am currently at Meta. For a glimpse at my projects and what I do, check these blog posts and products:


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
    Journals
    • Bayesian Meta-Prior Learning Using Empirical Bayes
      Nabi S, Nassif H, Hong J, Mamani H, and Imbens G
      Management Science, 68(3):1737-1755, 2022.
      (Paper, arXiv paper version, 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.
      (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
    • On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models
      Li B, Thomson AJ, Nassif H, Engelhard MW, and Page D
      Conference on Neural Information Processing Systems (NeurIPS'24), Vancouver, BC, 2024.
      (Paper, Slides, Poster, Code)

    • Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
      Fiez T, Nassif H, Chen YC, Gamez S, Jain L
      The Web Conference (WWW'24), Singapore, 2024.
      (Paper, Summary video, Poster)

    • Experimental Designs for Heteroskedastic Variance
      Weltz J, Fiez T, Laber E, Volfovsky A, Mason B, Nassif H, and Jain L
      Conference on Neural Information Processing Systems (NeurIPS'23), New Orleans, 2023.
      (Paper, Poster)

    • A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models
      Geng S, Nassif H, and Manzanares CA
      The Conference on Uncertainty in Artificial Intelligence (UAI'23), Pittsburgh, PA, pp. 647-657, 2023.
      (Paper, Poster)

    • Neural Insights for Digital Marketing Content Design
      Kong F, Li Y, Nassif H, Fiez T, Chakrabarti S, and Henao R
      International Conference on Knowledge Discovery and Data Mining (KDD'23), Long Beach, CA, pp. 4320-4332, 2023.
      (Paper, Poster, Summary video, Slides)

    • Enhancing Transistor Sizing in Analog IC Design using a Circuit-Focused Semi-Supervised Learning
      Mina R, Sakr GE, and Nassif H
      IEEE International Multidisciplinary Conference on Engineering Technology (IMCET'23), Beirut, Lebanon, pp. 223-228, 2023.
      (Paper, Slides)

    • Instance-Optimal PAC Algorithms for Contextual Bandits
      Li Z, Ratliff LJ, Nassif H, Jamieson K, and Jain L
      Conference on Neural Information Processing Systems (NeurIPS'22), New Orleans, pp. 37590-37603, 2022.
      (Paper, Slides, Poster, Video)

    • Adaptive Experimental Design and Counterfactual Inference
      Fiez T, Gamez S, Chen A, Nassif H, and Jain L
      ACM Conference on Recommender Systems (RecSys'22) Workshops, Seattle, 2022.
      (Paper, Slides, Poster, Video)

    • 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
      International Conference on Knowledge Discovery and Data Mining (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
      International Conference on Knowledge Discovery and Data Mining (KDD'17), Halifax, Canada, pp. 1813-1821, 2017.
      (Paper, Summary video, Poster, Additional slides, Award)

    • 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, Award)

    • 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)

    Patents
    • 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.
      (Patent)

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

    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)