Houssam Nassif, PhD

Picture of Houssam Nassif
Additional Public Presentations

In addition to my peer-reviewed publications, here is a list of my other public talks, posters and abstracts.

  • Solving Inverse Reinforcement Learning, Bootstrapping Bandits, and Adaptive Recommendation
    Nassif H
    REVEAL 2020 Workshop, RecSys'20, Virtual, 2020.
    (Slides, Abstract)

  • Solving Inverse Reinforcement Learning, and Bandit Adaptive Recommendation
    Nassif H
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'20), Virtual, 2020.
    (Slides, Video)

  • Bayesian Meta-Prior Learning Using Empirical Bayes
    Nabi S, Nassif H, Hong J, Mamani H, and Imbens G
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'20), Virtual, 2020.
    (Slides, Video)

  • Industrial Data Science: Content Recommendation Examples
    Nassif H
    University of Miami Data Analytics Student Association seminar series, Miami, FL, 2020.
    (Slides)

  • An Efficient Bandit Algorithm for Realtime Multivariate Optimization
    Nassif H
    2nd AUB North American Computer Science Alumni Reunion, Palo Alto, CA, 2020.
    (Slides)

  • Multi-Armed Bandits: Introduction and Extensions
    Nassif H
    Topics in Machine Learning lecture, Econ 517 A: Foundations Of Economic Analysis, University of Washington, Seattle, WA, 2020.
    (Slides, Course)

  • ML in practice: Thinking Like a Scientist
    Nassif H
    Amazon MENA Tech (AMTECH) Conference, Amman, Jordan, 2019.
    (Slides)

  • Industrial Data Science: Content Recommendation Examples
    Nassif H
    Capstone Guest Speaker Series, Bellevue College, Bellevue, WA, 2019.
    (Slides)

  • Industrial Data Science: Amazonian Perspective
    Nassif H
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'19), Seattle, WA, 2019.
    (Slides)

  • Decoupling Learning Rates Using Empirical Bayes
    Nabi S, Nassif H, Hong J, Mamani H, and Imbens G
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'19), Seattle, WA, 2019.
    (Slides)

  • Machine Learning for Content Recommendation
    Nassif H
    Nike Content Domain Talk Series, Beaverton, OR, 2018.
    (Slides)

  • A practitioner's perspective on Artificial Intelligence
    Nassif H
    UK Lebanon Tech Hub Tech Talk Series, Beirut, Lebanon, 2018.
    (Slides)

  • Adaptive, Personalized Diversity for Visual Discovery
    Nassif H
    1st AUB North American Computer Science Alumni Reunion, Harvard, Cambridge, MA, 2017.
    (Slides)

  • Diversifying Amazon Recommendations
    Nassif H
    Seminar Series special edition, University of Miami Computer Science Department, Miami, FL, 2017.
    (Slides)

  • A platform technology to rapidly identify cancer drug targets and design personalized (single and combinatorial) drug therapies
    Al-Ali H, Nassif H, Gautam P, Wennerberg K, Bixby JL, and Lemmon VP
    Florida Academic Cancer Center Alliance Retreat (FACCA'16), Miami, FL, 2016.
    (Poster)

  • Combining phenotypic and biochemical screening to identify drug targets, exploit polypharmacology, and personalize treatment
    Al-Ali H, Lee DH, Danzi MC, Azzam D, Nassif H, Gautam P, Wennerberg K, Soellner M, Xu XM, Lee JK, Lemmon VP, and Bixby JL
    1st Systems Biology Data Science Symposium (SBDSS'16), Miami, FL, 2016.
    (Poster)

  • Recommendation challenges at Amazon: Airstream use case
    Nassif H
    18th International Conference on Artificial Intelligence and Statistics (AISTATS'15), San Diego, CA, 2015.
    (Slides, Poster)

  • Guest Speaker
    Nassif H
    11th American University of Beirut Computer Science Alumni Chapter Reunion, Beirut, Lebanon, 2014.
    (Address)

  • 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
    LifeScience Alley Conference (LSA'13), Minneapolis, MN, 2013.
    (Poster)

  • Relational Differential Prediction
    Nassif H, Santos Costa V, Burnside ES, and Page D
    7th Annual University of Wisconsin Carbone Cancer Center Research Retreat (UWCCC'13), Madison, WI, 2013.
    (Poster)

  • Automatic Extraction of BI-RADS Features from Cross-Institution and Cross-Language Free-Text Mammography Reports
    Nassif H, Kitchner T, Cunha F, Moreira IC, and Burnside ES
    Radiological Society of North America Annual Meeting (RSNA'12), Chicago, 2012.
    (Abstract, Slides)

  • Characterizing and Predicting Hexose-Binding Sites
    Nassif H
    Computation and Informatics in Biology and Medicine Seminar (CIBM), Madison, WI, 2011.
    (Slides)

  • Differential Prediction Using Inductive Logic Programming
    Nassif H
    PhD Thesis Proposal, University of Wisconsin - Madison, 2011.
    (Slides)

  • Automatic Extraction of Breast Density Information from Mammography Reports
    Percha B, Nassif H, Lipson J, Burnside E, and Rubin D
    Radiological Society of North America Annual Meeting (RSNA'11), Chicago, 2011.
    (Abstract, Slides)

  • Computational Techniques to Improve the Early Diagnosis of Breast Cancer
    Burnside ES, Woods R, Ayer T, Ayvaci M, Alagoz O, Oliphant L, Liu J, Nassif H, Page CD, Shavlik J, and Gustafson DH
    4th Annual University of Wisconsin Carbone Cancer Center Research Retreat (UWCCC'10), Madison, WI, 2010.
    (Poster)

  • Superior Performance of Bayesian Networks in Predicting the Risk of Invasive Vs. In-Situ Breast Cancer in Older Women
    Ayvaci M, Alagoz O, Nassif H, Sickles E, and Burnside ES
    31st Annual Meeting of the Society for Medical Decision Making (SMDM'09), Los Angeles, 2009.
    (Abstract, Poster)

  • Age Stratified Risk Prediction of Invasive versus In-situ Breast Cancer: A Logistic Regression Model
    Ayvaci M, Alagoz O, Chhatwal J, Lindstrom M, Nassif H, and Burnside ES
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'09), San Diego, CA, 2009.
    (Slides)

  • Computational Techniques to Improve the Early Diagnosis of Breast Cancer
    Burnside ES, Woods R, Ayer T, Ayvaci M, Alagoz O, Oliphant L, Liu J, Nassif H, Page CD, Shavlik J, and Gustafson DH
    3rd Annual University of Wisconsin Carbone Cancer Center Research Retreat (UWCCC'09), Madison, WI, 2009.
    (Poster)

  • Predicting the Risk of Invasive Versus In Situ Breast Cancer to Aid Clinical Management
    Chhatwal J, Alagoz O, Nassif H, Sickles EA, Jovais C, and Burnside ES
    30st Annual Meeting of the Society for Medical Decision Making (SMDM'08), Philadelphia, PA, 2008.
    (Abstract, Poster)

  • Bayesian Network for Predicting Invasive and In-Situ Breast Cancer Using Mammographic Findings
    Chhatwal J, Alagoz O, Burnside ES, Nassif H, and Sickles EA
    The Institute for Operations Research and the Management Sciences Annual Meeting (INFORMS'08), Washigton, DC, 2008.
    (Slides)

  • Characteristics of Sugar Binding Sites of Enzymatic Proteins: Probing the Spatial and Chemical Features Using SVM
    Khuri S, Nassif H, Al-Ali H, and Keyrouz W
    Annual American University of Beirut Bioinformatics Research and Applications Team Retreat (BRAT'05), Beirut, Lebanon, 2005.
    (Slides)

  • Amino Acid Composition and Folding of the Monosaccharide Binding Sites of Enzymic Proteins
    Khuri S, Nassif H, Al-Ali H, Khalaf K, Khachfe H, and Keyrouz W
    International Conference for Bioinformatics and its Applications (ICBA'04), Fort Lauderdale, FL, 2004.
    (Abstract, Poster)

 
Website last updated: September 2020