Amr Ahmed

Amr Ahmed

Amr Ahmed is a Senior Staff Research Scientist at Google. He received his M.Sc and PhD degrees from the School of Computer Science, Carnegie Mellon University in 2009 and 2011, respectively. He received the best paper award at KDD 2014 , the best Paper Award at WSDM 2014, the 2012 ACM SIGKDD Doctoral Dissertation Award, and a best paper award (runner-up) at WSDM 2012. He co-chaired the WWW'18 track on Web Content Analysis and served as an Area Chair for IJCAI 2019, SIGIR 2019, SIGIR 2018, ICML 2018, ICML 2017, KDD 2016, WSDM 2015, ICML 2014, and ICDM 2014. His research interests include large-scale machine learning, data/web mining, user modeling, personalization, social networks and content analysis.
Authored Publications
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    Non-Stationary Off-policy Optimization
    Joey Hong
    Branislav Kveton
    Manzil Zaheer
    International Conference on Artificial Intelligence and Statistics (AISTATS) (2021)
    Exact and Approximate Hierarchical Clustering Using A*
    Craig Greenberg
    Sebastian Macaluso
    Nicholas Monath
    Patrick Flaherty
    Manzil Zaheer
    Kyle Cranmer
    Andrew McCallum
    Uncertainty in Artificial Intelligence (2021)
    Scalable Hierarchical Agglomerative Clustering
    Nick Monath
    Guru Prashanth Guruganesh
    Manzil Zaheer
    Andrew McCallum
    Gokhan Mergen
    Mert Terzihan
    Bryon Tjanaka
    Yuchen Wu
    Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2021), 1245–1255
    DAG-structured Clustering by Nearest-Neighbors
    Nicholas Monath
    Manzil Zaheer
    Andrew McCallum
    International Conference on Artificial Intelligence and Statistics (2021)
    Big Bird: Transformers for Longer Sequences
    Manzil Zaheer
    Guru Prashanth Guruganesh
    Joshua Ainslie
    Anirudh Ravula
    Qifan Wang
    Li Yang
    NeurIPS (2020)
    Latent Bandits Revisited
    Joey Hong
    Branislav Kveton
    Manzil Zaheer
    Advances in Neural Information Processing Systems 33 (NeurIPS 2020), pp. 13423-13433
    Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space
    Nick Monath
    Manzil Zaheer
    Daniel Silva
    Andrew McCallum
    The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’19) (2019)
    Uncovering Hidden Structure in Sequence Data via Threading Recurrent Models
    Manzil Zaheer
    Daniel Silva
    Yuchen Wu
    Shibani Sanan
    Surojit Chatterjee
    Proceedings of the 12 ACM International Conference on Web Search and Data Mining (2019), pp. 186-194