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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DAG-structured Clustering by Nearest-Neighbors
Nicholas Monath
Manzil Zaheer
Andrew McCallum
International Conference on Artificial Intelligence and Statistics (2021)
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
Latent Bandits Revisited
Joey Hong
Branislav Kveton
Manzil Zaheer
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), pp. 13423-13433
Big Bird: Transformers for Longer Sequences
Manzil Zaheer
Guru Prashanth Guruganesh
Joshua Ainslie
Anirudh Ravula
Qifan Wang
Li Yang
NeurIPS (2020)
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
Recurrent Recommender Networks
Chao-Yuan Wu
Alex Beutel
Alexander J. Smola
How Jing
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining (2017), pp. 495-503
