Umar Syed
Research Scientist
111 8th Avenue
New York, NY 10011
I am a research scientist at Google. I received a Ph.D. in Computer Science from Princeton University, where I was advised by Rob Schapire. I spent two years as a postdoctoral researcher at the University of Pennsylvania, hosted by Ben Taskar and Michael Kearns.
Publications
Berke, A., Ghazi, B., Bacis, E., Kamath, P., Kumar, R., Lassonde, R., Manurangsi, P., Syed, U. (2025) How unique is whose web browser? The role of demographics in browser fingerprinting among US users. Proceedings on Privacy Enhancing Technologies (PoPETs 2025).
Amin, K., Bie, A., Kong, W., Kurakin, A., Ponomareva, N., Syed, U., Terzis, A., Vassilvitskii, S. (2024)* Private prediction for large-scale synthetic text generation. Findings of the Association for Computational Linguistics (EMNLP 2024).
Kong, W., Medina, A. M., Ribero, M., Syed, U. (2024)* DP-Auditorium: A large-scale library for auditing differential privacy. Proceedings of the IEEE Symposium on Security and Privacy (S&P 2024).
Bacis, E., Bilogrevic, I., Busa-Fekete, R., Herath, A., Sartori, A., Syed, U. (2024)* Assessing web fingerprinting risk. Companion Proceedings of the ACM Web Conference (WWW 2024).
Abernethy, J., Schapire, R. E., Syed, U. (2024)* Lexicographic optimization: Algorithms and stability. Proceedings of the Twenty-Seventh International Conference on Artificial Intelligence and Statistics (AISTATS 2024).
Busa-Fekete, R., Medina, A. M., Syed, U., Vassilvitskii, S. (2023)* Label differential privacy and private training data release. Proceedings of the Fortieth International Conference on Machine Learning (ICML 2023).
Bravo-Hermsdorff, G., Busa-Fekete, R., Ghavamzadeh, M., Medina, A. M., Syed, U. (2022)* Private and communication-efficient algorithms for entropy estimation. Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
Esfandiari, H., Mirrokni, V., Syed, U., Vassilvitskii, S. (2021)* Label differential privacy via clustering. Proceedings of the Twenty-Fifth International Conference on Artificial Intelligence and Statistics (AISTATS 2022).
Epasto, A., Medina, A. M., Avery, S., Bai, Y., Busa-Fekete, R., Carey, C., Gao, Y., Guthrie, D., Ghosh, S., Ioannidis, J., Jiao, J., Lacki, J., Lee, J., Mauser, A., Milch, B., Mirrokni, V., Ravichandran, D., Shi, W., Spero, M., Sun, Y., Syed, U., Vassilvtiskii, S., Wang, S. (2021) Clustering for private interest-based advertising. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD 2021).
Medina, A. M., Syed, U., Vassilvitskii, S., Vitercik, E. (2021)* Private optimization without constraint violations. Proceedings of the Twenty-Fourth International Conference on Artificial Intelligence and Statistics (AISTATS 2021).
Syed, U., Vassilvitskii, S. (2017)* SQML: Large-scale in-database machine learning with pure SQL. Proceedings of the 2017 Symposium on Cloud Computing (SoCC 2017).
Balkanski, E., Syed, U., Vassilvitskii, S. (2017)* Statistical cost sharing. Advances in Neural Information Processing Systems 30 (NeurIPS 2017).
Nazerzadeh, H., Paes Leme, R., Rostamizadeh, A., Syed, U. (2016)* Where to sell: Simulating auctions from learning algorithms. Proceedings of the Seventeenth ACM Conference on Economics and Computation (EC 2016).
Heidari, H., Mahdian, M., Syed, U., Vassilvitskii, S., Yazdanbod, S. (2016)* Pricing a low-regret seller. Proceedings of the Thirty-Third International Conference on Machine Learning (ICML 2016).
Choromanski, K., Rostamizadeh, A., Syed, U. (2015)* An optimal online algorithm for retrieving heavily perturbed statistical databases in the low-dimensional querying model. Proceedings of the Twenty-Fourth ACM International Conference on Information and Knowledge Management (CIKM 2015).
DeSalvo, G., Mohri, M., Syed, U. (2015)* Learning with deep cascades. Proceedings of the Twenty-Sixth International Conference on Algorithmic Learning Theory (ALT 2015).
Cortes, C., Kuznetsov, V., Mohri, M., Syed, U. (2015)* Structural maxent models. Proceedings of the Thirty-Second International Conference on Machine Learning (ICML 2015). Supplement.
Kuznetsov, V., Mohri, M., Syed, U. (2014)* Multi-class deep boosting. Advances in Neural Information Processing Systems 27 (NeurIPS 2014). Supplement.
Amin, K., Rostamizadeh, A., Syed, U. (2014)* Repeated contextual auctions with strategic buyers. Advances in Neural Information Processing Systems 27 (NeurIPS 2014). Supplement.
Cortes, C., Mohri, M., Syed, U. (2014)* Deep boosting. Proceedings of the Thirty-First International Conference on Machine Learning (ICML 2014). Supplement.
Asuncion, A., de Haan, J., Mohri, M., Patel, K., Rostamizadeh, A., Syed, U., Wong, L. (2014)* Corporate learning at scale: Lessons from a large online course at Google. Learning at Scale 2014.
Amin, K., Rostamizadeh, A., Syed, U. (2013)* Learning prices for repeated auctions with strategic buyers. Advances in Neural Information Processing Systems 26 (NeurIPS 2013). Supplement.
Amin, K., Kearns, M., Syed, U. (2011)* Graphical models for bandit problems. Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Seventh Conference (UAI 2011).
Amin, K., Kearns, M., Syed, U. (2011)* Bandits, query learning, and the haystack dimension. Proceedings of the Twenty-Fourth Annual Conference on Learning Theory (COLT 2011).
Fabrikant, A., Syed, U., Rexford, J. (2011) There's something about MRAI: Timing diversity can exponentially worsen BGP convergence. Proceedings of the Thirtieth IEEE International Conference on Computer Communications (INFOCOM 2011).
Syed, U., Taskar, B. (2010) Semi-supervised learning with adversarially missing label information. Advances in Neural Information Processing Systems 23 (NeurIPS 2010). Supplement.
Syed, U., Schapire, R. E. (2010) A reduction from apprenticeship learning to classification. Advances in Neural Information Processing Systems 23 (NeurIPS 2010).
Brautbar, M., Kearns, M., Syed, U. (2010)* Private and third-party randomization in risk-sensitive equilibrium concepts. Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI 2010).
Syed, U. (2010) Reinforcement learning without rewards. Ph.D. dissertation. Department of Computer Science, Princeton University.
Syed, U., Slivkins, A., Mishra, N. (2009) Adapting to the shifting intent of search queries. Advances in Neural Information Processing Systems 22 (NeurIPS 2009). Full version
Syed, U., Bowling, M., Schapire, R. E. (2008) Apprenticeship learning using linear programming. Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML 2008).
Syed, U., Williams, J. D. (2008) Using automatically transcribed dialogs to learn user models in a spoken dialog system. Proceedings of the Forty-Sixth Annual Meeting of the Association for Computational Linguistics (ACL 2008).
Syed, U., Yona, G. (2008) Enzyme function prediction with interpretable models. Methods in Molecular Biology: Computational Systems Biology, edited by J. McDermott, K. Montgomery, R. Bumgarner and R. Samudrala. Humana Press. [Book chapter]
Syed, U., Schapire, R. E. (2007) A game-theoretic approach to apprenticeship learning. Advances in Neural Information Processing Systems 20 (NeurIPS 2007). Supplement and videos.
Syed, U., Schapire, R. E. (2007) Imitation learning with a value-based prior. Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Third Conference (UAI 2007).
Syed, U., Yona, G. (2003) Using a mixture of probabilistic decisions trees for direct prediction of protein function. Proceedings of the Seventh Annual International Conference on Research in Computational Biology (RECOMB 2003).
* Denotes alphabetical author order.