Program committee

• Area Chair at AAAI Conference on Artificial Intelligence (AAAI 2022)
• Program Committee at 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016)
• Program Committee at 27th International Conference on Algorithmic Learning Theory (ALT 2016)
• Senior Program Committee at 29th AAAI Conference on Artificial Intelligence (AAAI 2015)

Conference reviewer

• Neural Information Processing Systems (NeurIPS) [2013-present]
• Conference on Learning Theory (COLT 2013, COLT 2014, COLT 2015, COLT 2016, COLT 2017, COLT 2018)
• International Conference on Machine Learning (ICML) [2012-present]
• International Conference on Artificial Intelligence and Statistics (AISTAT) [2013-2022)
• International Conference on Learning Representations (ICLR 2017)
• Association for the Advancement of Artificial Intelligence (AAAI 2014, AAAI 2016, AAAI 2017)

Journal reviewer

Journal of Machine Learning Research (JMLR- MIT Press), Signal Processing Letters (IEEE), Information Science (Elsevier), Applied Mathematics and Computation (Elsevier), Journal of the Franklin Institute (Elsevier), Transactions on Evolutionary Computation (IEEE), Transactions on Systems, Man, and Cybernetics (IEEE), Journal of Applied Mathematics and Computation (Springer), Computers and Mathematics with Applications (Elsevier), Swarm and Evolutionary Computation (Elsevier), Neurocomputing (Elsevier), Transactions on Knowledge Discovery from Data (ACM)

Honors and awards

• NSF CAREER Award, IIS: Robust Intelligence, 2023
• Mark Fulk Best Student Paper Award, Conference on Learning Theory (COLT), 2012
• Top Cited Paper Award, Journal of Applied Mathematics and Computation, Elsevier, 2010
• Recognized as National Elite Student by Iranian National Foundation of Elites, 2007
• Ranked 18th in “National Entrance Examination for M.Sc. Program” among more than 10,000 participants
• Ranked 126th in “National Entrance Examination for B.Sc. Program” among more than 400,000 high school students in mathematics and physics
• Semifinalist of “National Mathematics Olympiad”

Talks/Posters

• 2017
  • Randomized algorithms for large-scale and high dimensional learning: sketching, random projections, and stochastic optimization, Ohio State University (OSU), 2017
• 2016
  • Stochastic Optimization for High-Dimensional Large-Scale Learning, Wisconsin Institute for Discovery (WID), University of Wisconsin-Madison, 2016
• 2015
  • Randomized Algorithms for Large-Scale Learning: from Optimization to Recovery, Center for Statistics and Machine Learning, Princeton University, 2015
  • Efficient Optimization for Large-scale Stochastic and Adversarial Losses, IDS at UIC Business, 2015
• 2014
  • Learning and Optimization with Smooth Losses, NEC Labs Princeton, 2014
  • Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization, Toyota Technological Institute at Chicago (TTIC)
• 2013
  • Passive Learning with Target Risk, Conference on Learning Theory (COLT)
  • Mixed Optimization for Smooth Functions, Advances in Neural Information Processing Systems (NeurIPS)
  • Stochastic Convex Optimization with Multiple Objectives, Advances in Neural Information Processing Systems (NeurIPS)
• 2012
  • Theoretical Investigation on Distributed Learning, NEC Labs America
  • Online Optimization with Gradual Variation, NEC Labs America
  • Online Decision Making under Stochastic Constraints, DISCML, NeurIPS Conference
  • Online Stochastic Optimization with Multiple Objectives, OPTML, NeurIPS Conference