- Post-Doctoral Fellow (Dec 2016-March 2020), Inference, Information and Decision Systems Group, Yale Institute for Network Science.
- I was fortunate to work with a group of prominent researchers (including my adviser Amin Karbasi) on a broad set of machine learning problems such as scalable submodular optimization, applications of deep learning in computational biology and fairness.
- Ph.D., Computer, Communication and Information Sciences (2011-2016), Thesis title: “Network Alignment: Theory, Algorithms, and Applications”, Laboratory for Computer Communications and Applications (LCA4), EPFL, Lausanne, Switzerland.
- Ph.D. candidate, Computer, Communication and Information Sciences (2010-2011), Unaffiliated Ph.D. student, EPFL, Lausanne, Switzerland, Laboratory for Computer Communications and Applications (LCA1).
- MS.c., Electrical Engineering and Communication Systems (2008-2010), Sharif University of Technology, Tehran, Iran.
- BS.c., Electrical Engineering and Communication Systems (2004-2008), Sharif University of Technology, Tehran, Iran.
- R. Haba, E. Kazemi, M. Feldman, and A. Karbasi. Streaming Submodular Maximization under a k-Set System Constraint. ICML, 2020.
- E. Kazemi, S. Minaee, M. Feldman, and A. Karbasi. Regularized Submodular Maximization at Scale. arXiv preprint arXiv:2002.03503, 2020.
- A. Badanidiyuru, A. Karbasi, E. Kazemi, and J. Vondrak. Submodular Maximization Through Barrier Functions. arXiv preprint arXiv:2002.03523, 2020.
- M. Mitrovic, E. Kazemi, M. Feldman, A. Krause, and A. Karbasi. Adaptive Sequence Submodularity. NeurIPS, 2019. [code] [poster]
- E. Kazemi, M. Mitrovic, M. Zadimoghaddam, S. Lattanzi, and A. Karbasi. Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity. ICML, 2019. [code] [poster]
- S. Ghili, E. Kazemi, and A. Karbasi. Eliminating Latent Discrimination: Train Then Mask. AAAI, 2019 (oral presentation). [slides] [poster]
- E. Kazemi and M. Grossglauser. MPGM: Scalable and Accurate Multiple Network Alignment. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019. [appendix] [publisher link]
- P. Khosravi, E. Kazemi, Q. Zhan, J. E. Malmsten, M. Toschi, P. Zisimopoulos, A. Sigaras, S. Lavery, L. A. D. Cooper, C. Hickman, M. Meseguer, Z. Rosenwaks, O. Elemento, N. Zaninovic and I. Hajirasouliha. Deep Learning Enables Robust Assessment and Selection of Human Blastocysts after in Vitro Fertilization. npj Digital Medicine, Nature Publishing Group, 2019. [code]
- P. Khosravi, M. Lysandrou, M. Eljalby, M. Brendel, Q. Li, E. Kazemi, J. Barnes, P. Zisimopoulos, A. Sigaras, C. Ricketts, et al. Biopsy-free prediction of prostate cancer aggressiveness using deep learning and radiology imaging. medRxiv, 2019.
- M. Feldman, A. Karbasi, and E. Kazemi. Do Less, Get More: Streaming Submodular Maximization with Subsampling. NeurIPS, 2018 (spotlight presentation). [slides] [poster] [video]
- P. Khosravi, E. Kazemi, Q. Zhan, M. Toschi, J. E Malmsten, C. Hickman, M. Meseguer, Z. Rosenwaks, O. Elemento, N. Zaninovic, and I. Hajirasouliha. Robust Automated Assessment of Human Blastocyst Quality using Deep Learning. bioRxiv, 2018.
- E. Kazemi, M. Zadimoghaddam, and A. Karbasi. Scalable Deletion-Robust Submodular Maximization: Data Summarization with Privacy and Fairness Constraints. ICML, 2018. [slides] [poster]
- M. Mitrovic, E. Kazemi, M. Zadimoghaddam, and A. Karbasi. Data Summarization at Scale: A Two-Stage Submodular Approach. ICML, 2018. [poster]
- E. Kazemi, L. Chen, S. Dasgupta, and A. Karbasi. Comparison Based Learning from Weak Oracles. AISTATS, 2018. [slides] [poster]
- P. Khosravi, E. Kazemi, M. Imielinski, O. Elemento, and I. Hajirasouliha. Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images. EBioMedicine, 2017. [poster] [code]
- E. Kazemi, H. Hassani, M. Grossglauser, and H. Pezeshghi Modarres. PROPER: Global Protein Interaction Network Alignment through Percolation Matching. BMC Bioinformatics, 2016. Website: http://proper.epfl.ch/
- E.Kazemi and M. Grossglauser. On the Structure and Efficient Computation of IsoRank Node Similarities. arXiv preprint arXiv:1602.00668, 2016.
- E. Kazemi, H. Hassani, and M. Grossglauser. Growing a Graph Matching from a Handful of Seeds. VLDB, 2015. [slides] [poster]
- E. Kazemi, L. Yartseva, and M. Grossglauser. When Can Two Unlabeled Networks Be Aligned under Partial Overlap? Annual Allerton Conference on Communication, Control, and Computing, 2015. [slides]
- R. Shokri, G. Theodorakopoulos, P. Papadimitratos, E. Kazemi, and J. P. Hubaux. Hiding in the mobile crowd: Location privacy through collaboration. IEEE Transactions on Dependable and Secure Computing, 2014.
- M. Kafsi, E. Kazemi, L. Maystre, L. Yartseva, M. Grossglauser, and P. Thiran. Mitigating Epidemics through Mobile Micro-Measures. Third International Conference on the Analysis of Mobile Phone Datasets, 2013. [poster]
- V. Etter, M. Kafsi, E. Kazemi, M. Grossglauser, and P. Thiran. Where to Go from Here? Mobility Prediction from Instantaneous Information. Pervasive and Mobile Computing, 2013.
- V. Etter, M. Kafsi, and E. Kazemi. Been There, Done That: What Your Mobility Traces Reveal about Your Behavior. Mobile Data Challenge by Nokia Workshop, in conjunction with Int. Conf. on Pervasive Computing, 2012. [poster]
My RESEARCH IN THE PRess
My RESEARCH IN THE PRess