I am a PhD candidate in my final year under the supervision of Bernhard Schölkopf in the Empirical Inference department. Additionally, I am affiliated with Hendrik Lensch at the University of Tübingen and I am an ETH Zürich Center for Learning Systems associated PhD fellow. Previously, I had been working with Ulrike von Luxburg in the theory of machine learning group at the University of Hamburg.
My research interests include probabilistic and approximate algorithms, game AI, graph theory, computational photography, computer vision and machine learning along with its countless applications. During my PhD, I am focusing on creating efficient intelligent algorithms for use in image and video processing and perceptual metrics for evaluation. More generally, I am working on deep generative models.
Our work with convolutional generative adversarial neural networks has reached state-of-the-art results for the task of single image super-resolution in both quantitative and qualitative benchmarks. We have further reached state-of-the-art results in video super-resolution. A further line of work entails evaluating generative models such as GANs and improving their performance.
Please see the Projects tab for more information.
Machine Learning Computational Imaging Image Processing Neural Networks Deep Learning Generative Modeling Perceptual Evaluation Metrics
Ghosh*, P., Sajjadi*, M. S. M., Vergari, A., Black, M. J., Schölkopf, B.
8th International Conference on Learning Representations (ICLR) , April 2020, *equal contribution (conference)
Sajjadi, M. S. M., Bachem, O., Lucic, M., Bousquet, O., Gelly, S.
Advances in Neural Information Processing Systems 31, pages: 5234-5243, (Editors: S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett), Curran Associates, Inc., 32nd Annual Conference on Neural Information Processing Systems, December 2018 (conference)
Kim, T. H., Sajjadi, M. S. M., Hirsch, M., Schölkopf, B.
15th European Conference on Computer Vision (ECCV), Part III, 11207, pages: 111-127, Lecture Notes in Computer Science, (Editors: Vittorio Ferrari, Martial Hebert,Cristian Sminchisescu and Yair Weiss), Springer, September 2018 (conference)
Sajjadi, M. S. M., Bachem, O., Lucic, M., Bousquet, O., Gelly, S.
Workshop on Theoretical Foundations and Applications of Deep Generative Models (TADGM) at the 35th International Conference on Machine Learning (ICML), July 2018 (conference)
Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.
Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4448-4456, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)
Sajjadi, M. S. M., Vemulapalli, R., Brown, M.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018 (conference)
Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.
Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)
Pérez-Pellitero, E., Sajjadi, M. S. M., Hirsch, M., Schölkopf, B.
Workshop and Challenge on Perceptual Image Restoration and Manipulation (PIRM) at the 15th European Conference on Computer Vision (ECCV), 2018 (poster)
Sajjadi, M. S. M., Köhler, R., Schölkopf, B., Hirsch, M.
Pattern Recognition - 38th German Conference (GCPR), 9796, pages: 426-438, Lecture Notes in Computer Science, (Editors: Rosenhahn, B. and Andres, B.), Springer International Publishing, September 2016 (conference)
Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.
Proceedings of the 3rd ACM conference on Learning @ Scale, pages: 369-378, (Editors: Haywood, J. and Aleven, V. and Kay, J. and Roll, I.), ACM, L@S, April 2016, (An earlier version of this paper had been presented at the ICML 2015 workshop for Machine Learning for Education.) (conference)
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