I am currently a Senior Research Scientist at NVIDIA Research and a Research Assistant at Imperial College London. Prior to that, I was a Research Scientist at the Samsung AI Center in Cambridge, following the completion of my PhD in the Department of Computing at Imperial College London, within the iBug group. I worked a lot on automatic facial affect estimation, a field which bridges the gap between Computer Vision and Machine Learning. After contributing to facial landmark detection using Active Appearance Models and to emotion detection from faces, I currently focus on Machine Learning using tensor methods.
I created TensorLy, a high-level API for tensor methods and deep tensorized neural networks in Python, designed to make tensor learning simple and accessible. TensorLy allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, MXNet, PyTorch, TensorFlow, CuPy or JAX, and run methods at scale on CPU or GPU. It is open-source under BSD licensed, making it suitable for both academic and industrial applications.
Panagakis, Yannis, J. Kossaifi, Chrysos, Grigorios G, Oldfield, James, Patti, Taylor, Nicolaou, Mihalis A, Anandkumar, Anima, Zafeiriou, Stefanos, Tensor methods in deep learning, in Signal Processing and Machine Learning Theory, 2024
Patti, Taylor L, J. Kossaifi, Anandkumar, Anima, Yelin, Susanne F, Quantum Goemans-Williamson Algorithm with the Hadamard Test and Approximate Amplitude Constraints, in Quantum, 2023
White, Colin, Tu, Renbo, J. Kossaifi, Pekhimenko, Gennady, Azizzadenesheli, Kamyar, Anandkumar, Anima, Speeding up Fourier Neural Operators via Mixed Precision, in arXiv preprint arXiv:2307.15034, 2023
Chaudhary, Smit, Huembeli, Patrick, MacCormack, Ian, Patti, Taylor L, J. Kossaifi and Galda, Alexey, Towards a scalable discrete quantum generative adversarial neural network, in Quantum Science and Technology, 2023
Patti, Taylor L, J. Kossaifi, Anandkumar, Anima, Yelin, Susanne F, Variational Quantum Optimization with Multi-Basis Encodings, in Physical Review Research, 2022
Patti, Taylor L, J. Kossaifi, Anandkumar, Anima, Yelin, Susanne F, Quantum Semidefinite Programming with the Hadamard Test and Approximate Amplitude Constraints, in arXiv preprint arXiv:2206.14999, 2022
Grigorios G Chrysos, Markos Georgopoulos, Jiankang Deng, J. Kossaifi, Yannis Panagakis, Anima Anandkumar, Augmenting Deep Classifiers with Polynomial Neural Networks, in European Conference in Computer Vision (ECCV), 2022
Gu, Jiaqi, Keller, Ben, J. Kossaifi, Anandkumar, Anima, Khailany, Brucek, Pan, David Z, Heat: Hardware-efficient automatic tensor decomposition for transformer compression, in arXiv preprint arXiv:2211.16749, 2022
J. Kossaifi, Kovachki, Nikola Borislavov, Azizzadenesheli, Kamyar, Anandkumar, Anima, Multi-Grid Tensorized Fourier Neural Operator for High Resolution PDEs, , 2022
J. Kossaifi, Walecki, Robert, Panagakis, Yannis, Shen, Jie, Schmitt, Maximilian, Ringeval, Fabien, Han, Jing, Pandit, Vedhas, Toisoul, Antoine, Schuller, Bjoern W, others, SEWA DB: A rich database for audio-visual emotion and sentiment research in the wild, in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Kolbeinsson, Arinbjorn, J. Kossaifi, Panagakis, Yannis, Bulat, Adrian, Anandkumar, Anima, Tzoulaki, Ioanna, Matthews, Paul, Tensor Dropout for Robust Learning, in IEEE Journal of Selected Topics in Signal Processing, 2021
Chrysos, Grigorios G, J. Kossaifi, Yu, Zhiding, Anandkumar, Anima, Unsupervised Controllable Generation with Self-Training, in International Joint Conference on Neural Networks (IJCNN), 2021
Toisoul, Antoine, J. Kossaifi, Bulat, Adrian, Tzimiropoulos, Georgios and Pantic, Maja, Estimation of continuous valence and arousal levels from faces in naturalistic conditions, in Nature Machine Intelligence, 2021
Panagakis, Yannis, J. Kossaifi, Chrysos, Grigorios G, Oldfield, James, Nicolaou, Mihalis A, Anandkumar, Anima, Zafeiriou, Stefanos, Tensor methods in computer vision and deep learning, in Proceedings of the IEEE, 2021
Mahajan, Anuj, Samvelyan, Mikayel, Mao, Lei, Makoviychuk, Viktor, Garg, Animesh, J. Kossaifi, Whiteson, Shimon, Zhu, Yuke, Anandkumar, Animashree, Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning, in International Conference on Machine Learning (ICML), 2021
Wang, Haotao, Xiao, Chaowei, J. Kossaifi, Yu, Zhiding, Anandkumar, Anima, Wang, Zhangyang, AugMax: Adversarial Composition of Random Augmentations for Robust Training, in Advances in Neural Information Processing Systems (NeurIPS), 2021
Bulat, Adrian, J. Kossaifi, Bhattacharya, Sourav, Panagakis, Yannis, Hospedales, Timothy, Tzimiropoulos, Georgios, Lane, Nicholas D and Pantic, Maja, Defensive Tensorization, in BMVC, 2021
Mahajan, Anuj, Samvelyan, Mikayel, Mao, Lei, Makoviychuk, Viktor, Garg, Animesh, J. Kossaifi, Whiteson, Shimon, Zhu, Yuke, Anandkumar, Animashree, Reinforcement Learning in Factored Action Spaces using Tensor Decompositions, in arXiv preprint arXiv:2110.14538, 2021
Patti, Taylor L, J. Kossaifi, Yelin, Susanne F, Anandkumar, Anima, Tensorly-quantum: Quantum machine learning with tensor methods, in arXiv preprint arXiv:2112.10239, 2021
Chrysos, Grigorios G, J. Kossaifi and Zafeiriou, Stefanos, RoCGAN: Robust Conditional GAN, in International Journal of Computer Vision (IJCV), 2020
J. Kossaifi,
Adrian Bulat,
Yannis Panagakis and
Maja Pantic, Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
Bulat, Adrian, J. Kossaifi, Tzimiropoulos, Georgios and Pantic, Maja, Incremental multi-domain learning with network latent tensor factorization, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020
Bulat, Adrian, J. Kossaifi, Tzimiropoulos, Georgios and Pantic, Maja, Toward fast and accurate human pose estimation via soft-gated skip connections, in 15th IEEE International Conference on Automatic Face \& Gesture Recognition (FG), 2020
Janzamin, Majid, Ge, Rong, J. Kossaifi, Anandkumar, Anima, others, Spectral learning on matrices and tensors, in Foundations and Trends{\textregistered} in Machine Learning, 2019
Mitenkova, Anna, J. Kossaifi, Panagakis, Yannis and Pantic, Maja, Valence and Arousal Estimation In-The-Wild with Tensor Methods, in 2019 14th IEEE International Conference on Automatic Face \& Gesture Recognition (FG 2019), 2019
Bulat, Adrian, J. Kossaifi, Tzimiropoulos, Georgios and Pantic, Maja, Matrix and tensor decompositions for training binary neural networks, in arXiv preprint arXiv:1904.07852, 2019
Bulat, Adrian, Tzimiropoulos, Georgios, J. Kossaifi and Pantic, Maja, Improved training of binary networks for human pose estimation and image recognition, in arXiv preprint arXiv:1904.05868, 2019
J. Kossaifi, Walecki, Robert, Panagakis, Yannis, Shen, Jie, Schmitt, Maximilian, Ringeval, Fabien, Han, Jing, Pandit, Vedhas, Schuller, Bjorn, Star, Kam, others, SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild, in TPAMI, 2019
J. Kossaifi, Bulat, Adrian, Tzimiropoulos, Georgios and Pantic, Maja, T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Tran, Linh, J. Kossaifi, Panagakis, Yannis and Pantic, Maja, Disentangling Geometry and Appearance with Regularised Geometry-Aware Generative Adversarial Networks, in International Journal of Computer Vision (IJCV), 2019
G. G. Chrysos, J. Kossaifi and S. Zafeiriou, Robust Conditional Generative Adversarial Networks, in ICLR, 2019
J. Kossaifi, Y. Panagakis, A. Anandkumar, M. Pantic, TensorLy: Tensor Learning in Python, in JMLR, 2019
J. Kossaifi, L, Tran, Y. Panagakis and M. Pantic, GAGAN: Geometry-Aware Generative Adverserial Networks, in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
G. Dhillon, K. Azizzadenesheli, Z.C.Lipton, J. Bernstein, J. Kossaifi, A.Khanna, A.Anandkumar, Stochastic activation pruning for robust adversarial defense, in ICLR, 2018
J. Kossaifi, G. Tzimiropoulos, S. Todorovic and M. Pantic, AFEW-VA database for valence and arousal estimation in-the-wild, in Image and Vision Computing, 2017
J. Kossaifi, Z. Lipton, A. Khanna, T. Furlanello, A. Anandkumar, Tensor Regression Networks, in CoRR, 2017
J. Kossaifi, A. Khanna, Z. Lipton, T. Furlanello, A. Anandkumar, Tensor Contraction Layers for Parsimonious Deep Nets, in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), July 2017
J. Kossaifi, G. Tzimiropoulos and M. Pantic, Fast and exact Newton and Bidirectional fitting of Active Appearance Models, in IEEE Transactions on Image Processing (TIP), accepted for publication, 2016
J. Shen, S. Zafeiriou, G. Chrysos, J. Kossaifi, G. Tzimiropoulos and M. Pantic, The First Facial Landmark Tracking in-the-Wild Challenge: Benchmark and Results, in Proceedings of IEEE International Conference on Computer Vision, 300 Videos in the Wild (300-VW): Facial Landmark Tracking in-the-Wild Challenge and Workshop (ICCVW'15), December 2015
J. Kossaifi, G. Tzimiropoulos and M. Pantic, Fast and exact Bi-directional Fitting of Active Appearance Models, in ICIP, September 2015
A. Abraham, F. Pedregosa, M. Eickenberg, P. Gervais, A. Mueller, J. Kossaifi, A. Gramfort, B. Thirion and G. Varoquaux, Machine Learning for Neuroimaging with Scikit-Learn, in Frontiers in Neuroinformatics, 2014
J. Kossaifi, G. Tzimiropoulos and M. Pantic, Fast Newton Active Appearance Models, in ICIP, October 2014
