I am interested in designing intelligent systems that can learn concepts from visual data. Visual data are images or videos coming from either existing available databases, or directly from the Web.
My PhD thesis was focused on machine learning models for attribute-based object recognition task in computer vision. My current research interests include deep learning methods for human behaviour understanding from facial and bodily cues, visual synthesis with generative adversarial networks, and 3D vision. I am also working in the topics of algorithmic fairness and machine bias mitigation in computer vision and machine learning, and most recently in multi-modal toxicity moderation.
Area Chair: ICLR2023
Reviewer CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, IJCAI, TPAMI, IJCV
2010-2015, PhD in Computer Vision and Machine Learning
I received my PhD from the Institute of Science and Technology Austria (ISTA). With my supervisor, Prof. Christoph Lampert, we worked on the topic of attribute based object recognition, specifically "Learning with attributes for object recognition: parametric and non-parametric views".
2003-2009, MSc in Applied Mathematics
I got my BSc and MSc in Applied Mathematics, summa cum laude, from the Taras Shevchenko National University of Kyiv, Ukraine. With my supervisor, Prof. Bogdan Rublyov, we explored the area of computational geometry.
2021 UCU, Pinata Farm, CTU
Since 2021, we started an inspiring collaborating with the researchers from the Ukrainian Catholic University (UCU) who are also senior engineers at PinataFarm, and Dr Jiri Matas from the Czech Technical University in Prague, on the topics of 3D face modelling.
2020-now, University of Sussex, UK
From September 2020, I am a Lecturer in Artificial Intelligence at the Department of Informatics, University of Sussex, UK. I am delighted to be part of the Predictive Analytics Lab (PAL), and to collaborate with Dr. Novi Quadrianto on the topics of algorithmic fairness in visual and tabular domains, subgroup bias mitigation in active learning, few shot learning and semi-supervised learning settings.
2017-now, Imperial College London, UK
In 2017, I was a recipient of the prestigious Imperial College Research Fellowship at the Department of Computing, Imperial College London. My fellowship project "Deep Understanding of Human Behaviour from Video Data: Action and Emotion Approach" has started a fruitful collaboration with Dr Stefanos Zafeiriou on the topics of facial behaviour analysis and synthesis, and with Dr Dimitrios Kollias on the topics of continual emotions and multi-task learning. Since April 2021, I am also an honorary Lecturer at Imperial College London.
2013, NICTA, Australia
In December 2013 I was visiting Prof. Tiberio Caetano and Machine Learning Group at NICTA Sydney Research Laboratory, Australia.
2013, UT Austin, USA
I spent around three months visiting Prof. Kristen Grauman and Computer Vision Group at the University of Texas at Austin, USA, working on object recognition in images.
2012-2013, Cambridge, UK
I was visiting Machine Learning Group at the University of Cambridge, UK. Together with Dr. Novi Quadrianto and Prof. Zoubin Ghahramani we worked on infinite latent variable models.
Imperial College London, UK
In spring term 2020, I delivered lectures on algorithmic fairness methods in machine learning in the Ethics, Privacy, AI in Society module for postgraduate students at Imperial College London.
Since 2018, I am organising the machine learning tutorials at Imperial College London as part of the Machine Learning initiative.
Lviv Data Science Summer School, Ukraine
In summer 2018, I was invited as a lecturer for two courses: Introduction to Computer Vision, Computer Vision for video understanding and Interpretability of automated decisions at UCU.
University of Sussex, UK
In spring 2016 - 2019, I delivered invited lectures on Deep learning models in the Computer Vision, Machine Learning, and Neural Networks courses for undergraduate and postgraduate students at the University of Sussex.
2013-2014, IST Austria
I was teaching assistant for the Image Processing and Statistical Machine Learning courses at IST Austria.