4 PhD positions in Machine Learning and Computer Vision in QMUL

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[Αιμιλία η φτερωτή χελώνα]

Four (4) PhD positions in the area of Computer Vision and Machine Learning for the analysis of actions,
activity and behavior with applications in the field of Augmented Reality, Affective Computing and/or
Mental Health are available in the group of Multimedia and Vision in the School of Electronic Engineering
and Computer Science in Queen Mary University of London.

At a methodological level, the work will focus on the development of novel Machine Learning methods for
learning from multimodal data, on learning with efficient architectures and on learning from few or no annotations.

For more information, please visit: https://sites.google.com/view/ioannispatras/phd-positions

Contact Prof. Patras, i.patras@qmul.ac.uk and/or Dr Tzimiropoulos g.tzimiropoulos@qmul.ac.uk with an email with subject that includes the string: [PhD-2022]

Team
The student will be based in the Multimedia and Vision group in the school of EECS. Queen Mary University of London
is a research intensive university and a member of the Russel group. The school of EECS is 11th in the UK for quality
of computer science research (REF 2014) and 6th in the UK for quality of electronic engineering research (REF 2014).
The School is a dynamic community of approximately 350 PhD students and 80 research assistants.The school has
one of the largest teams in Computer Vision in the UK and a very strong team in Computational Linguistics.
For more information please see:

Ioannis Patras: Home page, Google Scholar
Georgios Tzimiropoulos: Homepage, Google Scholar
Multimedia and Vision Research group: Homepage
Cognitive Sciences Research group: CogSci homepage

Computing Infrastructure: The team has a Deep Learning computing infrastructure with over 256 CPU cores, 6 large GPU servers with 175,248 CUDA (GPU) cores and 36TB of storage.

References
[1] M Bishay, G Zoumpourlis, I Patras, “TARN: Temporal Attentive Relation Network for Few-Shotand Zero-Shot Action Recognition”, British Machine Vision Conference, Sept. 2019.
[2] J Yang, B Martinez, A Bulat, G Tzimiropoulos, “Knowledge Distillation via Softmax Regression Representation Learnings”, Int’l Conference on Representation Learning, 2021
[3] M Bishay, P Palasek, S Priebe, I Patras, “Schinet: Automatic estimation of symptoms of schizophrenia from facial behaviour analysis” IEEE Transactions on Affective Computing, 2019
[4] Giorgos Kordopatis-Zilos, Christos Tzelepis, Symeon Papadopoulos, Ioannis Kompatsiaris, Ioannis Patras, “DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval”, ArXiv, 2021

ΥΓ: ισως παρατηρησετε ενα overlap με διπλανο thread του board. αναφερεται εν μερει στις ιδιες θεσεις, αλλα και σε αλλες

[Katarameno]

Εγώ, καθότι πολύ παρατηρητικός αν θέλω, παρατήρησα και ένα ...loop