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Ioannis Patras

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Professor at School of Electronic Engineering and Computer Science

Queen Mary University of London
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Ioannis Patras is a Professor at the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK. His research areas encompass realistic synthetic data generation, image classification, and effective learning with noisy labels, as reflected in his recent publications. He has contributed to advancements in generative adversarial networks, video indexing, and summarization, as well as mental health analysis through facial behavior.

Recent Grants

Grant: Close

Deep Learning from Crawled Spatio-Temporal Representations of Video (DECSTER)

Open Date: 2018-06-30

Close Date: 2021-06-29

Grant: Close

Recognition and Localisation of Human Actions in Image Sequences

Open Date: 2009-08-31

Close Date: 2012-11-30

Positions (1)

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Ioannis Patras

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Queen Mary University of London

This funded PhD position at Queen Mary University of London offers an exciting opportunity to advance the field of multimodal conversational foundation models. The research is conducted in collaboration with Tavus Inc, a US-based startup specializing in digital humans, and is embedded within the Multimedia and Vision Research group and the Centre for Multimodal AI. The project aims to design and train components of a next-generation multimodal model capable of perceiving and generating both verbal and non-verbal responses in conversational contexts. Unlike traditional text-based dialogue systems, this research focuses on capturing the richness of human-to-human interaction, including facial expressions, voice intonation, gestures, emotions, and social signals. The objectives include multimodal perception of human behaviour using supervised, unsupervised, and reinforcement learning methodologies; post-training techniques for controllable multimodal generation aligned with conversational goals and personality; and the development of diffusion-based methods for high-quality, identity-preserving audio-visual output. The team regularly publishes in top conferences such as CVPR, ICCV, ECCV, NeurIPS, TPAMI, and IJCV, and has access to extensive computational resources, including a server with 64 A100 GPUs and exclusive access to additional servers. The research environment is highly collaborative, with regular interaction between the London-based and international teams of Tavus Inc. Funding includes a full tuition fee (for both Home and International students) and an annual stipend of £22,780 for three years. Applicants should hold or expect to obtain an MSc in Electronic Engineering, Computer Science, or a closely related discipline, with a distinction or first-class degree highly desirable. The application process requires submission of a CV, cover letter, research proposal, two references, and a certificate of English language proficiency (if applicable). Applications are accepted year-round until the position is filled, with a preferred start date of June 1, 2026 (or as soon as possible). For further information, prospective candidates are encouraged to contact Prof Ioannis Patras at [email protected] and review the supervisor’s academic profile at https://ipatras.github.io and https://www.qmul.ac.uk/eecs/people/profiles/patrasioannis.html . Detailed application instructions are available at http://eecs.qmul.ac.uk/phd/how-to-apply/ . This position is ideal for candidates passionate about artificial intelligence, computer vision, and multimodal machine learning, seeking to contribute to cutting-edge research in conversational AI and digital avatars.

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Articles (9)

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Collaborators (5)

Chen Feng

Queen's University Belfast

UNITED KINGDOM
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Georgios Tzimiropoulos

Assistant Professor

University of Nottingham

UNITED KINGDOM
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Ioannis Panagakis

Associate Professor

National and Kapodistrian University of Athens

GREECE
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Christos Tzelepis

City, University of London

UNITED KINGDOM
View details

Alberto Del Bimbo

University of Florence

ITALY
View details
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