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Weekly Research Seminars

This page contains a list with next and coming talks on our weekly seminars in Computer Vision (CV) and Natural Language Processing (NLP).

If you want to be included in the Computer Vision (CV) mailing list, please contact: <alba.garcia(at)> or <e.yagis(at)>

If you would like to be included in the Natural Language and Information Processing (NLIP) mailing list, please contact Jon Chamberlain <jchamb (at)

For past seminars see here.

26 May 2021 – NLP – Zoom meeting

Title: Discussion of paper: “KERMIT: Complementing Transformer Architectures with Encoders of Explicit Syntactic Interpretations” discussion led by Kakia Chatsiou

Abstract: This week we will be discussing the above paper (download) from the last year’s EMNLP 2020. Paper abstract: “Syntactic parsers have dominated natural language understanding for decades. Yet, their syntactic interpretations are losing centrality in downstream tasks due to the success of large-scale textual representation learners. In this paper, we propose KERMIT (Kernel-inspired Encoder with Recursive Mechanism for Interpretable Trees) to embed symbolic syntactic parse trees into artificial neural networks and to visualize how syntax is used in inference. We experimented with KERMIT paired with two state-of-the-art transformer-based universal sentence encoders (BERT and XLNet) and we showed that KERMIT can indeed boost their performance by effectively embedding human-coded universal syntactic representations in neural networks”

2 June 2021 – CV – Zoom meeting

Title: Human Recognition Based on Multi-biometric Systems by Inas Al-taie 

Abstract: Biometrics are fundamental to a wide range of technologies that require credible authentication approach to approve personal identification. This work aims to identify effective features and machine learning methods for human recognition based on multiple biometrics and produce the sufficient combination of single biometric systems suitable in specific applications for identification purposes. For example, banking systems which use multi-biometric authentication for login procedures and the police and criminal evidence applications. An implementation of a person identification system fusing different combinations of biometric modalities; face, ear, eye, hand, and palmprint at score level has I been examined in this work. 

Bio: Dr. Inas Al-taie is a Senior Research Officer in the Brain-Computer Interfacing and Neural Engineering Laboratory in School of Computer Science and Electronic Engineering at University of Essex. Inas had more than 7 years of academic experience and 5 years of working on Remote Sensing Technology Research before she received her PhD in Computer Science in 2020 from Essex University, United Kingdom.  Research interest is cognitive neuroscience of visual object recognition, Computer Vision and Image Processing, Human Biometric Recognition and exploring the use of multiple biometrics (based on behavioural and physiological traits) and how their use could out-perform single biometrics, Machine Learning and Artificial intelligence with focusing on deep and shallow convolutional neural networks (CNN).