DIMITRIOS KOLLIAS

Lecturer (Assistant Professor) in Artificial Intelligence

Queen Mary University of London

United Kingdom

Research Interests

Explore related searches

Professors in United Kingdom Professors in Medical Imaging Medical Imaging professors in United Kingdom

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dimitrios Kollias is a Lecturer (Assistant Professor) in Artificial Intelligence at Queen Mary University of London. His research interests encompass affect analysis, deep learning applications in medical imaging, and the use of machine learning in healthcare diagnostics and predictive modeling. Recent publications include works on fairness in affect analysis, deep-learning pipelines for advanced air mobility, and the diagnosis of primary immune thrombocytopenia. He is based in the United Kingdom.

Articles (12)

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2021

Year:

2020

Year:

2020

Year:

2020

Collaborators (3)

Drew Provan

UNITED KINGDOM

View details

Stefanos Kollias

Professor of MAchine Learning

University of Lincoln

UNITED KINGDOM

View details

James Wingate

Lecturer in Computer Science

University of Lincoln

UNITED KINGDOM

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

DIMITRIOS KOLLIAS

Research Interests

Explore related searches

Contact this professor

About

Articles (12)

Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency

Common Corruptions for Evaluating and Enhancing Robustness in Air-to-Air Visual Object Detection

Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A Feasibility Study

NEFELI: A deep-learning detection and tracking pipeline for enhancing autonomy in advanced air mobility

COVID-19 Detection from Computed Tomography Images Using Slice Processing Techniques and a Modified Xception Classifier

A deep neural architecture for harmonizing 3-D input data analysis and decision making in medical imaging

CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images

BTDNet: A Multi-Modal Approach for Brain Tumor Radiogenomic Classification

Machine Learning for Predictive Modelling of Ambulance Calls

Affect recognition & generation in-the-wild

Deep Neural Network Augmentation: Generating Faces for Affect Analysis

Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset

Collaborators (3)

Drew Provan

Stefanos Kollias

James Wingate

Make your next move.

DIMITRIOS KOLLIAS

Research Interests

Explore related searches

Contact this professor

About

Articles (12)

Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency

Common Corruptions for Evaluating and Enhancing Robustness in Air-to-Air Visual Object Detection

Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A Feasibility Study

NEFELI: A deep-learning detection and tracking pipeline for enhancing autonomy in advanced air mobility

COVID-19 Detection from Computed Tomography Images Using Slice Processing Techniques and a Modified Xception Classifier

A deep neural architecture for harmonizing 3-D input data analysis and decision making in medical imaging

CoviDetector: A transfer learning-based semi supervised approach to detect Covid-19 using CXR images

BTDNet: A Multi-Modal Approach for Brain Tumor Radiogenomic Classification

Machine Learning for Predictive Modelling of Ambulance Calls

Affect recognition &amp; generation in-the-wild

Deep Neural Network Augmentation: Generating Faces for Affect Analysis

Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Dataset

Collaborators (3)

Drew Provan

Stefanos Kollias

James Wingate

Make your next move.

Affect recognition & generation in-the-wild