1 citations · 1 across the 14 of their papers we have counts for
14 papers
Data Safety: Synthetic Data Quality Analysis Using CIFAKE Dataset
Kuniko Paxton, Amila Akagić, Koorosh Aslansefat +2
Recently, the societal implementation of high-performance image classification models has expanded rapidly. While these models require vast amounts of training data to improve perf…
Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering
Louis Donaldson, Connor Walker, Koorosh Aslansefat +1
Trustworthy deployment of Agentic Retrieval-Augmented Generation (RAG) systems requires mechanisms for estimating when multi-stage reasoning pipelines may fail. This paper presents…
Exploring the Impact of Skin Color on Skin Lesion Segmentation
Kuniko Paxton, Medina Kapo, Amila Akagić +3
Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segme…
A Multi-Modal Dataset for Ground Reaction Force Estimation Using Consumer Wearable Sensors
Parvin Ghaffarzadeh, Debarati Chakraborty, Koorosh Aslansefat +2
This Data Descriptor presents a fully open, multi-modal dataset for estimating vertical ground reaction force (vGRF) from consumer-grade Apple Watch sensors with laboratory force p…
Skewness-Guided Pruning of Multimodal Swin Transformers for Federated Skin Lesion Classification on Edge Devices
Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +1
In recent years, high-performance computer vision models have achieved remarkable success in medical imaging, with some skin lesion classification systems even surpassing dermatolo…
Mitigating Individual Skin Tone Bias in Skin Lesion Classification through Distribution-Aware Reweighting
Kuniko Paxton, Zeinab Dehghani, Koorosh Aslansefat +2
Skin color has historically been a focal point of discrimination, yet fairness research in machine learning for medical imaging often relies on coarse subgroup categories, overlook…
Q-SafeML: Safety Assessment of Quantum Machine Learning via Quantum Distance Metrics
Oliver Dunn, Koorosh Aslansefat, Yiannis Papadopoulos
The rise of machine learning in safety-critical systems has paralleled advancements in quantum computing, leading to the emerging field of Quantum Machine Learning (QML). While saf…
RAGuard: A Novel Approach for in-context Safe Retrieval Augmented Generation for LLMs
Connor Walker, Koorosh Aslansefat, Mohammad Naveed Akram +1
Accuracy and safety are paramount in Offshore Wind (OSW) maintenance, yet conventional Large Language Models (LLMs) often fail when confronted with highly specialised or unexpected…
Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning
Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +2
Recent advances in deep learning have significantly improved the accuracy of skin lesion classification models, supporting medical diagnoses and promoting equitable healthcare. How…
Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML
Kuniko Paxton, Koorosh Aslansefat, Amila Akagić +2
Recent advancements in skin lesion classification models have significantly improved accuracy, with some models even surpassing dermatologists' diagnostic performance. However, in…
Evaluating Fairness and Mitigating Bias in Machine Learning: A Novel Technique using Tensor Data and Bayesian Regression
Kuniko Paxton, Koorosh Aslansefat, Dhavalkumar Thakker +1
Fairness is a critical component of Trustworthy AI. In this paper, we focus on Machine Learning (ML) and the performance of model predictions when dealing with skin color. Unlike o…
Incorporating Failure of Machine Learning in Dynamic Probabilistic Safety Assurance
Razieh Arshadizadeh, Mahmoud Asgari, Zeinab Khosravi +2
Machine Learning (ML) models are increasingly integrated into safety-critical systems, such as autonomous vehicle platooning, to enable real-time decision-making. However, their in…
Explaining Large Language Models with gSMILE
Zeinab Dehghani, Mohammed Naveed Akram, Koorosh Aslansefat +2
Large Language Models (LLMs) such as GPT, LLaMA, and Claude achieve remarkable performance in text generation but remain opaque in their decision-making processes, limiting trust a…
SafeLLM: Domain-Specific Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance
Connor Walker, Callum Rothon, Koorosh Aslansefat +2
The Offshore Wind (OSW) industry is experiencing significant expansion, resulting in increased Operations \& Maintenance (O\&M) costs. Intelligent alarm systems offer the prospect…