Scott Barnett

52 papers A* 2A 1B 10C 1Misc 1Journal 28Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Large language models and conditional rules in clinical decision support systems.
Health Inf. Sci. Syst.
Shangeetha Sivasothy, Adrian Bingham, Irini Logothetis, Scott Barnett, Mohamed Abdelrazek, Carl Luckhoff, Joseph Mathew, Rajesh Vasa, Kon Mouzakis
2025 J jnl
Channel-annotated deep learning for enhanced interpretability in EEG-based seizure detection.
Biomed. Signal Process. Control.
Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien
2025 J jnl
Monitoring Machine Learning Systems: A Multivocal Literature Review.
CoRR
Hira Naveed, Scott Barnett, Chetan Arora, John C. Grundy, Hourieh Khalajzadeh, Omar Haggag
2025 B conf
RAGProbe: Breaking RAG Pipelines with Evaluation Scenarios.
CAIN
Shangeetha Sivasothy, Scott Barnett, Stefanus Kurniawan, Zafaryab Rasool, Rajesh Vasa
2025 J jnl
TaskEval: Synthesised Evaluation for Foundation-Model Tasks.
CoRR
Dilani Widanapathiranage, Scott Barnett, Stefanus Kurniawan, Wannita Takerngsaksiri
2025 J jnl
The M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments.
CoRR
Srikanth Thudumu, Hy Nguyen, Hung Du, Nhat Duong, Zafaryab Rasool, Rena Logothetis, Scott Barnett, Rajesh Vasa, Kon Mouzakis
2024 Misc conf
A Novel Vision-Based Transformer for Seizure Detection with Multi-biosignals.
AusDM
Sheng Wong, Scott Barnett, Shobi Sivathamboo, Piero Perucca, Zongyuan Ge, Patrick Kwan, Levin Kuhlmann, Terence J. O'Brien
2024 J jnl
Comparative analysis of real issues in open-source machine learning projects.
Empir. Softw. Eng.
Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa
2024 J jnl
Evaluating LLMs on document-based QA: Exact answer selection and numerical extraction using CogTale dataset.
Nat. Lang. Process. J.
Zafaryab Rasool, Stefanus Kurniawan, Sherwin Balugo, Scott Barnett, Rajesh Vasa, Courtney Chesser, Benjamin M. Hampstead, Sylvie Belleville, Kon Mouzakis, Alex Bahar-Fuchs
2024 J jnl
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models.
CoRR
Scott Barnett, Zach Brannelly, Stefanus Kurniawan, Sheng Wong
2024 B conf
Green Runner: A Tool for Efficient Deep Learning Component Selection.
CAIN
Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz
2024 B conf
LLMs for Test Input Generation for Semantic Applications.
CAIN
Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Abdelrazek
2024 J jnl
LLMs for Test Input Generation for Semantic Caches.
CoRR
Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Almorsy Abdelrazek
2024 J jnl
Large language models for generating rules, yay or nay?
CoRR
Shangeetha Sivasothy, Scott Barnett, Rena Logothetis, Mohamed Abdelrazek, Zafaryab Rasool, Srikanth Thudumu, Zach Brannelly
2024 B conf
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems - A Case Study.
CAIN
Hala Abdelkader, Mohamed Abdelrazek, Scott Barnett, Jean-Guy Schneider, Priya Rani, Rajesh Vasa
2024 J jnl
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study.
CoRR
Hala Abdelkader, Mohamed Abdelrazek, Scott Barnett, Jean-Guy Schneider, Priya Rani, Rajesh Vasa
2024 J jnl
Minimising changes to audit when updating decision trees.
CoRR
Anj Simmons, Scott Barnett, Anupam Chaudhuri, Sankhya Singh, Shangeetha Sivasothy
2024 J jnl
RAGProbe: An Automated Approach for Evaluating RAG Applications.
CoRR
Shangeetha Sivasothy, Scott Barnett, Stefanus Kurniawan, Zafaryab Rasool, Rajesh Vasa
2024 B conf
Seven Failure Points When Engineering a Retrieval Augmented Generation System.
CAIN
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek
2024 J jnl
Seven Failure Points When Engineering a Retrieval Augmented Generation System.
CoRR
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek
2023 A* conf
Cell2Doc: ML Pipeline for Generating Documentation in Computational Notebooks.
ASE
Tamal Mondal, Scott Barnett, Akash Lal, Jyothi Vedurada
2023 — conf
Decentralized Federated Learning Strategy with Image Classification using ResNet Architecture.
CCNC
Hung Du, Srikanth Thudumu, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa, Kon Mouzakis
2023 J jnl
Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique.
Sensors
Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett
2023 J jnl
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset.
CoRR
Zafaryab Rasool, Scott Barnett, Stefanus Kurniawan, Sherwin Balugo, Rajesh Vasa, Courtney Chesser, Alex Bahar-Fuchs
2023 J jnl
Green Runner: A tool for efficient model selection from model repositories.
CoRR
Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz
2023 — conf
MLGuard: Defend Your Machine Learning Model!
SE4SafeML@SIGSOFT FSE
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
2023 J jnl
MLGuard: Defend Your Machine Learning Model!
CoRR
Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa
2023 J jnl
Toward a Unified mHealth Platform: A Survey of Current User Challenges and Expectations.
IEEE Access
Ben Joseph Philip, Mohamed Almorsy Abdelrazek, Scott Barnett, Alessio Bonti, John Grundy
2023 B conf
mHealthSwarm: A Unified Platform for mHealth Applications.
ENASE
Ben Joseph Philip, Yasmeen Anjeer Alshehhi, Mohamed Abdelrazek, Scott Barnett, Alessio Bonti, John Grundy
2022 B conf
A Framework for Evaluating MRC Approaches with Unanswerable Questions.
e-Science
Hung Du, Srikanth Thudumu, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa, Kon Mouzakis
2022 J jnl
Comparative analysis of real bugs in open-source Machine Learning projects - A Registered Report.
CoRR
Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa
2022 — conf
MLSmellHound: A Context-Aware Code Analysis Tool.
ICSE (NIER)
Jai Kannan, Scott Barnett, Luis Cruz, Anj Simmons, Akash Agarwal
2022 J jnl
MLSmellHound: A Context-Aware Code Analysis Tool.
CoRR
Jai Kannan, Scott Barnett, Luís Cruz, Anj Simmons, Akash Agarwal
2022 B conf
PiMS: A Pre-ML Labelling Tool.
e-Science
Irini Logothetis, Scott Barnett, Leonard Hoon, Srikanth Thudumu, Joseph Mathew, Carl Luckhoff, Gerard O'Reilly, David Collard, Rajesh Vasa, Kon Mouzakis, Mark Fitzgerald
2022 B conf
Subspace based Anomaly Detection Framework for Point Clouds.
e-Science
Johnahan Van Zyl, Hung Du, Srikanth Thudumu, Irini Logothetis, Scott Barnett, Rajesh Vasa, Kon Mouzakis
2022 — conf
Towards Better mHealth Apps: Understanding Current Challenges and User Expectations.
MOBILESoft
Ben Joseph Philip, Mohamed Abdelrazek, Scott Barnett, Alessio Bonti, John C. Grundy
2021 — conf
Emotions in Computer Vision Service Q&A.
SEmotion@ICSE
Alex Cummaudo, Ulrike Maria Graetsch, Maheswaree Kissoon Curumsing, Rajesh Vasa, Scott Barnett, John Grundy
2021 C conf
Towards a taxonomy for annotation of data science experiment repositories.
SCAM
Shangeetha Sivasothy, Scott Barnett, Niroshinie Fernando, Rajesh Vasa, Roopak Sinha, Andrew J. Simmons
2020 A conf
A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects.
ESEM
Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana, Akshat Bajaj, Rajesh Vasa
2020 J jnl
A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects.
CoRR
Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana, Akshat Bajaj, Rajesh Vasa
2020 J jnl
Beware the evolving 'intelligent' web service! An integration architecture tactic to guard AI-first components.
CoRR
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy, Mohamed Abdelrazek
2020 — conf
Beware the evolving 'intelligent' web service! an integration architecture tactic to guard AI-first components.
ESEC/SIGSOFT FSE
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy, Mohamed Abdelrazek
2020 J jnl
Interpreting Cloud Computer Vision Pain-Points: A Mining Study of Stack Overflow.
CoRR
Alex Cummaudo, Rajesh Vasa, Scott Barnett, John C. Grundy, Mohamed Abdelrazek
2020 A* conf
Interpreting cloud computer vision pain-points: a mining study of stack overflow.
ICSE
Alex Cummaudo, Rajesh Vasa, Scott Barnett, John C. Grundy, Mohamed Abdelrazek
2020 J jnl
Ranking Computer Vision Service Issues using Emotion.
CoRR
Maheswaree Kissoon Curumsing, Alex Cummaudo, Ulrike Maria Graetsch, Scott Barnett, Rajesh Vasa
2020 J jnl
Threshy: Supporting Safe Usage of Intelligent Web Services.
CoRR
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy
2020 — conf
Threshy: supporting safe usage of intelligent web services.
ESEC/SIGSOFT FSE
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John C. Grundy
2019 J jnl
Supporting multi-view development for mobile applications.
J. Comput. Lang.
Scott Barnett, Iman Avazpour, Rajesh Vasa, John Grundy
2018 J jnl
Data Provenance for Sport.
CoRR
Andrew J. Simmons, Scott Barnett, Simon Vajda, Rajesh Vasa
2015 — conf
A Conceptual Model for Architecting Mobile Applications.
WICSA
Scott Barnett, Rajesh Vasa, Antony Tang
2015 B conf
A multi-view framework for generating mobile apps.
VL/HCC
Scott Barnett, Iman Avazpour, Rajesh Vasa, John C. Grundy
2015 — conf
Bootstrapping Mobile App Development.
ICSE (2)
Scott Barnett, Rajesh Vasa, John Grundy