Sean Moran | Personal Page

My ChatGPT assisted bio:

Dr. Moran is a seasoned professional with a passion for innovation and a track record of success in developing and deploying AI/ML for large, complex organisations. As a leader of teams developing AI/ML technologies, he has made several contributions to the field, including:

A scalable real-time source code search engine
A federated AI/ML system for COVID-19 detection from chest CT scans
An automated system for detecting illicit transactions on blockchains
Anomaly detection techniques for network devices and cybersecurity

Currently he leads a team at JP Morgan Chase & Co. that is bringing innovative new anomaly detection capabilities to the firm.

Dr. Moran's expertise has been recognized by JP Morgan, where he was named the top inventor of the year in 2022. He has also extensively published patents and scientific papers.

Prior to joining JP Morgan, Dr. Moran served as a Senior Research Scientist at Huawei Technologies R&D and was a member of the Edinburgh University NLP group. His Ph.D in AI/ML was earned at the University of Edinburgh.

Service to the Community

ECCV 2020 conference certificate (high quality reviews)

Awesome Papers on Learning to Hash: a living literature review of the field

Senatus AI: Software Development Re-invented

Patents Granted

A device and method for image processing. An image processing device for transforming an image. Sean Moran et al (2021).

Image Processor. An image processing module configured to implement a multi-part trained artificial intelligence model. Sean Moran et al (2020).

Noise Estimation. Processing data derived from the image by means of a first trained model for detecting stochastic noise so as to form a first noise estimate;. Sean Moran et al (2020).

Image Processor. An image processor comprising a plurality of processing modules configured to operate in series to refine a raw image captured by a camera. Sean Moran et al (2020).

Published and Presented Work

New! A Benchmark Generative Probabilistic Model for Weak Supervised Learning
Georgios Papadopoulos, Fran Silavong, Sean Moran. In Arxiv, 2022.
[ bibtex ]

New! A New Baseline for GreenAI: Finding the Optimal Sub-Network via Layer and Channel Pruning
Xiaoying Zhi, Varun Babbar, Pheobe Sun, Fran Silavong, Ruibo Shi, Sean Moran. In Arxiv, 2022.
[ bibtex ]

New! API-Spector: an API-to-API Specification Recommendation Engine
Sae Young Moon, Fran Silavong, Sean Moran. In Arxiv, 2022.
[ bibtex ]

Towards Data Efficient and Robust Speech Representation Model Distillation
Pheobe Sun, Ruibo Shi, Ahmad Emami, Sean Moran. In NeurIPS ENLSP Workshop, 2022.
[ bibtex ]

Code Librarian: A Software Package Recommendation Engine
Lili Tao, Alexandru-Petre Cazan, Senad Ibraimoski and Sean Moran. In ICSE SEIP, 2023.
[ bibtex ]

Topical: Learning Repository Embeddings from Source Code using Attention
Agathe Lherondelle, Yash Satsangi, Fran Silavong, Shaltiel Eloul, Sean Moran. In Arxiv, 2022.
[ bibtex ]

Ledgit: A Service to Diagnose Illicit Addresses on Blockchain using Multi-Modal Unsupervised Learning
Xiaoying Zhi, Yash Satsangi, Sean Moran, Shaltiel Eloul. In CIKM, 2022.
[ poster ][ bibtex ]

Utility Preserving Biometric Information Anonymization
Bill Moriarty, Chun-Fu Chen, Shaohan Hu, Sean Moran, Marco Pistoia, Vincenzo. Piuri, Pierangela Samarati, In ESORICS, 2022.
[ bibtex ]

CV4Code: Sourcecode Understanding via Visual Code Representations
Ruibo Shi, Lili Tao, Rohan Saphal, Fran Silavong, and Sean Moran. In ACCV, 2022.
[ poster ][ bibtex ] [ code ]

Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies
Shaltiel Eloul, Fran Silavong, Sanket Kamthe, Antonios Georgiadis, Sean Moran. In Arxiv, 2022.
[ bibtex ]

Senatus: A Fast and Accurate Code-To-Code Recommendation Engine
Fran Silavong, Sean Moran, Antonios Georgiadis, Rohan Saphal, Robert Otter. In Mining Software Repositories (MSR) Conference, 2022.
[ bibtex ]

ST-FL: style transfer preprocessing in federated learning for COVID-19 segmentation.
Antonios Georgiadis, Varun Babbar, Fran Silavong, Sean Moran, Robert Otter. In SPIE Medical Imaging, 2022.
[ bibtex ] [ poster ]

Improving Streaming Cryptocurrency Transaction Classification via Biased Sampling and Graph Feedback.
Shaltiel Eloul, Sean Moran, Jacob Mendel. In ACSAC, 2021.
[ bibtex ]

Low light video Enhancement using Synthetic Data Produced with an Intermediate Domain Mapping.
Danai Triantafyllidou,Sean Moran, Steven McDonagh, Sarah Parisot, Gregory Slabaugh. In ECCV, 2020.
[ bibtex ] [ code ] [ supplementary ] [ 10 minute video ] [ 1 minute video ]

DeepLPF: Deep Local Parametric Filters For Image Enhancement.
Sean Moran, Pierre Marza, Steven McDonagh, Sarah Parisot, Gregory Slabaugh. In CVPR, 2020.
[ bibtex ] [ code ] [ supplementary ] [ poster ] [ slides ] [ 1 minute video ]

CURL: Neural Curve Layers for Global Image Enhancement.
Sean Moran, Steven McDonagh, Gregory Slabaugh. In ICPR, 2020.
[ bibtex ] [ talk (ICPR) ] [ talk (IADS) ] [ poster ] [ code ] [ video ] [ supplementary ]

NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network.
Hao Guan, Liu Liu, Sean Moran, Fenglong Song, Gregory Slabaugh. In Arxiv, 2019.
[ bibtex ]

A Novel Genomics-Based Platform for the Creation of Environmental-Responsive Gene Promoters.
Juan Manuel Iglesias, Ross M. Fraser, Sean Moran, Patricia del Rio, Katie Baker, Sinclair Cooper, Graham Whyteside, Nicolle Kippen, Polyxeni Katsoupi, Rinku Rajan, Jorge Yanez, Michael L. Roberts. In Molecular Therapy 2018.
[ Abstract ]

Learning to Hash for Computer Vision and Image Retrieval
Sean Moran. In Arxiv 2019.

Learning to Project and Binarise for Hashing Based Approximate Nearest Neighbour Search.
Sean Moran. In SIGIR, 2016.
[ bibtex ] [ poster ]

Enhancing First Story Detection using Word Embeddings.
Sean Moran, Richard McCreadie, Craig MacDonald, Iadh Ounis. In SIGIR, 2016.
[ bibtex ]

Learning to Hash for Large-Scale Image Retrieval.
Sean Moran (PhD thesis, 2015)
[ bibtex ]

Regularised Cross-Modal Hashing.
Sean Moran, Victor Lavrenko. In SIGIR, 2015.
[ bibtex ] [ poster ] [ code ] [ datasets ]

A Note on Automatic Kernel Carpentry for Atomistic Support of Continuum Stress
Manfred Ulz, Sean Moran. In Arxiv, 2015.
[ bibtex ]

Graph Regularised Hashing.
Sean Moran, Victor Lavrenko. In ECIR, 2015.
[ bibtex ] [ talk ] [ poster ] [ code ] [ datasets ]

A Sparse Kernel Relevance Model for Automatic Image Annotation.
Sean Moran, Victor Lavrenko. In IJMIR 2014 (Best Papers in Image Retrieval).
[ bibtex ] [ code ] [ datasets ]

Sparse Kernel Learning for Image Annotation.
Sean Moran, Victor Lavrenko. In ICMR 2014 (Oral) (Best Student Paper Winner).
[ bibtex ] [ talk ] [ code ] [ datasets ]

Real-Time Detection, Tracking and Monitoring of Discovered Events in Social Media.
Sean Moran et al. In ACL 2014 (Demo).
[ bibtex ]

Optimal Kernel Shape and Bandwidth for Atomistic Support of Continuum Stress.
Manfred Ulz, Sean Moran. In MSMSE 2013.
[ bibtex ]

Variable Bit Quantisation for LSH.
Sean Moran, Victor Lavrenko, Miles Osborne. In ACL 2013.
[ bibtex ] [ talk ][ code ] [ datasets ]

Neighbourhood Preserving Quantisation for LSH.
Sean Moran, Victor Lavrenko, Miles Osborne. In SIGIR 2013.
[ bibtex ] [ poster ] [ code ] [ datasets ]

A Gaussian mixture modelling approach to the data-driven estimation of atomistic support for continuum stress.
Manfred Ulz, Sean Moran. In MSMSE 2012.
[ bibtex ]

Optimal Tag Sets for Automatic Image Annotation.
Sean Moran, Victor Lavrenko. In BMVC 2011.
[ bibtex ] [ abstract ] [ talk ]

Linking Video Segments to Relevant Wikipedia Content
Victor Larevnko, Johanna Moore, Sean Moran (2010).

Automatic Image Tagging.
Sean Moran (MSc Disseration, 2009).

Video Inpainting (Overview)
Sean Moran (2009).

Using the Grid for Satellite Imagery with UNOSAT.
Sean Moran, Patricia Mendez Lorenzo. Internal UNOSAT-CERN report, 2005

Robust Fusion of Colour Appearance Models for Object Tracking.
Chris Town, Sean Moran. In BMVC 2004.
[ bibtex ]