Improved E-model for monitoring quality of multi-party VoIP communications. - Mohamed Adel; Haytham Assem; Brendan Jennings; David Malone; Jonathan Dunne; Pat O'Sullivan (GLOBECOM Workshops, 2013)

A new adaptive redundancy control algorithm for VoIP applications. - Haytham Assem; David Malone; Jonathan Dunne; Pat O'Sullivan (GLOBECOM, 2013)

Monitoring VoIP call quality using improved simplified E-model. - Haytham Assem; David Malone; Jonathan Dunne; Pat O'Sullivan (ICNC, 2013)

A generic algorithm for mid-call audio codec switching. - Haytham Assem; Mohamed Adel; Brendan Jennings; David Malone; Jonathan Dunne; Pat O'Sullivan (IM, 2013)

Towards Bridging the Gap between Machine Learning Researchers and Practitioners. - Haytham Assem; Declan O'Sullivan (SmartCity, 2015)

CogNet: A network management architecture featuring cognitive capabilities. - Lei Xu; Haytham Assem; Imen Grida Ben Yahia; Teodora Sandra Buda; Ángel Martín; Domenico Gallico; Matteo Biancani; Antonio Pastor 001; Pedro A. Aranda; Mikhail I. Smirnov; Danny Raz; Olga Uryupina; et al. (EuCNC, 2016)

Discovering New Socio-demographic Regional Patterns in Cities. - Haytham Assem; Declan O'Sullivan (LBSN@SIGSPATIAL/GIS, 2016)

Spatio-Temporal Clustering Approach for Detecting Functional Regions in Cities. - Haytham Assem; Lei Xu; Teodora Sandra Buda; Declan O'Sullivan (ICTAI, 2016)

Machine Learning for Autonomic Network Management in a Connected Cars Scenario. - Gorka Vélez; Marco Quartulli; Ángel Martín; Oihana Otaegui; Haytham Assem (Nets4Cars/Nets4Trains/Nets4Aircraft, 2016)

Can machine learning aid in delivering new use cases and scenarios in 5G? - Teodora Sandra Buda; Haytham Assem; Lei Xu; Danny Raz; Udi Margolin; Elisha J. Rosensweig; Diego R. López; Marius Iulian Corici; Mikhail Smirnov; Robert Mullins; Olga Uryupina; Alberto Mozo; et al. (NOMS, 2016)

Machine learning as a service for enabling Internet of Things and People. - Haytham Assem; Lei Xu; Teodora Sandra Buda; Declan O'Sullivan (Pers. Ubiquitous Comput., 2016)

ADE: An ensemble approach for early Anomaly Detection. - Teodora Sandra Buda; Haytham Assem; Lei Xu (IM, 2017)

Urban Water Flow and Water Level Prediction Based on Deep Learning. - Haytham Assem; Salem Gharbia; Gabor Makrai; Paul Johnston; Laurence W. Gill; Francesco Pilla (ECML/PKDD (3), 2017)

RCMC: Recognizing Crowd-Mobility Patterns in Cities Based on Location Based Social Networks Data. - Haytham Assem; Teodora Sandra Buda; Declan O'Sullivan (ACM Trans. Intell. Syst. Technol., 2017)

A Framework for Enterprise Social Network Assessment and Weak Ties Recommendation. - Faisal Ghaffar; Teodora Sandra Buda; Haytham Assem; Armita Afsharinejad; Neil Hurley (ASONAM, 2018)

SCCD: Social Capital-Driven Career Development Framework. - Faisal Ghaffar; Teodora Sandra Buda; Haytham Assem; Armita Afsharinejad; Neil Hurley (ASONAM, 2018)

Practical Performance Degradation Mitigation Solution Using Anomaly Detection for Carrier-Grade Software Networks. - Marius Corici; Teodora Sandra Buda; Ranjan Shrestha; Eleonora Cau; Taner Metin; Haytham Assem (CSCN, 2018)

Analysis of Machine Learning Techniques for Anomaly Detection in the Internet of Things. - Shane Brady; Damien Magoni; John Murphy 001; Haytham Assem; A. Omar Portillo-Dominguez (LA-CCI, 2018)

DeepAD: A Generic Framework Based on Deep Learning for Time Series Anomaly Detection. - Teodora Sandra Buda; Bora Caglayan; Haytham Assem (PAKDD (1), 2018)

ST-DenNetFus: A New Deep Learning Approach for Network Demand Prediction. - Haytham Assem; Bora Caglayan; Teodora Sandra Buda; Declan O'Sullivan (ECML/PKDD (3), 2018)

A Cloud-Based AI Framework for Machine Learning Orchestration: A "Driving or Not-Driving" Case-Study for Self-Driving Cars. - Cristian Olariu; Haytham Assem; Juan Diego Ortega; Marcos Nieto (IV, 2019)

Classification of Cybercrime Indicators in Open Social Data. - Ihsan Ullah 002; Caoilfhionn Lane; Teodora Sandra Buda; Brett Drury; Marc Mellotte; Haytham Assem; Michael G. Madden (SIMBig, 2020)

Unsupervised Word Translation Pairing using Refinement based Point Set Registration. - Silviu Oprea; Sourav Dutta 001; Haytham Assem (CoRR, 2020)

Qasar: Self-Supervised Learning Framework for Extractive Question Answering. - Haytham Assem; Rajdeep Sarkar; Sourav Dutta 001 (IEEE BigData, 2021)

Mufin: Enriching Semantic Understanding of Sentence Embedding using Dual Tune Framework. - Koustava Goswami; Sourav Dutta 001; Haytham Assem (IEEE BigData, 2021)

Efficient Multi-Lingual Sentence Classification Framework with Sentence Meta Encoders. - Raj Nath Patel; Edward Burgin; Haytham Assem; Sourav Dutta 001 (IEEE BigData, 2021)

Cross-lingual Sentence Embedding using Multi-Task Learning. - Koustava Goswami; Sourav Dutta 001; Haytham Assem; Theodorus Fransen; John P. McCrae (EMNLP (1), 2021)

DTAFA: Decoupled Training Architecture for Efficient FAQ Retrieval. - Haytham Assem; Sourav Dutta 001; Edward Burgin (SIGDIAL, 2021)

Sequence-to-Sequence Learning on Keywords for Efficient FAQ Retrieval. - Sourav Dutta 001; Haytham Assem; Edward Burgin (CoRR, 2021)

Deep Neural Compression Via Concurrent Pruning and Self-Distillation. - James O'Neill; Sourav Dutta 001; Haytham Assem (CoRR, 2021)

Aligned Weight Regularizers for Pruning Pretrained Neural Networks. - James O'Neill; Sourav Dutta 001; Haytham Assem (ACL (Findings), 2022)

Multi-Stage Framework with Refinement Based Point Set Registration for Unsupervised Bi-Lingual Word Alignment. - Silviu Vlad Oprea; Sourav Dutta 001; Haytham Assem (COLING, 2022)

Enhanced Sentence Meta-Embeddings for Textual Understanding. - Sourav Dutta 001; Haytham Assem (ECIR (2), 2022)

Semantic Aware Answer Sentence Selection Using Self-Learning Based Domain Adaptation. - Rajdeep Sarkar; Sourav Dutta 001; Haytham Assem; Mihael Arcan; John P. McCrae (KDD, 2022)

Cage: A Hybrid Framework for Closed-Domain Conversational Agents. - Edward Burgin; Sourav Dutta 001; Haytham Assem; Raj Nath Patel (ECML/PKDD (6), 2022)

Self-distilled Pruning of Deep Neural Networks. - James O'Neill; Sourav Dutta 001; Haytham Assem (ECML/PKDD (2), 2022)

Attending to Entity Class Attributes for Named Entity Recognition with Few-Shot Learning. - Raj Nath Patel; Sourav Dutta 001; Haytham Assem (IntelliSys (3), 2023)

Intent Classification by the Use of Automatically Generated Knowledge Graphs. - Mihael Arcan; Sampritha H. Manjunath; Cécile Robin; Ghanshyam Verma; Devishree Pillai; Simon Sarkar; Sourav Dutta 001; Haytham Assem; John P. McCrae; Paul Buitelaar (Inf., 2023)

Improved Out-of-Scope Intent Classification with Dual Encoding and Threshold-based Re-Classification. - Hossam M. Zawbaa; Wael Rashwan; Sourav Dutta 001; Haytham Assem (LREC/COLING, 2024)

Enhancing Contextual Understanding in Large Language Models through Contrastive Decoding. - Zheng Zhao 005; Emilio Monti; Jens Lehmann 001; Haytham Assem (NAACL-HLT, 2024)