Rahul Agrahari

Research Engineer

Rahul was awarded a BSc in Information and Technology in India. He has completed his MSc in Computer Science(AI) at Trinity College, Dublin where he specialised in intelligent systems. Prior to this, he worked in India as a Project Engineer at Wipro Technology for almost three years. Rahul is now working as a Research Engineer in the dLab at ADAPT.

Research Domains

Deep Learning
Machine Learning

Publications by Rahul Agrahari

The interaction of normalisation and clustering in sub-domain definition for multi-source transfer learning based time series anomaly detection

PUBLICATION:	Knowledge-based Systems
AUTHOR(S):	Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John Kelleher
DATE:	17 September 2022
TYPE:	Journal Articles

Assessing Feature Representations for Instance-Based Cross-Domain Anomaly Detection in Cloud Services Univariate Time Series Data

PUBLICATION:	IoT
AUTHOR(S):	Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem, John Kelleher
DATE:	29 January 2022
TYPE:	Journal Articles

A Data-Driven Analysis of Formula 1 Car Races Outcome

PUBLICATION:	AICS 2022 - 30th Irish Conference on Artificial Intelligence and Cognitive Science
AUTHOR(S):	Ankur Patil, Nishtha Jain, Rahul Agrahari, Murhaf Hossari, Fabrizio Orlandi & Soumyabrata Dev
DATE:	23 February 2023
TYPE:	Conf papers

An Advert Creation System for 3D Product Placements

PUBLICATION:	ECML-PKDD 2020 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
AUTHOR(S):	Ivan Bacher, Hossein Javidnia, Soumyabrata Dev, Rahul Agrahari, Murhaf Hossari, Matthew Nicholson, Clare Conran, Jian Tang, Peng Song, David Corrigan, François Pitié
DATE:	14 September 2020
TYPE:	Conf papers

DeepReal - A Deep Learning Based 3D Advert Integration System

PUBLICATION:	NEM Summit 2020 - B’Smart - European Media Science and Technology Meets Arts, 2020.
AUTHOR(S):	Ivan Bacher, Hossein Javidnia, Soumyabrata Dev, Rahul Agrahari, Murhaf Hossari, Matthew Nicholson, Clare Conran, David Corrigan, Francois Pitié
DATE:	18 May 2020
TYPE:	Conf papers