Contact Dr Irene Moulitsas
- Tel: +44 (0) 1234 758572
- Email: i.moulitsas@cranfield.ac.uk
- ORCID
Areas of expertise
- Computing, Simulation & Modelling
Background
Dr Moulitsas received her PhD in Scientific Computation from the University of Minnesota in USA and a BSc in Mathematics, with emphasis on Computational Mathematics, from the University of Crete in Greece. Before joining Cranfield University, Irene was a research scientist at the University of Cyprus, adjunct faculty at the Cyprus University of Technology and research assistant at the University of Minnesota Army High Performance Computing Research Center (AHPCRC) and the Minnesota Supercomputing Institute (MSI).
Research opportunities
High Performance Computing, Machine Learning, Artificial Intelligence, Graph Algorithms, Numerical Simulations, Scientific Computing, Computational Science and Engineering, Novel algorithms development for solving important existing and emerging problems, and development of practical software tools implementing these algorithms.
Current activities
Dr Irene Moulitsas joined Cranfield University in 2012 and is currently a Senior Lecturer in Scientific Computing. Irene's research has focused on developing novel algorithms for enabling the efficient execution of large scientific computations on parallel processing platforms. She has developed highly efficient serial and parallel algorithms, and software, that are publicly available for use. Her research work is published in highly selective conferences and international journals and her software packages are used extensively by numerous universities, research laboratories, and companies. In 2021 Irene was selected in the Top 100 Women in Engineering in the UK (INWED2021: Engineering Heroes).
Clients
Irene's research work has been funded through the US National Science Foundation (NSF) and the Department of Defence (DoD), European Framework Programs (FP5 and FP7), the Research Promotion Foundation (RPF) of Cyprus, UK Research and Innovation EPSRC and Innovate UK.
Publications
Articles In Journals
- Alreshidi I, Moulitsas I & Jenkins KW. (2024). Advancing Aviation Safety Through Machine Learning and Psychophysiological Data: A Systematic Review. IEEE Access, 12
- Bala Bisandu D & Moulitsas I. (2024). Prediction of flight delay using deep operator network with gradient-mayfly optimisation algorithm. Expert Systems with Applications, 247
- Amran Abolholl HA, Teschner T-R & Moulitsas I. (2024). A Hybrid Computer Vision and Machine Learning Approach for Robust Vortex Core Detection in Fluid Mechanics Applications. Journal of Computing and Information Science in Engineering, 24(6)
- Abolholl HAA, Teschner T-R & Moulitsas I. (2023). Surface Line Integral Convolution-Based Vortex Detection Using Computer Vision. Journal of Computing and Information Science in Engineering, 23(5)
- Bisandu DB & Moulitsas I. (2023). A Deep BiLSTM Machine Learning Method for Flight Delay Prediction Classification. Journal of Aviation/Aerospace Education & Research, 32(2)
- Alreshidi I, Moulitsas I & Jenkins KW. (2023). Multimodal Approach for Pilot Mental State Detection Based on EEG. Sensors, 23(17)
- Alreshidi I, Bisandu D & Moulitsas I. (2023). Illuminating the Neural Landscape of Pilot Mental States: A Convolutional Neural Network Approach with Shapley Additive Explanations Interpretability. Sensors, 23(22)
- Wright KVM, Kayraklioglu E, Moulitsas I, Slaughter E, Long B, .... (2023). 6th Parallel Applications Workshop, Alternatives to MPI+X (PAW-ATM). ACM International Conference Proceeding Series
- Xu Z, Maria A, Chelli K, Premare TDD, Bilbao X, .... (2023). Vortex and Core Detection using Computer Vision and Machine Learning Methods. European Journal of Computational Mechanics, 32(5)
- Bisandu DB, Moulitsas I & Filippone S. (2022). Social ski driver conditional autoregressive-based deep learning classifier for flight delay prediction. Neural Computing and Applications, 34(11)
- Homaid MS, Bisandu DB, Moulitsas I & Jenkins K. (2022). Analysing the Sentiment of Air-Traveller: A Comparative Analysis. International Journal of Computer Theory and Engineering, 14(2)
- Morris K, Ferguson M, Moulitsas I & Slaughter E. (2022). Message from the Workshop Chairs. 2022 IEEE/ACM Parallel Applications Workshop: Alternatives To MPI+X (PAW-ATM)
- Alsanousi H, Albarrak N, Moulitsas I & Filippone S. (2021). Understanding customer behaviours toward the use of electronic banking given customer characteristics and financial portfolios. International Journal of Business and Social Science, 12(1)
- Alexiadis A, Simmons MJH, Stamatopoulos K, Batchelor HK & Moulitsas I. (2021). The virtual physiological human gets nerves! How to account for the action of the nervous system in multiphysics simulations of human organs. Journal of The Royal Society Interface, 18(177)
- Rasmussen S, Gutmann ED, Moulitsas I & Filippone S. (2021). Fortran Coarray Implementation of Semi-Lagrangian Convected Air Particles within an Atmospheric Model. ChemEngineering, 5(2)
- Albano A, le Guillou E, Danzé A, Moulitsas I, Sahputra IH, .... (2021). How to Modify LAMMPS: From the Prospective of a Particle Method Researcher. ChemEngineering, 5(2)
- Alexiadis A, Simmons MJH, Stamatopoulos K, Batchelor HK & Moulitsas I. (2021). Publisher Correction: The duality between particle methods and artificial neural networks. Scientific Reports, 11(1)
- Alexiadis A, Simmons MJH, Stamatopoulos K, Batchelor HK & Moulitsas I. (2020). The duality between particle methods and artificial neural networks. Scientific Reports, 10(1)
- Szőke M, Józsa TI, Koleszár Á, Moulitsas I & Könözsy L. (2018). Performance Evaluation of a Two-Dimensional Lattice Boltzmann Solver Using CUDA and PGAS UPC Based Parallelisation. ACM Transactions on Mathematical Software, 44(1)
- Sharma A & Moulitsas I. (2017). MPI to Coarray Fortran: Experiences with a CFD Solver for Unstructured Meshes. Scientific Programming, 2017
- Rutherford R, Moulitsas I, Snow BJ, Kolios AJ & De Dominicis M. (2015). CranSLIK v2.0: improving the stochastic prediction of oil spill transport and fate using approximation methods. Geoscientific Model Development, 8(10)
- Snow BJ, Moulitsas I, Kolios AJ & De Dominicis M. (2014). CranSLIK v1.0: stochastic prediction of oil spill transport and fate using approximation methods. Geoscientific Model Development, 7(4)
- Moulitsas I & Georgiou G. (2009). Steady Flow of a Two-Dimensional Liquid Curtain Under Pressure. Engineering Applications of Computational Fluid Mechanics, 3(2)
- Taliadorou E, Georgiou GC & Moulitsas I. (2009). Weakly compressible Poiseuille flows of a Herschel–Bulkley fluid. Journal of Non-Newtonian Fluid Mechanics, 158(1-3)
- Rouson DWI, Kassinos SC, Moulitsas I, Sarris IE & Xu X. (2008). Dispersed-phase structural anisotropy in homogeneous magnetohydrodynamic turbulence at low magnetic Reynolds number. Physics of Fluids, 20(2)
- Rouson DWI, Rosenberg R, Xu X, Moulitsas I & Kassinos SC. (2008). A grid-free abstraction of the Navier-Stokes equations in Fortran 95/2003. ACM Transactions on Mathematical Software, 34(1)
- Moulitsas I & Karypis G. (2004). Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods.
- CAPUTO J-G, EFREMIDIS N, FLYTZANIS N, LAZARIDES N, GAIDIDEI Y, .... (2000). STATIC PROPERTIES AND WAVEGUIDE MODES OF A WIDE LATERAL WINDOW JOSEPHSON JUNCTION. International Journal of Modern Physics C, 11(03)
- Caputo J-G, Flytzanis N, Gaididei Y, Moulitsa I & Vavalis E. (1998). Split Mode Method for the Elliptic 2D Sine-Gordon Equation: Application to Josephson Junction in Overlap Geometry. International Journal of Modern Physics C, 09(02)
Conference Papers
- Bisandu DB & Moulitsas I. (2023). A Hybrid Ensemble Machine Learning Approach For Arrival Flight Delay Classification Prediction Using Voting Aggregation Technique
- Xiong X, Teschner T-R & Moulitsas I. (2023). Simulate cavitation bubble with single component multi-phase Lattice Boltzmann method
- Alreshidi I, Yadav S, Moulitsas I & Jenkins K. (2023). A Comprehensive Analysis of Machine Learning and Deep Learning Models for Identifying Pilots’ Mental States from Imbalanced Physiological Data
- Albarrak N, Alsanousi H, Moulitsas I & Filippone S. (2022). Using Big Data to Compare Classification Models for Household Credit Rating in Kuwait
- Alsanousi H, Albarrak N, Moulitsas I & Filippone S. (2022). Using client’s Characteristics and Their Financial Products to Predict Their Usage of Banking Electronic Channels
- Homaid MS & Moulitsas I. (2022). Measuring Airport Service Quality Using Machine Learning Algorithms
- Alreshidi IM, Moulitsas I & Jenkins KW. (2022). Miscellaneous EEG Preprocessing and Machine Learning for Pilots' Mental States Classification: Implications
- Bisandu DB & Moulitsas I. (2022). A bidirectional deep LSTM machine learning method for flight delay modelling and analysis
- Abolholl HAA, Teschner T-R & Moulitsas I. (2022). A hybrid computer vision and machine learning approach for robust vortex core detection in fluid mechanics applications
- Bala Bisandu D, Salih Homaid M, Moulitsas I & Filippone S. (2021). A Deep Feedforward Neural Network and Shallow Architectures Effectiveness Comparison: Flight Delays Classification Perspective
- Figueroa-González A, Oliveira J, Teschner TR, Könözsy L, Moulitsas I, .... (2020). Validation of an in-house lattice Boltzmann solver for a multiphase flow application
- Rasmussen S, Gutmann ED, Friesen B, Rouson D, Filippone S, .... (2018). Development and performance comparison of MPI and Fortran Coarrays within an atmospheric research model
- Weber S, Southgate D, Mullaney K, James S, Rutherford R, .... (2018). Bladesense - A novel approach for measuring dynamic helicopter rotor blade deformation
- Józsa TI, Szőke M, Teschner T-R, Könözsy L & Moulitsas I. (2016). VALIDATION AND VERIFICATION OF A 2D LATTICE BOLTZMANN SOLVER FOR INCOMPRESSIBLE FLUID FLOW
- Damianou Y, Georgiou GC & Moulitsas I. (2013). Combined effects of compressibility and slip in flows of a Herschel–Bulkley fluid
- Radhakrishnan H, Moulitsas I, Syrakos A, Hayes D, Zodiates G, .... (2012). On improving the operational performance of the Cyprus coastal ocean forecasting system
- Moulitsas I. (2011). Graph Partitioning for Scientific Computing Applications
- Moulitsas I. (2010). Mesh partitioning and fill reducing ordering for domain decomposition problems
- Taliadorou E, Georgiou G & Moulitsas I. (2009). Weakly compressible flows of viscoplastic fluids
- Moulitsas I & Karypis G. (2008). Architecture Aware Partitioning Algorithms
- Moulitsas I & Karypis G. (2006). Partitioning algorithms for parallel applications on heterogeneous architectures
- Moulitsas I & Karypis G. (2001). Multilevel algorithms for generating coarse grids for multigrid methods
- Moulitsas I & Karypis G. (2001). Multilevel Algorithms for Generating Coarse Grids for Multigrid Methods
- Radhakrishnan H, Moulitsas I, Hayes D, Zodiatis G & Georgiou G. Development of a parallel Cyprus coastal ocean forecasting and observing system
