People

Carlos Rodriguez started his PhD has worked as a research scientist in the sector of Fluid Dynamics at the Department of Mechanical Engineering and Aeronautics at City, University of London (UK) since 2016. During his PhD degree he was involved in a Marie Skłodowska-Curie Initial Training Networks (ITN) project (with acronym IPPAD) focusing on the development of a systematic understanding of soot emission reduction strategies from Diesel engines. The researcher worked closely and interacted with the universities and industries of the ITN network (Friedrich- Alexander-Universität Erlangen-Nürnberg (DE), Lund University (SE), Technische Universität München (DE), IFP Energies Nouvelles (FR), Afton Chemical Limited (UK), Perkins Engines Co Ltd (UK), AVL List GmbH (AT), Caterpillar Fuel Systems (US), Argonne National Laboratory (US), Sandia National Laboratories (US)). After the end of his PhD (August 2019), he continued his research at City, University of London. His postdoctoral research focuses on the simulation of compressible multiphase flows and multicomponent vaporization in Diesel sprays. He is responsible for the development of a numerical framework that combines the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) EoS, vapor and liquid equilibrium (VLE) calculations coupled with the Navier-Stokes equations to perform simulations for dual-fuel injections simultaneously with the in nozzle flow that takes into account the multicomponent cavitation process of the liquid fuel. Apart from the applied nature of his research, he has worked on fundamental aspects of numerical methodologies, publishing three papers in well-known peer reviewed journals. During his post-doctoral research, he worked with open source (OpenFOAM) software for the prediction of cavitation in various hydraulic devices, focusing mainly on Diesel injection systems. Due to the nature of such systems, he has gained experience on compressible multiphase flows with phase-change and non-ideal fluid effects. As part of this work, some early neural network-based AI models were investigated to accelerate the algorithms developed by predicting the thermodynamic stability of complex fuel mixtures by knowing the internal energy, density and composition of the mixture. Moreover, he is actively involved in the supervision of three early career researchers (PhD students). As the specific topic of his research is of interest to oil companies, he has collaborated with BP International Ltd, the leading UK fuel manufacturer. Apart from applied research in fuel systems, he has also worked in fundamental bubble dynamic cases for understanding the interaction of bubbles with stationary boundaries. Over the course of the post-doctoral career so far, he has produced two publications to peer-reviewed journals related to Diesel injections, while also participated in five international conferences as author/presenter.

Dr Ioannis Karathanassis is currently a Lecturer at City, University of London. In the course of his research activities, he has gained substantial experience in the design and development of test rigs suitable for the thermo-hydraulic evaluation of various flow devices and the visualisation/quantification of complex single and multi-phase flows (with or without phase-change). Besides, he is highly experienced in the simulation of single and two-phase, laminar and turbulent, incompressible and compressible flows relevant to a wide range of devices in the automotive, aviation, marine and energy sectors, e.g. thermal-management, HVAC, hydraulic and propulsion systems. He received his PhD from the National Technical University of Athens in 2015 on heat-transfer enhancement techniques, which was awarded as the best Thesis in applied sciences by NCSR Demokritos, the largest research institute in Greece. Between 2015-2017, he worked as a post-doctoral research fellow at City, supported by EU-funded projects. During this period and until now, he has been working closely with the Argonne National Laboratory (US), where he performed the first ever-reported experiment in cavitating orifices using high-energy X-rays. Furthermore, he is currently the Co-Investigator of an international Marie Curie Innovative Training Networks programme (MSCA-EID-861002, 2019-2023) on dual-fuel engines. His first PhD co-supervised student graduated in 2019, while he is currently (co-) supervising 6 PhD students. He has published over 40 peer-reviewed journal and conference papers (H-index 12). Dr Karathanassis has also collaborated closely with several industries including Caterpillar/Perkins Engines UK, Lubrizol Corp./Ltd., Delphi Diesel Systems UK, Woodward L’Orange, ISUZU Motors Japan and BP International Ltd.

Prof. Manolis Gavaises received PhD from Imperial College London in 1997 (the 1998 Richard Way Prize for ‘Most outstanding doctoral thesis in the area of IC engines in the UK’; the Arch T. Collwell Merit Award from the Society of Automotive Engineers (SAE)). He was appointed lecturer at the School of Engineering and Mathematical Sciences of City University London in 2001, promoted to Reader in 2006 and Professor and Director of the ThermoFluids Engineering Research Centre at City in 2009. In 2009-2012 he was holding the Delphi Diesel Systems Chair in FIE Fluid Dynamics. MG is currently a director of the International Institute for Cavitation Research at City in partnership with TU Delft and Loughborough Universities supported by The Lloyd’s Register Foundation (The LRF). In 2015 he was appointed Associate Editor of Int. J. Engine Res. while he is the editor of a special volume on ‘Cavitation in IC Engines’ published in 2014. He serves on the editorial board of Atomisation & Sprays, Journal of Applied Mathematics and Interfacial Phenomena and Heat Transfer. In 2013 he was elected secretary of the organisation Liquid Atomisation and Spray Systems (ILASS-Europe). He serves on the organisation committee of 3 major international conferences (the IMechE conference on Fuel Injection Systems, ILASS-Europe and the SIA conference on Diesel Powertrain). He is a Fellow of the Institution of Mechanical Engineers in the UK and Fellow of the Institute of Applied Mathematics.

Dr Lyle Pickett received his PhD from the University of Wisconsin-Madison in 2000. He now holds the title of Distinguished Member of the Technical Staff at Sandia National Laboratories in Livermore, California, a position held by only the top 10% of the R&D staff at Sandia. He has sustained funding from the U.S. Department of Energy, and other automotive and energy industries totalling more than $11M USD to support his laboratory over the last 15 years. His research is award winning, having received 6 different Society of Automotive Engineers (SAE) “best-paper” category awards, as well as similar awards from the Institute of Liquid Atomisation and Spray Systems and American Society of Mechanical Engineers. He serves as an organizer or scientific committee member for SAE, the Combustion Institute, LES4ICE, and is a fellow of the SAE. He has published over 100 scientific papers (H-index 38), and delivered over 20 invited keynote talks. Main achievements of his work is the development of quantitative mixture fraction and soot datasets in a spray chamber operating at high-pressure, high-temperature conditions representative of a diesel engine.

Dr Eduardo Alonso (supervisory team at CITY) is Associate Professor in Computing at CITY, with over 100 publications. His research interests pivot around AI with an emphasis on optimisation algorithms and Deep Learning and their application to renewable energies, transport, health sciences and nanotechnology. He has acted as vice-chair of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB, the British learned society for AI) and won the first prize in the European Institute of Innovation and Technology (EIT) ICT Labs Idea Challenge on Smart Energy Systems in 2014. He has contributed to The Cambridge Handbook of Artificial Intelligence and publishes regularly in specialised journals such as IEEE Transactions on Neural Networks and Learning Systems, Neural Computation, Neural Networks, and Neuroinformatics. His papers have received awards by the IEEE Computational Intelligence Society and at the European Conference of Mathematical and Theoretical Biology. He has been a member of the organising and programme committees of The International Joint Conferences on Artificial Intelligence (IJCAI) and The International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS). Dr Alonso is the Director of the Artificial Intelligence Research Centre (CitAI) at CITY. (Google Scholar citations exceeds 1700, h-index 20, i10-index 43).

Dr Alex (Aram) Ter-Sarkisov (supervisory team at CITY) received his PhD in Computer Science in 2012 from Massey University, New Zealand, his thesis was on mathematical modeling of the runtime of Evolutionary Algorithms (EAs). He held postdoc positions at Waterloo (2013), Canada, Universite du Maine (2014-2015), France and Dublin Institute of Technology (2015-2018), Ireland. Since 2019 he is a Lecturer in Computer Science position at City. In the past few years he has published papers on Deep Learning (DL) in Computer Vision (CV) with the emphasis on instance segmentation and neural style transfer (CRV 2017, BMVC 2018, ICPRAM 2020), language modeling (ACM 2015) and EAs (Soft Computing, 2017).