YCIL Alumni

Dr Louis Rose

Louis was a founding co-investigator of YCIL, who conducted research involving the development of model-driven and domain-specific structures and techniques for engineering large-scale, complex and distributed systems. His collaboration with Jon Timmis and Mark Coles focused on automated calibration of simulations by applying state-of-the-art software engineering techniques, a technique we have now published in the Journal of the Royal Society Interface.

Dr Mark Read

University of Sydney

 

Mark joined the group in 2007 as a Computer Science PhD student, and instigated the Experimental Autoimmune Encephalomyelitis (EAE) case study.

His expertise lies in establishing confidence that simulations accurately reflect the systems they are built to represent.

 

Dr Martina Husakova

University of Hradec Králové

Martina, based at the Faculty of Informatics and Management at the University of Hradec Králové (Czech Republic), visited YCIL for 3 months from September 2013.

Her visit aimed to gain a familiarisation of the model and simulation development process and tools used at YCIL, as part of a European Union funded research mobility project.

 

Dr Richard Greaves

University of York

Richard joined the group in 2010, having previously attained a PhD in Computational Chemistry, to work towards an MSc by Research in Computer Science, supervised by Prof. Jon Timmis. He worked on modelling the behaviour of regulatory T-cells in the disease Experimental Autoimmune Encephalomyelitis, an animal model for the autoimmune disorder, Multiple Sclerosis.  

After his MSc by Research, Richard worked with Dr Dimitris Lagos (CII) and Prof Jon Timmis (CS) on modelling microRNA regulatory networks, followed by a period working with Prof Jon Timmis and Dr Mark Coles on tool-chains for autoimmune disease modelling. 

Dr Dan Moyo

University of Sheffield

Daniel joined the group in 2010 and is registered for a PhD in Computer Science, supervised by Prof. Jon Timmis and Prof Paul Kaye. He works in collaboration with Dr. Lynette Beattie, researching how a computational agent-based model can give novel insight into the mechanisms underpinning hepatic granuloma formation in experimental visceral leishmaniasis.

Daniel joined the University of Sheffield in 2013 and now investigates whether micro-simulation modelling approaches can be used to predict episodic alcohol drinking behaviours in the British population.

Dr Richard Williams

University of Lancaster

Richard joined the group in 2010 and completed a PhD in Computer Science, supervised by Prof. Jon Timmis and Prof Eva Qwarnstrom (Dept Cardiovascular Science, Sheffield Medical School). His research focused on Agent-Based Modelling and Simulation of the intracellular NF-kB Signalling Pathway.

Richard joined the University of Lancaster in 2013 as a Management & Business Development Fellow, in the Management School.

Dr Stephanie Evans

Imperial College London

Steph joined the university in 2012 as a PhD student in the CII. Supervised by Jon Timmis, Marika Kullberg and Lourdes Curcurell-Sanchez (GSK), her project aimed to develop an understanding of the immunology of the intestinal tract using a systems biology and computational modelling approach. Steph is the lead author on our ASPASIA paper, specifically designed to study the impact of interventions on SBML model behaviour.

Dr German Leonov (Johnny)

 

University of York

Johnny worked with Dr Dimitris Lagos and Prof Jon Timmis on micro-RNA, trying to understand the role of miR-132 on microRNA processing. Johnny was funded by the CIDCATS doctoral programme here at York.

Dr Lynette Beattie

Lynette’s research focuses on a population of liver resident macrophages known as Kupffer cells, which are found within liver sinusoids. Here, they are ideally located for phagocytosis, but also provide an intracellular niche for a number of important human pathogens. By using a combination of immunological techniques including flow-cytometery, fluorescence activated cell sorting, two photon microscopy, live cell imaging, and gene expression profile analysis, she aims to understand how Kupffer cells function in health and disease.

 

Dr Simon Hickinbotham

University of York

Simon worked on developing a software tool for clinical decision support in the context of Leichmaniasis, funded by the N3CRs, in collaboration with Prof Paul Kaye and Dr Mark Coles.

Liz Gothard

Liz conducted her PhD research with Prof Martin Bees and Prof Mark Coles on mathematical models of wound healing. Liz was funded by the CIDCATS programme here at York.

 

Magnus Tripp

Magnus was working on his MEng project in Computer Science, investigating automated calibration techniques. We published an extended abstract as a result of his work, see the publication page for more information

 

Chris Saunders

Chris completed a rotation (April – July 2013) as part of the CIDCATS doctoral programme here at York, working with Jon Timmis and Mark Read on the EAE simulation.
 

Angela Privat Maldonado

Angela completed a rotation (April – July 2012) as part of the CIDCATS doctoral programme here at York, working with Jon Timmis, Mark Coles, and Kieran Alden on the simulation of Peyer’s Patch development.

Alistair Hendrickson

Alistair worked with Prof Jon Timmis and Dr Louis Rose for his MEng in Computer Systems and Electronic Engineering Masters project in the summer of 2014, on automated calibration of agent-based simulations.

Hayley Clissold

Hayley completed a rotation project in the lab in the Spring of 2014, working with Prof Jon Timmis, Dr Marika Kullberg, and Steph Dyson. She contributed to the development of our simulation of Crohn's disease.
 

Frances Drachenberg

Frances completed a rotation in YCIL (January - April 2015) as part of the CIDCATS doctoral programme at York, working with Mark Coles and Jon Timmis on simulating lymph node remodelling.

Sarah Rixham

Sarah completed a rotation project in the lab in the Spring of 2015, working with Prof Jon Timmis, Dr Marika Kullberg. She is contributing to the Crohn's disease simulation developed by Steph Dyson.