Dr Jano van Hemert has a PhD in Mathematics and Physical Sciences from Leiden University, The Netherlands (2002). He is a Senior Research Manager and the Academic Liaison at Optos—an innovative retinal imaging company with a vision to be recognised as the leading provider of retinal diagnostics. Since 2010, he is an Honorary Fellow of the University of Edinburgh. Since 2011, he is a member of The Young Academy of The Royal Society of Edinburgh. In 2013, he was elevated to Senior Member of the IEEE.
From 2007 until 2010 he led the research of the UK National e-Science Centre, supported by an EPSRC Platform Grant. His then personal research group in the University of Edinburgh's School of Informatics, Edinburgh Data-Intensive Research, comprised 7 post-doctoral researchers and 7 PhD students, who were all funded through national and international projects, with collaborations in seismology, brain imaging, developmental and evolutionary biology, fire safety engineering, nano-engineering, urban water management, molecular medicine and neuro-informatics.
van Hemert has held research positions at the Leiden University (NL), the Vienna University of Technology (AT) and the National Research Institute for Mathematics and Computer Science (NL). In 2004, he was awarded the Talented Young Researcher Fellowship by the Netherlands Organization for Scientific Research. In 2009, he was recognised as a promising young research leader with a Scottish Crucicible. All of his projects are interdisciplinary collaborations and many of his research projects have included partners from industry. From 2005 until 2011 he was a visiting researcher at the Human Genetics Unit in Edinburgh of the United Kingdom's Medical Research Council.
He was the programme chair of five international conferences and workshops in computer science. In 2008, he has published a book on Recent Advances in Evolutionary Computation for Combinatorial Optimization as part of Springer's Studies in Computational Intelligence series. In 2013, he published a book "The DATA Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business."
His research output includes over one hundred published papers, patents and software on image processing, optimisation, constraint satisfaction, evolutionary computation, data mining, scheduling, problem difficulty, dynamic optimisation, distributed computing, web portals, experiment design, and e-Science and retinal imaging applications.
M. Sagong, J. van Hemert, L.C. Olmos de Koo, C. Barnett, and S.R. Sadda. Assessment of accuracy
and precision of quantification of ultra-widefield images. Ophthalmology, 122(4), 2015.
D.E. Croft, J. van Hemert, C.C. Wykoff, D. Clifton, M. Verhoek, A. Fleming, and D.M. Brown. Precise
montaging and metric quantification of retinal surface area from ultra-widefield fundus photography
and fluorescein angiography. Ophthalmic Surg Lasers Imaging Retina, 45(4):312–317, Jul 2014.
J.I. van Hemert, J. Koetsier, L. Torterolo, I. Porro, M. Melato, R. Barbera. Generating web-based user interfaces for computational science, In Concurrency and Computation: Practice and Experience, Wiley, volume 23, 2011.
L. Han, J.I. van Hemert, R.A. Baldock. Automatically Identifying and Annotating Mouse Embryo Gene Expression Patterns, In Bioinformatics, volume 27, 2011.
R.R. Kitchen, V.S. Sabine, A.H. Sims, E.J. Macaskill, L. Renshaw, J.S. Thomas, J.I. van Hemert, J.M. Dixon and J.M.S. Bartlett. Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles, 11(134), 2010.
D. Rodriguez Gonzalez, T. Carpenter, J.I. van Hemert, and J. Wardlaw. An open source toolkit for medical imaging de-identification. European Radiology, 20(8):1896–1904, 2010.
J. Armstrong and J. van Hemert. Towards a virtual fly brain. Philosophical Transactions A, 367(1896):2387–2397, 2009.
J.I. van Hemert. Evolving combinatorial problem instances that are difficult to solve. Evolutionary Computation, 14(4):433–462, 2006.
B.G.W. Craenen, A.E. Eiben, and J.I. van Hemert. Comparing evolutionary algorithms on binary constraint satisfaction problems. IEEE Transactions on Evolutionary Computation, 7(5):424–444, 2003.
I. Juhos and J.I. van Hemert. Increasing the efficiency of graph colouring algorithms with a representation based on vector operations. Journal of Software, 1(2):24–33, 2006.
J.I. van Hemert and T. Bäck. Robust parameter settings for variation operators by measuring the resampling ratio: A study on binary constraint satisfaction problems. Journal of Heuristics, 10(6):629–640, 2004.