Kosmas Deligkaris, PhD
Deep Learning and Machine Vision Engineer
My current work focuses on posture tracking and 3D scene understanding for the analysis of animal behaviour. I am also interested in evolutionary algorithms and their application in optimization of neural network architectures. I am a strong supporter of writing reproducible and extensible software in academia/research, as well as the utilization of agile tools for project and team management. Have a look around, and if anything comes to your mind, feel free to get in touch through the form at the bottom.
Developing software is perhaps the cornerstone of my work. I have worked with all kinds of different programming languages, from assembly language in microcontrollers to Fortran, and later on to Python and Java. I like developing in Java, with all its rules and patterns. For deep learning applications though, I mostly work with Python due to the extensive ecosystem and easy scripting capabilities.
I have been a long user of agile tools, such as issue trackers, project managers, and knowledge repositories. In several of my previous organizations I also took the lead in establishing tools and workflows to enhance collaboration and transparency. I am mostly familiar with the Atlassian ecosystem, where I am certified as a Jira Cloud Project administrator.
Deligkaris K, Bullmann T and Frey U (2016)
Extracellularly Recorded Somatic and Neuritic Signal Shapes and Classification Algorithms for High-Density Microelectrode Array Electrophysiology. Front. Neurosci. 10:421.
Bullmann T, Radivojevic M, Huber ST, Deligkaris K, Hierlemann A and Frey U (2019)
Large-Scale Mapping of Axonal Arbors Using High-Density Microelectrode Arrays. Front. Cell. Neurosci. 13:404.
K. V. Deligkaris, Z. D. Zaharis, D. G. Kampitaki, S. K. Goudos, I. T. Rekanos and M. N. Spasos (2009)
Thinned Planar Array Design Using Boolean PSO With Velocity Mutation. IEEE Transactions on Magnetics, vol. 45, no. 3, pp. 1490-1493.