Since commencing the PhD program in April 2017, I have worked on event-based vision, a new mode of acquiring visual data that presents a revolutionary paradigm shift in the way machines are able to percieve the world. As part of the PhD, I spent six months in Davide Scaramuzza's Robotics and Perception Group in Zurich, Switzerland, where I collaborated with world-class researchers to publish work in the IEEE International Conference on Computer Vision (ICCV). My work has also been published at CVPR and gained a best paper award at ACRA'17.

I also keep busy with several personal hardware and software projects, such as developing and building an egg engraving machine, a 3D printer/CNC router or working on my deep-learning based automated drosophila morphology software suite for life-sciences laboratories.

I have extensive skills in C++, Python and Java development and have plenty of experience with deep-learning libraries such as PyTorch and TensorFlow. I also have experience using CAD software such as SolidWorks and Autodesk and plenty of private experience in the workshop and with additive manufacturing, which serves me well during prototyping.