Monthly Archives: March 2016

Talk by Errol Zalmijn (ASML)

You are all cordially invited to a presentation on Wednesday, March 9, at 11:00 in C3.163 by Errol Zalmijn, data analyst at ASML, on “Transfer entropy: an information signature of causation in ASML lithographic time series analysis“. 

Abstract: Considering the ASML lithography system to be a complex, distributed computing system that can be modeled as a network of driving and responding or driven observables i.e. cause-and-effect relationships, transfer entropy (Schreiber, 2000), an information-theoretic measure of time-directed information transfer between jointly dependent processes, enables detection of causal interactions between simultaneously observed time series from lithographic system data. Being a non-parametric measure, capable of identifying arbitrary linear and non-linear causal effects, transfer entropy can effectively gain a better understanding of the underlying system dynamics, a prerequisite for accurate diagnosis and prognosis, as well as structural design improvements.

Talk by Sarod Yatawatta (RUG)

You are all cordially invited to the next AMLab colloquium on Tuesday, March 8 at 16:00 in C4.174, where Sarod Yatawatta from the Kapteyn Astronomical Institute at the RUG will give a talk titled “Modern radio astronomy: challenges and opportunities”. Afterwards there are drinks and snacks!

Abstract: Radio astronomy enables us to probe the universe in unprecedented depth and resolution. Many new radio interferometric arrays are becoming operational and the largest one yet, the square kilometre array, is in the planning phase. The flow of data from these telescopes have not even reached their full capacity and nonetheless, manage to overwhelm our data processing capabilities. I will give a brief overview of radio interferometric data processing, starting from the raw data to the end results as images. The data deluge creates many challenges in terms of computational issues as well as meeting demanding scientific
requirements. On the other hand, this also creates many opportunities, in particular for the machine learning community, which I will highlight during this talk.