As I wind down a rewarding career at Brookhaven National Laboratory where for more than thirty years I participated in the RHIC program to form and study extended Quantum Chromodynamics systems.

Now I’m ready to embark in a new and challenging occupation; my attention is now focused in the field of Data Science.

As a physicist I did participate in many projects, among them:
● Thirty years of work in physics research with a span that extends from detector design and construction to data analysis and publications.
●I have engaged and pursued different research projects leading to publications well recognized in our community.
● I have built, installed and extracted physics results from key detectors in the BRAHMS experiment at RHIC.

I was the principal author of the BRAHMS d+Au as function of rapidity and centrality which was quoted as the first evidence of the onset of saturation in nuclear systems at RHIC energy. That paper has accumulated 405 citations to this date.

I have been familiarizing myself with most of the tools of Machine Learning and I find them exhilaratingly simple in their foundation, and yet capable of tackling complicated problems. The linear algebra used to process the data brings memories of my student years working with the matrix formalism of Quantum Mechanics.

I'm currently enrolled in the Deep Learning course at Udacity where we use deep neural networks in the Google TensorFlow environment.