So right now I'm a Senior Researcher, Software Engineer at Microsoft. I did a few graduate school degrees, so I have a master's in computer engineering and a PhD in computer engineering as well. I think the main reason how I get where I am it's basically on networking. A lot was depending on who I was surrounded by, and I think that's very much important. So here's to give an example my PhD adviser was very well known in the industry and academia. So for me, it was very important to go to lab research for my PhD so I can launder to a good position. Once I was done with my PhD, that happened. I did a few internships when I was a PhD student. I did one for a year at Apple and two more at another company in the Boston area. I did my PhD at the Eastern University in Boston, and then once I finished, I got a job at the research scientist at Intel. I joined Intel. I'm located right now in the Silicon Valley area. And that was a really good opportunity for me to learn more about the industry, how you can do apply research in the industry. And then once I was there, I learned more about what you can do it in more sophisticated way for the industry. Before I was very academic-oriented. And then Microsoft came along and I thought that was a nice next opportunity for me, for my career growth, and then that is how I ended up here now with Microsoft.

Yeah, so that's very flexible in my case. I spent a lot of time a close collaboration with different teams. So I have a good chunk of meetings. I have at least 30% 40% of meetings. You know, remotely. I don't have to be locally in the building and plus my team is actually located in Redmond in Washington. And I'm here in Sunnyvale in California so that can be from home. That is not necessary for me to be in the office. I'd rather be at the office of being there. For me, it's a much nicer environment, and then the rest of the time will be divided. I do 10-20% of research in terms, of checking data to review, seeing what is the state of the art, how we can apply that to our current cases in the current problems. And the rest of the time, I think will be applied to actually do to the thinking, the development, and experiments. So I think there will be three major chunks like one will be meetings, another one will be stay updated with the team if they are, and the last one will be actually development.

My preference is entirely computing and high-performance computing and for that, given that you're trying to achieve high-performance execution, it more adores cluster execution. So it's more in the terminal base access into clusters and servers. So my preference for that regard will be a specific tool that will access to terminals. So command line execution is my favorite. It has much flexibility and elasticity for me to navigate through the things that I want to do. In terms of Frameworks, I'm heavily working on the Meteor right now, so we use the Meteor frameworks. We don't have a preference whatsoever. A C++, of course, for high performance. I developed different quality programming algorithms so that will be depending on what kind of architecture we're targeting. So far CUDA is the one which is taking the market, so CUDA might be a good option. But honestly as far as it's a terminal and common line. I think that's my preference. And you know, you can add on top of that Git and all of those classic tools, but I think that will be very close to my expertise.