Systems research encompasses a vast variety of domains, problems, and solution approaches. While in some cases the research problem is well-defined, in other cases defining the problem itself can be a major task. Sometimes we arrive at a solution through a novel and elegant idea that strikes us suddenly, while at other times we solve the problem by putting together known ideas in interesting, counter-intuitive ways. While some solutions are designed, implemented, and evaluated in a matter of weeks, in other cases the whole process from conceptualization to realization can take multiple years from start to finish. In this talk, through problems I have worked on over the years, I will describe these various styles of systems research and how each can be enjoyable and rewarding in its own way.
Bio: Ranjita Bhagwan (BTech, IIT Kharagpur; MS and PhD, Univ California, San Diego) is a Senior Principal Researcher at Microsoft Research India. She has worked for more than a decade on applying machine learning to improve system reliability, security and performance. Recently, her work has focused on using data-driven approaches to improve cloud services and has led to severalpublications (including a best paper award at USENIX OSDI 2018), as well as several tools that are widely used by Microsoft's services. She is an ACM Distinguished Member and is the recipient of the 2020 ACM India Outstanding Contributions to Computing by a Woman Award.