Reflexion - Learning Launch

Challenge

I am a first year PhD student and my challenge is to successfully complete my thesis defense at the end of three years of work. This defense must show the realization of an applied project allowing to advance the research in the field of Artificial Intelligence applied to connected objects (Internet of Things i.e “IoT”). Previously, I worked 3 years in the industry. According to me, many relevant concepts can be applied in academic research. I have two thesis supervisors, coming from two different backgrounds (Applied Mathematics and Computer Networks). My supervisors are the equivalent of my managers and my clients, they have both roles. In addition to my defense, I have to realize a publication (at least) and in a field related to Artificial Intelligence and “IoT” accompanied by a real application (a prototype). My research is not fundamental (i.e theoretical), but applied.

Selection

Coming from the industrial world, in the field of Artificial Intelligence, I often had to used prototype, visualization and other "Design Thinking" tools for clients. I apply the concept of "Learning Launch" in the academic world because I find it relevant to applied research. Broadly speaking, the learning launch is an experiment meant to quickly test an idea and prototype.

Application

In the applied research we need to quickly see if an idea can be realizable and useful in a practical world. Reflection is done in groups but application and realization is done lonely. First, we discuss the idea, the possibility and how it can improve some aspect of the world of connected objects. This exploratory phase is done in a team through the laboratory, through research in the scientific literature but also around discussion with my thesis supervisors (i.e my clients and partners). The discussion in the team is every two weeks and the discussion with my thesis supervisors every week.

The first phase lasts maximum 1 month in order to avoid long and theoretical debates. After this part, I set a short deadline, in agreement with my thesis supervisors (i.e. managers and clients) to build a first prototype which is the realization in practice of the hypothesis and deduction made in the previous part. This is a very iterative process where we focus on one big idea and try to put it into practice. Every week, a review is done with my thesis supervisor (i.e. managers and clients) to see if the schedule is respected and if the research and the result are valid and consistent with the hypothesis made with the theory.

Insight

The use of the “Learning Lauch” tools allows us to quickly realize a prototype. Thus, each researcher according to his specialty (Artificial Intelligence or Connected Object / Computer network) will be able to quickly apprehend the objective and the interest or the drawbacks of the tool by using it quickly in a quasi-real situation. The development of a rapid tool allows us

to cross the theoretical barriers and to allow each specialty to quickly apprehend its relevance. The regular feedback from users allows me to determine the best research directions, to "fail early" and focus my limited time on functional ideas. The objective is very similar to industry. However, the objective here is not to produce a product version that can be delivered to a client but to the research community in what is called "reproducible research". In other words, to show through a product that the research is part of a practical framework and that it can easily be reused.

Approach

Due to my practical research and my experience in industry we are not a lot to practice this "Learning Launch". Nevertheless, after having integrated this concept with my thesis supervisors (i.e my managers and clients) I am much more relevant in my research and quickly locate points of interest for the scientific community. I am much faster at making applied and relevant publications for the industrial world. Thanks to this course I am also able to formalize this concept better and apply it more efficiently.

