What are the best ways to communicate your algorithm research findings to a diverse audience?

Use evidence that best suits the cognitive style of your listener. In the book People's Styles at Work the authors note four cognitive types: Analyticals, Drivers, Expressives and Amiables. Analyticals find data and analysis convincing, expressives find the uniqueness of the solution motivating, Drivers tend to look for the practical implementation of the ideas and Amiables like to know that "everyone else does it this way". So, as much as possible try to include evidence for all four types in your audience preparation. Especially ask yourself if the leader is a driver, expressive, etc.

'Know your audience' is a truism regardless of what you are presenting, or who you are presenting to. Beyond the usual advice of 'don't use jargon', you must also learn the cultural norms of the group that you are presenting to. For some audiences and venues, the norm is to refer to oneself in the third person, while for others you must use the first or second person. In addition, research sometimes goes through fashionable phases, which means that while your ideas could be published easily in the past (or maybe the future), it is more difficult to publish it now. Research your audience to learn the best method of 'marketing' your ideas to them; once your audience is hooked, they will ask you for more, but first they need to be hooked!

Since algorithms are dynamic processes, animations can be very helpful for making the flow of the algorithm clear. They don't need to be very sophisticated. On the contrary, too many bells and whistles, such as 3D rendering or textures, can be distracting rather than illuminating. A little 2D animation with simple clip art renderings can go a long way towards making the algorithm intuitive to grasp.

Cuando he tenido que explicar algún concepto sobre Machine Learning siempre busco un esquema que contenga imágenes que describan es proceso de la manera más simple posible, de esta manera llegaremos a la audiencia que no tiene conocimientos previos del tema y a la que si los tiene.

You must be extremely careful when using visual aids when talking to non-technical audiences. I have taught students where I showed a data structure as a directed graph. Implementing this would involve heap allocations and pointers. The issue is that some students wanted to store arbitrary data within the nodes (rather than pointers to heap-allocated memory). I explained the issues that this would cause (i.e., the need to reserve sufficient memory in every node), which confused some of the students. It turned out that they didn't understand how pointers and memory worked, so they assumed that each node could be 'moved around to make space' as needed, all because they could see it was possible on the white board. Caveat magister!

Communicating complex algorithm research to general audiences requires translating technical concepts into plain language. Avoid excessive jargon and focus on conveying key ideas clearly. Use analogies and examples people relate to, like following recipes or navigating traffic. This makes abstract notions more concrete. Emphasize real-world applications that improve lives. Connect your research to solving problems in medicine, technology, business, etc. This demonstrates relevance. Use graphics like charts and diagrams to visualize complex processes and information. Visuals are more digestible than dense text.

Además de participar, a?adiría estar abierto a las posibles colaboraciones que pudieran surgir del interés de la audiencia. Ya sea en el momento o en el futuro, proporcionando los datos de contacto y las referencias del trabajo.

In my experience as a researcher and professor, I believe that the best way to communicate findings from algorithmic research to a diverse audience is to place yourself in the position of someone with little or no knowledge about the topic. When you adopt this perspective, it becomes essential to craft a presentation or explanation in the simplest and most direct manner to reach the audience effectively. I consistently aim to articulate concepts as if I were explaining them to a child. By doing so, clarity, conciseness, and maintaining interest become priorities without losing focus on conveying what truly matters.

Initiating discussions on any given topic should commence with foundational concepts and progressively advance in complexity. It is prudent to avoid presuming prior knowledge among the audience regarding essential details. In cases where in-depth explanations may not be feasible, it is consistently advisable to provide references to fundamental principles. This approach not only accommodates individuals encountering the information for the first time but also serves as a valuable refresher for those seeking to reinforce their understanding.