Primordial black holes as Dark Matter candidates: A Meme Presentation

• Antonio Junior Iovino (Università degli studi di Roma "La Sapienza")

One of the biggest unsolved mysteries in physics is to explain the nature of dark matter. Among the multiple candidates proposed in recent years, in this brief discussion, we will analyze the primordial black holes. We will discuss why the latter can explain dark matter and at the same time be linked to some experimental observations related to induced stochastic gravitational waves. All of this will be done with a new tool not yet widely used in physics, the use of memes.

Dicussion

Re-thinking radiotherapy treatment optimization: a Deep Learning approach

• Lorenzo Arsini

Radiotherapy (RT) is a vital tool in the fight against cancer. One of the primary challenges in radiotherapy is creating accurate and optimized treatment plans, which means finding the best way to shoot radiation to patients, killing the tumor cells, while avoiding collateral damages. Traditional methods are (of course!) extremely safe and reliable, but they are often time-consuming and they can be limited by the complexity of the optimization problem. That's where Deep Learning comes in. Deep learning models are fast, flexible and, most importantly, differentiable. That makes them perfect for… almost everything; but among the countless applications, they could also represent an opportunity to innovate RT treatment planning. In this seminar, we will explore such possibility, looking at both the current and future prospects of radiotherapy.

Discussion