ActiveMatter and Scholarship Opportunities: A Day of Learning at Ozyeğin University

On January 4, 2024, engineering students at Ozyeğin University were treated to an insightful session on active matter, exploring its journey from theoretical concepts to real-world applications. This event, led by Alireza Khoshzaban, was an eye-opener for students, demonstrating how active matter plays a key role in modern engineering innovations.
During the session at Ozyegin University, the theory and history of active matter were briefly covered, emphasizing its evolution from early physics concepts to modern engineering marvels. This discussion connected theoretical foundations to practical applications in soft robotics, biomedical devices, and smart materials, showcasing how significant active matter has impacted contemporary engineering solutions.

Round Table Discussion on: Machine Learning

The third round table session of the experimental training was about machine learning and its role in science, in particular physics and active matter. The panelists invited to the discussion were Carlo Manzo from Vic University, Benjamin Midtvedt and Saga Helgadottir from Gothenburg University, Onofrio Maragò and Alessandro Magazzù from CNR ICPF-Messina. The discussion was organized and lead by Jesus M. A. Dominguez, Davide Breoni, Liam Ruske, Chun-Jen Chen and Alireza Khoshzaban, who are students attending the training.

The discussion touched topics like the applications of machine learning in fields like optics, biophysics, medical research, the potentialities and the reliability of the method. Questions on when a machine learning approach is advisable and how cautious one must be when applying machine learning were also addressed. Current important logical and practical aspects of the method were also discussed, together with the need of testing machine learning applications against more classical ones. The panelists also stated the importance of reliably checking the results obtained to avoid biases that can lead to false conclusions.

After one hour of fruitful discussion we gained a broader perspective and a deeper understanding of machine learning.