Tübingen Science Bridge - Connecting Brazil Germany
Tübingen Science Bridge: “Articial Inteligence and Machine Learning”
Date and time
Location
Online
About this event
Seeking for internationalization of Science and Research and new impulses for cooperation between the University of Tübingen and partner universities in Brazil, Baden-Württembergisches Brasilien- und Lateinamerika-Zentrum at the Universität Tübingen launched the Program Tübingen Science Bridge - Connecting Brazil Germany, in April 2022. The program's goal is to promote and expand science, in addition intensify research cooperation through a sequence of lectures, online.
Scientists from several partner institutions will present their latest research data, promoting an integrated and constructive environment for scientific interaction and also contributing global knowledge.
The webinar planned for October, which takes place on October 5 at 11:30 am BRT (04:30 pm MEZ), will focus on the area of Artificial Intelligence (AI) and has the participation of Prof. Dr. Teresa B. Ludermir, Informatics Center at the Federal University of Pernambuco - UFPE.
The webinar will be held in English on the ZOOM platform in order to allow discussion and interaction.
Lecture Briefing: Machine Learning has shown extraordinary advances in recent years and is currently used to solve numerous technological and economic problems. AutoML is a subfield of machine learning which aims to automate the training & tuning of machine learning models.In this presentation it will be talked about Machine Learning applications in our daily lives and AutoML.
Short bio: Teresa B. Ludermir received the Ph.D. degree in Neural Networks in 1990 from Imperial College London. She is a Professor and head of the Artificial Intelligence Group at Centro de Informatica, Universidade Federal de Pernambuco, Brazil. She has published over 400 articles in scientific journals and conferences and three books in Neural Networks (in Portuguese). Her research interests include weightless Neural Networks, hybrid neural systems and automated machine learning (AutoML).