September 25 to 29 - Bremen, Germany
PIP Summer School:
Machine Learning and its Applications
About the Event
The summer school “Machine Learning and its Applications” will be held on September 25-29 at the University of Bremen, Bremen, Germany.
Our one-week summer school brings together students, researchers, and professionals from diverse backgrounds to explore cutting-edge topics in neuroscience, wearable sensor data analysis, and robotics. Not only will you have the opportunity to advance your skills in this exciting field, but you’ll also get to network and connect with like-minded individuals who are as enthusiastic about machine learning as you are.
During summer school, you’ll engage in six productive working hours each day, where you’ll delve into the fascinating world of machine learning. Our esteemed speakers, experts in their respective domains, will guide you through thought-provoking lectures and engaging hands-on lab sessions.
But it’s not all work and no play! Beyond the educational sessions, our summer school offers a diverse range of social events, providing the perfect platform for you to unwind, relax, and foster connections with your peers. From networking evenings to group activities, these events will create an environment that encourages collaboration and camaraderie among attendees.
Whether you are a student eager to expand your knowledge or a seasoned researcher looking to stay abreast of the latest advancements in machine learning, the Machine Learning and Applications Summer School at the University of Bremen is the ideal opportunity for you. Join us for an unforgettable week of intensive learning, inspiring discussions, and forging lifelong connections.
Speakers
Workshops and Talks
Deep Dive into Modern Machine Learning
In this presentation, we will introduce core concepts of modern machine learning, with a focus on different deep learning architectures (such as Convolutional Neural Networks, recurrent networks, and Transformers), as well as aspects of the machine learning life cycle, such as training, application, and evaluation of deep learning models – including approaches to quantify and tackle the challenge of generalization beyond the training data distribution.
Athletic Intelligence in Robotics
Achieving athletic intelligence in robots is one of the grand challenges of robotics and artificial intelligence. It is the pursuit to enable dynamic control of robots and produce motions which look very natural to their biological counterparts. The aim of this lecture is to provide a holistic view of athletic intelligence which combines three important insights.
Leveraging Behavioral and Neural Data with CEBRA
Mapping behavioral actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioral data increases, there is growing interest in modeling neural dynamics during adaptive behaviors to probe neural representations. In particular, neural latent embeddings can reveal underlying correlates of behavior, yet, we lack non-linear techniques that can explicitly and flexibly leverage joint behavior and neural data to uncover neural dynamics.
Supervised Machine Learning for Wearable Sensors
Nowadays, wearable sensors have become ubiquitous in our daily lives, from fitness trackers to smartwatches and health monitoring devices. However, analyzing the data and getting meaningful insights can be challenging. In this workshop, we will investigate the use of supervised machine learning methods, such as Support Vector Machine, Decision Trees, and Artificial Neural Networks, in understanding data from wearable sensors.
Timetable
Address:
Universität Bremen, Cognium,
Hochschulring 18
28359 Bremen
Email:
pipedu@uni-bremen.de
Register
Partners & Sponsors
Frequently Asked Question
September 25-29 at University Bremen in City Bremen, Germany.
The Machine Learning and Applications Summer School primarily targets postgraduate students with a background in machine learning or related fields who are eager to deepen their understanding and gain practical skills in this rapidly evolving field. However, we also welcome motivated individuals from diverse academic and professional backgrounds who have a strong interest in machine learning and its applications.
To register, please fill out the registration form available on our website and provide the required information. Registration is free of charge, however, we do not cover transport costs to and from events.
Yes, participants who fully attend the summer school and actively engage in the program and fulfill the requirements will receive a certificate of completion.
After the registration period ends, our selection committee will carefully review all applications. Accepted participants will be notified via email with further instructions in 1-2 weeks after the registration deadline.
Registration for the summer school is free of charge. However, attendees must pay for their accommodation, transportation, and meals themselves.
Organizing Committee
Saurabh Band (Comnet ET) – Alexander Jochim (ITP/Physics) – Katharina Korb (Neurophysics) – Jinming Sun (ITEM/ET) – Mahbod Nouri (ITP/Neurophysics)
Universität Bremen
Postgraduate International Programme
Otto-Hahn-Allee 1
28359 Bremen, Germany
Phone: 0049 421 218 62055
E-Mail: pipedu@uni-bremen.de
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