Watching fish think, individualizing radiation therapies, and examining patients with dark field X-ray imaging – these were just some of the topics of the Bioengineering Autumn School 2022 in Herrsching am Ammersee. From October 26 to 28, doctoral students from the Technical University of Munich (TUM) and the Ludwig-Maximilians-Universität (LMU) met with renowned researchers from science and industry to exchange ideas and network in lectures, poster sessions and workshops.
The participants of the Autumn School conduct intensive research on a wide variety of bioengineering topics to prevent, alleviate and treat diseases through new developments and findings. Chen Wang is working with active microgels to investigate the mechano-biology of cells. Aleksandra Milojkovic and Prachi Kumari are studying magnetoelectric nanoparticles to develop wireless neural implants that could be used, for example, to alleviate symptoms of Parkinson's disease.
"The variety of topics was really incredible. During the poster session, I was able to gain many new insights into different projects. Thus, it was great that the poster session was scheduled on the first day of the event and there was still enough time on the other days to tie in with the topics and deepen the discussions," says Jonathan Rapp, who investigates magnetic stimulation of nerves in his doctoral project.
In addition to networking with peers, the three-day event in picturesque Herrsching am Ammersee also offered the doctoral candidates numerous opportunities to get inspiration from renowned researchers and to learn from the experiences of industrial partners.
"I am working on improving the image quality of low-radiation CBCT images and enabling the dose calculation for radiation therapy for prostate cancer using deep learning. Therefore, the lectures on optimized treatment planning and machine learning in imaging and diagnostics were of course particularly interesting for me. But I was also very fascinated by the lecture on sensorimotor control, i.e. how our brain plans and performs movements," says Ivy Chan, summarizing the topics of some of the lectures.
"Exchange and networking are central aspects of the Bioengineering Autumn School," emphasizes Franz Pfeiffer, Professor of Biomedical Physics and Director of MIBE as well as Vice Speaker of GRK2274. "We aim to give doctoral students insights into the diverse areas of biomedical engineering in order to provide impulses for synergies and cooperation. The lively exchange during the entire three days and the feedback from the participants shows how well this approach is accepted. It was a truly successful event."
List of talks at the Bioengineering Autumn School 2022:
Spectral Detector CT
PD Dr. Nils Große Hokamp (University Hospital of Cologne)
Translation of X-ray Dark-Field Imaging from Bench to Bedside
Dr. Thomas Köhler (Philips Research Laboratories)
Image-guided Interventions and Robotics
Prof. Dr. Andreas Melzer (Innovation Center Computer Assisted Surgery (ICCAS), Leipzig University)
Sensorimotor control in a small vertebrate
Prof. Dr. Ruben Portugues (Technical University of Munich)
Laser-Plasma Based Particle Sources – Global Progress and Activities at the Centre for Advanced Laser Applications
Prof. Dr. Jörg Schreiber (Ludwig-Maximilians-Universität Munich)
Brain Tumor Resection and the need for Intra-Operative Imaging
Wolfgang Steinle (Brainlab AG)
Biologically optimised treatment planning
Prof. Dr. Iuliana Toma-Dasu (Stockholm University and Karolinska Institute)
Combining Visual Computing with Machine Learning for Advancing Medical Diagnosis and Image-guided Interventions
Dr. Wolfgang Wein (ImFusion GmbH)
The Bioengineering Autumn School takes place annually and is aimed at doctoral candidates from various disciplines who conduct research in the broad field of biomedical engineering.
Since 2019, the Autumn School has been offered jointly by the MIBE and the Research Training Group GRK2274 – Advanced Medical Physics in Image-Guided Cancer Therapy angeboten.
The following subpage provides an overview of MIBE's offers for doctoral candidates.
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