Florian Bernard

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Assistant Professor at University of Bonn

contact: f.bernardpi::gmail::com

News

10/2021: I joined the Department of Visual Computing at University of Bonn as Assistant Professor and head of the ‘Learning and Optimisation for Visual Computing’ group.

09/2021: Our paper Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation has been accepted at NeurIPS 2021.

05/2021: I received a CVPR 2021 Outstanding Reviewer Award.

03/2021: Two submissions were accepted and selected for oral presentation at CVPR 2021:
o Isometric Multi-Shape Matching
o i3DMM: Deep Implicit 3D Morphable Model of Human Heads

10/2020: Two ACM Transactions on Graphics (TOG) papers, to be presented at SIGGRAPH Asia, are now available:
o PIE: Portrait Image Embedding for Semantic Control
o RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video

04/2020: I joined the Chair of Computer Vision & Artificial Intelligence at TU Munich as Visiting Professor.

News archive

Useful resources

Information for prospective students

If you want to work with me feel free to directly get in touch. Please be specific and concisely explain your background and interests, and also don’t forget to mention why you are particular interested in working with me. Generic and unspecific applications that fail in explaining so will not be answered.

Bachelor’s/Master’s thesis and guided research projects

I am offering various research-oriented topics for student projects. Most commonly, students explain their interests and provide some information about their background (CV, academic transcripts, self-assessement), and then I offer a project if there is a suitable topic available. I do not supervise external theses, but I am open to discussing own ideas of students for projects - before you propose a project idea, please check whether it is relevant to my research interests.

PhD students

We are looking for highly-motivated PhD students that are passionate about research and want to push the boundaries of current visual computing solutions. Successful applicants typically have a strong background and solid working knowledge in basic mathematics (linear algebra, analysis), and some experience in at least one of the following areas:

Self-assessment

It is highly recommended that in your application you provide a short self-assessment in which you assign grades from 1-5 (1 means best) to indicate your background in relevant topics. In case you get selected for an interview it will be based on your self-assessment.

Since I am not familiar with all international grading systems it is recommended that international applicants provide a short summary on the ranking of their university (e.g. ‘Top 10% in India’), and also rank their total grade (e.g. ‘Top 20% of students across all computer science graduates at the university’).

You can use the following template (feel free to leave topics with no experience blank).

linear algebra: 
analysis & calculus: 
algorithms & data structures:
computer vision: 
computer graphics: 
geometry processing/shape analysis: 
mathematical optimisation: 
deep learning: 

ranking of my university:
ranking of my performance:

Tips for current students

When writing a report/thesis/paper, please take into account the following points: