Curriculum Vitae

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Education

• PhD in Computer Science - University of Bern, 2017-present
  Topics: Analysis and design of self-supervised learning methods
  Advisor: Prof. Paolo Favaro

• MSc in Computer Science - University of Bern, 2017
  With specialization in Advanced Information Processing – summa cum laude
  Thesis Title: From Cartoons to Real Images: An Approach to Unsupervised Visual Representation Learning

• BSc in Computer Science - University of Bern, 2015
  With minors in Mathematics (60 ECTS) and Physics (30 ECTS) – magna cum laude
  Thesis Title: A Study of 3D Deformable Parts Models for Detection and Pose-Estimation

Professional Experience

• Junior Data Analyst - Philip Morris International, 2016
  Development of a Matlab tool for the automatic analysis of ciliary beating videos. The tool extracts key features such as tissue activity and main beating frequency with higher accuracy than prior methods.

• Software Engineering Intern - AdNovum, 2015
  I worked on a mobile payment app, implementing several parts of the iOS version in Objective-C.

Publications

Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation

S. Jenni, and P. Favaro. "Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation." In ACCV 2020.

Video Representation Learning by Recognizing Temporal Transformations

S. Jenni, G. Meishvili, and P. Favaro. "Video Representation Learning by Recognizing Temporal Transformations." In ECCV 2020.

Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics

S. Jenni, H. Jin, and P. Favaro. "Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics." In CVPR 2020.

Learning to Have an Ear for Face Super-Resolution

G.Meishvili, S. Jenni, and P. Favaro. "Learning to Have an Ear for Face Super-Resolution." In CVPR 2020.

EEG-based Outcome Prediction after Cardiac Arrest with Convolutional Neural Networks: Performance and Visualization of Discriminative Features

S. Jonas, A. Rossetti, M. Oddo, S. Jenni, P. Favaro and F. Zubler. "EEG-based Outcome Prediction after Cardiac Arrest with Convolutional Neural Networks: Performance and Visualization of Discriminative Features." In HBM 2019.

On Stabilizing Generative Adversarial Training with Noise

S. Jenni, and P. Favaro. "On Stabilizing Generative Adversarial Training with Noise." In CVPR 2019.

Deep Bilevel Learning

S. Jenni, and P. Favaro. "Deep Bilevel Learning." In ECCV 2018.

Self-Supervised Feature Learning by Learning to Spot Artifacts

S. Jenni, and P. Favaro. "Self-Supervised Feature Learning by Learning to Spot Artifacts." In CVPR 2018.

Awards

• Joint Alumni Association in Computer Science (JAACS):
  Award for the best Master Thesis in Computer Science (2017)

• P.A.I.S.S. Best Poster Award:
  Award for the poster on “Self-Supervised Feature Learning by Learning to Spot Artifacts” (2018)

• Paper Reviewing Recognitions:
  CVPR, outstanding reviewer (2019)
  ECCV, top reviewer (2020)

Skills

• Programming Languages:
  Python, MATLAB/Octave, Java, Objective-C, LaTeX

• Frameworks:
  Tensorflow, PyTorch, Caffe, SciPy, Numpy, OpenCV

• Languages:
  German (native), English (fluent), French

Teaching

Machine Learning

Advanced Topics in Machine Learning

Bern Winter School on Machine Learning