I am a PhD student at the Max Planck Institute for Informatics where I work on Computer Vision, Machine Learning, and Privacy/Security. My advisors are Mario Fritz and Professor Bernt Schiele. Previously, I graduated with a Master's degree in CS from ETH Zürich.
I'm broadly interested in computer vision, machine learning, privacy, and security. Currently, my research focuses on the "double-edged" sword of ML. While I study ML models to understand and control privacy in data, I also address how these very ML models are susceptible to adversarial attacks.
Gradient model updates in federated learning encodes non-IIDness of participating clients, raising linkability concerns.
Connecting Pixels to Privacy and Utility: Automatic Redaction of Private
Information in Images
Tribhuvanesh Orekondy, Mario Fritz, Bernt Schiele
CVPR, 2018 (Spotlight)
paper  ·  poster  ·  project page  ·  video  ·  bibtex
Automatic method to identify and redact a broad range of private information spanning multiple modalities in visual content.
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images
Tribhuvanesh Orekondy, Bernt Schiele, Mario Fritz
paper  ·  poster  ·  extended abstract (VSM@ICCV)  ·  project page  ·  bibtex
An approach to understand and predict a wide spectrum of privacy risks in images.
HADES: Hierarchical Approximate Decoding for Structured Prediction
Tribhuvanesh Orekondy (under supervision of Martin Jaggi, Aurelien Lucchi, Thomas Hoffman )
Master Thesis, 2016
paper  ·  project page  ·  bibtex
A fast structured output learning algorithm, which works by approximately decoding oracles to various extents.
- PC member: CVPR '19, CV-COPS '19
- Teaching Assistant: Machine Learning in Cyber Security, 2018
- Student supervision: Shadi Rahimian (MSc., University of Saarland), Jonas Klesen (BSc., University of Saarland)