PostDoc Positions
ellis 2023-01-31 PostDoc Saarbrücken
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Prof. Dr. Mario Fritz
Faculty
CISPA Helmholtz Center for Information Security
Professor
Saarland University
Fellow
European Laboratory for Learning and Intelligent Systems (ELLIS)
Google Scholar
Semantic Scholar
My group is working on Trustworthy Information Processing with a focus on the intersection of AI & Machine Learning with Security & Privacy.
Recent projects and initiatives related to trustworthy AI/ML, health, privacy:
- Coordinator and PI: European Lighthouse on Secure and Safe AI (ELSA)
- Leading Scientist: Helmholtz Medical Security, Privacy, and AI Research Center (HMSP)
- Coordinator and PI: PriSyn: Representative, synthetic health data with strong privacy guarantees
- Coordinator and PI: ImageTox: Automated image-based detection of early toxicity events in zebrafish larvae
- Coordinator and PI: Trustworthy Federated Data Analytics Project (TFDA)
- Coordinator and PI: Protecting Genetic Data with Synthetic Cohorts from Deep Generative Models (PRO-GENE-GEN)
- PI: Integrated Early Warning System for Local Recognition, Prevention, and Control for Epidemic Outbreaks (LOKI)
- Partner-PI: The German Human Genome-Phenome Archive (GHGA)
- Member of working group in “Forum Gesundheit” of BMBF: “AG Nutzbarmachung digitaler Daten für KI-Entwicklungen in der Gesundheitsforschung”
Recent work on DeepFake detecting, misinformation, attribution,and responsible disclosure:
- Usenix’23: UnGANable: Defending Against GAN-based Face Manipulation
- ArXiv’22: Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification Systems
- CVPR’22: Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
- ICLR’22: Responsible Disclosure of Generative Models Using Scalable Fingerprinting
- ICCV’21: Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data
- S&P’21: Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
- IJCAI’21: Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
- CVPR’21: Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
- ICCV’19: Attributing Fake Images to GANs: Learning and Analyzing GAN Fingerprints
Recent publications:
- Usenix’23: UnGANable: Defending Against GAN-based Face Manipulation
- NeurIPS’22: Private Set Generation with Discriminative Information
- ICML’22: ProgFed: Effective, Communication, and Computation Efficient Federated Learning by Progressive Training
- CVPR’22: Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
- CVPR’22: B-cos Networks: Alignment is All We Need for Interpretability
- CHIL’22: Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
- ICLR’22: Responsible Disclosure of Generative Models Using Scalable Fingerprinting
- ICLR’22: RelaxLoss: Defending Membership Inference Attacks without Losing Utility
- Usenix’22: ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
- PETS’22: Understanding Utility and Privacy of Demographic Data in Education Technology by Causal Analysis and Adversarial-Censoring
- IJCV’21: Semantic Bottlenecks: Quantifying and Improving Inspectability of Deep Representations
- CCS-W’21: Differential Privacy Defenses and Sampling Attacks for Membership Inference
- CCS-W’21: “What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
- PKDD-W’21: IReEn: Reverse-Engineering of Black-Box Functions via Iterative Neural Program Synthesis
- PKDD-W’21: SampleFix: Learning to Generate Functionally Diverse Fixes
- ICCV’21: Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data
- ICCV’21: Dual Contrastive Loss and Attention for GANs
- EXCLI’21: Privacy Considerations for Sharing Genomics Data
- IJCAI’21: Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis
- S&P’21: Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
- CVPR’21: Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANs
- CVPR’21: Convolutional Dynamic Alignment Networks for Interpretable Classifications
- CVPR’21: Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers
- CVPR-W’21: MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
- CVPR-W’21: InfoScrub: Towards Attribute Privacy by Targeted Obfuscation
- WACV’21: Future Moment Assessment for Action Query
News, talks, events:
- Talk at Deutscher EDV Gerichtstag
- Talk at AI, Neuroscience and Hardware: From Neural to Artificial Systems and Back Again
- Scientific Advisory Board: Bosch AIShield
- Steering Board: Helmholtz.AI
- Recent program committees: ICML’21, NeurIPS’21, S&P’22, EuroS&P’22, CVPR’22 (AC); CCS’22
- Runner-up Inria/CNIL Privacy Protection Prize 2020
S&P’20 paper: “Automatically Detecting Bystanders in Photos to Reduce Privacy Risks” - Co-Organizers of ICLR’21 Workshop on “Synthetic Data Generation – Quality, Privacy, Bias”
- Co-Organizers of CVPR’21 Workshop on “QuoVadis: Interdisciplinary, Socio-Technical Workshop on the Future of Computer Vision and Pattern Recognition (QuoVadis-CVPR)”
- Co-Organizers of CVPR’21 Workshop on “Causality in Vision”
- Founding member of Saarbrücken Artificial Intelligence & Machine Learning (SAM) unit of the European Laboratory of Learning and Intelligent Systems (ELLIS)
- Lecturer at Digital CISPA Summer School 2020
- Co-Organizer of Third International Workshop on The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS) at ECCV 2020
- Co-Organizer: 4. ACM Symposium on Computer Science in Cars: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles CSCS’20
- Keynote at Workshop Machine Learning for Cybersecurity, ECMLPKDD’19
- Talk at Cyber Defense Campus (CYD) Conference on Artificial Intelligence in Defence and Security
- Co-Organizer of Second International Workshop on The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CV-COPS) at CVPR 2019
- Co-Organizer: 3. ACM Symposium on Computer Science in Cars: Future Challenges in Artificial Intelligence & Security for Autonomous Vehicles CSCS’19
- Leading scientist at new Helmholtz Medical Security and Privacy Research Center
- Member of ACM Technical Policy Committee Europe
- Mateusz Malinowski received the DAGM MVTec dissertation award as well as the Dr.-Eduard-Martin award for his PhD
- Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)