Mihai Maruseac
The year around now
Talks in the past 12 months and announced talks ahead, one row per conference, January to December. Hover a mark for the talk.
Appearances by year
- AI By the Bay
- JupyterCon
- PyTorch Conference
- SciPy Conference (Scientific Computing with Python)
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Nov 17, 2025 | AI By the Bay 2025 | AI By the Bay | speaker | Taming the Wild West of ML: Practical Model Signing with Sigstore on Kaggle as Google | Video |
| Nov 3, 2025 | JupyterCon 2025 | JupyterCon | speaker | Training Tamper-Proof AI models on Notebooks as OpenAI | Slides |
| Oct 22, 2025 | PyTorch Conference 2025 | PyTorch Conference | speaker | From Model To Trust: Building Upon Tamper-proof ML Metadata Records as OpenAI The integrity and provenance of machine learning models are critical for building trustworthy AI systems. While cryptographic signing protects many digital…Show lessThe integrity and provenance of machine learning models are critical for building trustworthy AI systems. While cryptographic signing protects many digital assets, a standardized approach for verifying model origins and ensuring they haven't been tampered with is still missing. We are addressing... | |
| Oct 22, 2025 | PyTorch Conference 2025 | PyTorch Conference | poster | Poster Presentations: Responsible AI & Community as OpenAI From Model To Trust: Building Upon Tamper-proof ML Metadata Records - Mihai Maruseac, Google Breaking Barriers: The PyTorch Multi-Cloud CI Working Group -…Show lessFrom Model To Trust: Building Upon Tamper-proof ML Metadata Records - Mihai Maruseac, Google Breaking Barriers: The PyTorch Multi-Cloud CI Working Group - Andrea Frittoli, IBM PyTorch in China: Community Growth, Localization, and Interaction - Zesheng Zong, Huawei The Hidden Heroes: How Non-Code... | |
| Jul 7, 2025 | SciPy 2025 | SciPy Conference (Scientific Computing with Python) | speaker | From Model to Trust: Building upon tamper-proof ML metadata records as Google The increasing prevalence of AI models necessitates robust mechanisms to ensure their trustworthiness. This talk introduces a standardized, PKI-agnostic…Show lessThe increasing prevalence of AI models necessitates robust mechanisms to ensure their trustworthiness. This talk introduces a standardized, PKI-agnostic approach to verifying the origins and integrity of machine learning models, as built by the OpenSSF Model Signing project. | |
| Nov 13, 2023 | Scale By the Bay 2023 | AI By the Bay | speaker | Model transparency for AI/ML security as Google | Video |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Lahari Chowtoori | 2 | 1 | 2025 |
| Miaolai Zhou | 2 | 1 | 2025 |
| Alex Monahan | 2 | — | 2025 |
| Angus Hollands | 2 | — | 2025 |
| Baruch Sadogursky | 2 | — | 2025 |
| C.A.M. Gerlach | 2 | — | 2025 |
| Chia-Wei Chen | 2 | — | 2025 |
| Chris Holdgraf | 2 | — | 2025 |
| Debarshi Datta | 2 | — | 2025 |
| Franklin Koch | 2 | — | 2025 |
| Julien Le Dem | 2 | — | 2025 |
| Kerim Satirli | 2 | — | 2025 |
| Mary Grygleski | 2 | — | 2025 |
| Nikita Shulga | 2 | — | 2025 |
| Rowan Cockett | 2 | — | 2025 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.