OpenMined
2020
2021
2022
2023
2024
Between 2020 and 2024, I led product design for OpenMined's privacy infrastructure platform PyGrid (now SyftBox). Our goal was to unlock cross-institutional research through privacy-enhancing technologies (PETs) and decentralized data networks. We used these technologies to advance progress in spaces like algorithmic transparency and collaborative computing.
Through this work I facilitated partner workshops, implemented community studies, guided product direction, and directed prototyping initiatives that visualized potential end-states for both PyGrid and PySyft—the open-source library PyGrid runs off of.
Conducting a Differential Privacy User Study
Syft 0.6
User Research
PETs Literacy
Leading a cross-disciplinary team of data scientists, privacy experts, ML engineers, and full-stack developers, I conducted a mixed-methods study to understand how non-technical users engaged with PySyft’s Differential Privacy features.
Mapping a Data Network for Research
Syft 0.7
Co-Mapping
Data Agency
Partnering with data consortia Dementias Platform UK (DPUK) and the U.S. Census Bureau’s XD Lab, I facilitated a series of workshops and mapping sessions to uncover the operational, social, and ethical challenges faced by modern day data stewards.
Prototyping a Differential Privacy Dashboard
Syft 0.7
Prototyping
PETs Literacy
Collaborating with privacy experts, data scientists, and full-stack developers, our team prototyped an interactive Differential Privacy Dashboard that promotes literacy through helping users simulate and see the trade-offs between data accuracy and privacy risk.
Designing for Secure Enclave Collaboration
Syft 0.8 - 0.9
Prototyping
AI Evaluation
Leading co-design sessions with OpenMined’s founder and head of engineering, I prototyped UX flows, object hierarchies, and interaction models that treated AI evaluation as a jointly governed process, not just a secure computation.
Mapping Access Friction in Academic Research
Syft 0.9
Interviewing
Encoding Context
Leading user research across a community outreach team, I investigated how procedural and institutional frictions, rather than data sensitivity alone, shape academic researchers’ ability to access data, collaborate, and adopt new research infrastructure.
Information-Centered Design in the Age of AI
Syft 0.8 - 0.9
Co-Mapping
Encoding Context
As design lead on OpenMined’s decentralized PET stack (PySyft, PyGrid, PyGrid Admin), I started treating information flows—not interfaces or isolated features—as my primary design material. This case study tracks the evolution of that practice through my activities as a product and design lead.
During my time at OpenMined we were able to establish pilots within the spaces of government, academia, NGO, and private industry. These pilots demonstrated a new path forward for privacy-preserving collaboration.
Twitter for Algorithmic Transparency
2021
Syft 0.7
Partnering with Twitter's ML Ethics, Transparency and Accountability (META) team, we exhibited how privacy-enhancing technologies (PETs) could be applied to problem spaces like algorithmic transparency, to foster learning and accountability of algorithmic impact without revealing IP sensitive data.
International Trade with the UN PET Lab
2022
Syft 0.7
Working with multiple national statistical offices, including Statistics Canada, the US Census Bureau, the UK Office for National Statistics, Statistics Netherlands, and ISTAT Italy, we developed privacy-preserving methods for analyzing trade data across countries.
The Christchurch Call Initiative on Algorithmic Outcomes
2024
Syft 0.8.0
Partnering with The Christchurch Call Initiative on Algorithmic Outcomes (CCIAO) we contributed to a pilot that demonstrated how privacy-enhancing technologies could be used to enable independent external researchers to study social media recommendation algorithms while protecting user privacy and platform security.
Secure Enclaves with AISI and Anthropic
2024
Syft 0.8.2
In partnership with staff from the UK AI Safety Institute (AISI) and Anthropic, we implemented a small-scale test using cloud infrastructure to evaluate an open-source model (provided by Anthropic as a proxy for their models) against an AISI-hosted CAMEL-bio dataset.
Reddit for Research
2024
Syft 0.9
In a new partnership, OpenMined will work closely with Reddit to develop privacy-preserving infrastructure that enable researchers to analyze Reddit data while maintaining strong privacy guarantees.