Name: PyLadies SF at AutoKitteh
Start: 2025-10-23T17:30:00-07:00
End: 2025-10-23T20:30:00-07:00

**Join us for an exciting evening of talks and networking sponsored by AutoKitteh!**

**Tentative Agenda:**

* **5:30 pm**: Networking
* **6:00 pm**: Sponsor Presentation and Workshop by AutoKitteh
* **6:45 pm**: Community Announcements
* **6:55 pm**: *Advanced Safeguarding for AI Inference Pipelines*, Aishwarya Ramasethu

Explore practical methods for integrating privacy-preserving techniques in AI applications. Learn about risks associated with large language models (LLMs) during inference and discover safeguards such as Differential Privacy, Federated Learning, and Homomorphic Encryption. This workshop will feature live demonstrations and hands- on exercises.

* **7:45 pm**: Lightning Talk (TBD)
* **8:00 pm**: Networking
* **8:30 pm**: Event ends

We are seeking additional speakers. Please DM us your talk proposals.

Alla Barbalat

PyLadies of San Francisco

Python Software Foundation Meetup Pro Network

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I’m Aishwarya, an AI Engineer at Prediction Guard. I work at the intersection of privacy, safety, and large language models (LLMs), with a focus on designing systems that are practical, grounded in real-world use, and safe.

My work spans building LLM pipelines with safety risks in mind, as well as fine-tuning open models for downstream tasks. Currently, I’m focused on evaluating LLMs across multiple dimensions for enterprise use cases—addressing pre-deployment risks, deployment-time issues, and online risk monitoring.

I’ve contributed to research in this space and am part of MLCommons, a community-driven AI safety initiative. I’ve also explored a range of privacy-preserving techniques, including differential privacy and federated learning.



Aishwarya Ramasethu

PyLadies SF at AutoKitteh

Artificial Intelligence

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