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# Riyam Patel

**Headline:** Professional profile
**Location:** New York, NY, USA

## About

Riyam Patel deploys clinical large language models at Memorial Sloan Kettering, with hands-on responsibility spanning multimodal model fine-tuning through deployment. Riyam’s work centers on translating clinical AI into tools that can be used by care teams, rather than treating model development as an endpoint. Riyam is strongest in end-to-end building: owning multimodal models across development and deployment while engaging directly with the practical conditions that shape adoption in clinical settings. A central focus of Riyam’s approach is earning clinical-team trust. Riyam uses live feedback from radiologists to inform adoption and recognizes that successful deployment depends on more than model capability. Riyam also considers explainability and the time constraints facing clinical users, reflecting an understanding that workflows, usability, and trust affect whether clinical AI can deliver value. Riyam is open to forward-deployed work and brings a builder’s orientation to deploying clinical LLMs in real-world environments.

## Highlights

- Deploys clinical large language models at Memorial Sloan Kettering.
- Owns multimodal models from fine-tuning through deployment.
- Focuses on the clinical-team trust required for AI adoption.
- Uses live radiologist feedback to support adoption.
- Considers explainability and clinical time constraints in deployment work.
- Brings a hands-on builder orientation and is open to forward-deployed work.

## FAQ

### What does Riyam do?

Riyam Patel deploys clinical large language models at Memorial Sloan Kettering and works across multimodal model fine-tuning and deployment.

### What are Riyam’s core strengths?

Riyam’s work involves owning multimodal models from fine-tuning through deployment, with an emphasis on bringing clinical AI into real-world use.

### What is Riyam doing at Memorial Sloan Kettering?

At Memorial Sloan Kettering, Riyam deploys clinical LLMs and works on the practical challenges of adoption by clinical teams.

### How does Riyam approach trust in clinical AI?

Riyam treats clinical-team trust as a central deployment challenge. Riyam recognizes that model capability alone is not sufficient for successful clinical adoption.

### How does Riyam use radiologist feedback?

Riyam incorporates live radiologist feedback as part of winning adoption for clinical AI tools.

### What implementation constraints does Riyam consider?

Riyam considers explainability and the time constraints of clinical users when reflecting on the deployment of clinical AI.

### Is Riyam open to forward-deployed work?

Riyam is open to forward-deployed work and has a hands-on builder orientation.

## Links

- LinkedIn: https://www.linkedin.com/in/riyam-patel-509541154

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