Rachel Cohen
I'm Rachel Cohen, an AI engineer and researcher focused on turning ideas into reliable real-time AI systems.
About
I’m Rachel Cohen, an AI engineer and researcher focused on turning ideas into reliable real-time AI systems. My work spans end-to-end pipelines for image enhancement in medical contexts and production-grade deployment that blends research with practical impact.
I enjoy collaborating across healthcare, software, and operations to simplify complex workflows, automate data processes, and deliver measurable improvements. I’m passionate about applying machine learning to solve real-world problems while fostering open communication with stakeholders and teams.
- 7 years' experience
- Joined February 2026
Languages
- EnglishFluent
- FrenchAdvanced
- JapaneseIntermediate
Industry experience
- Healthcare
- Life Sciences
- Software & Internet
- Education
- Professional Services
More experts in Montreal, Canada
Work experience· 4 roles
Developed end-to-end AI image enhancement pipelines for laparoscopic surgery, including data processing and generation, model training, performance evaluation, and real-time optimization, reducing visual obstructions from smoke and fluids by ~60%. Designed/modified GAN, ViT and Diffusion architectures for image restoration, added novel evaluation frameworks and architectural changes beyond hyperparameter tuning; optimized a sub-40 ms real-time inference pipeline and validated in vivo, enabling seamless integration into live surgical workflows.
Developed end-to-end AI image enhancement pipelines from proof of concepts to production; Leveraged LangChain with LLMs to automate generation of grant applications and business plans, streamline business operations, and accelerate funding opportunities; Created and deployed computer vision software to monitor system performance and detect anomalies.
Directed a cross-functional R&D team of 5 to develop AI applications using depth cameras for person and object tracking, enabling automated hygiene-compliance monitoring; built cloud-hosted CNN- and YOLO-based CV models for object localization and action recognition; created automated customer-facing reports and dashboards on AWS (Python, JavaScript, and C#), reducing manual workload by ~25% and improving client insights.
Education
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