Elsa Bismuth
AI Engineer & Community Builder, Bridging Silicon Valley and Europe
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Stanford, California
Paris, France
Joined March 2026
Network
3.6K connectionsCFMCSE
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Summary
Elsa Bismuth is a dedicated community builder with a focus on connecting innovators across continents. She founded 'The FOMO Club' to democratize access to opportunities and foster meaningful relationships, bridging Silicon Valley with global talent. Her work emphasizes a kindness-first culture and leveraging technology for high-impact connections. join-fomo
Elsa possesses a strong background in AI and its applications, particularly in healthcare. Her academic pursuits at Stanford focused on Computational and Mathematical Engineering with an AI and Data Science specialization. She conducted AI research at Stanford School of Medicine, including projects on multimodal emergency department data summarization and opportunistic screening for atrial fibrillation, aligning with her ambition to use AI for healthcare. join-fomo+5
With a keen entrepreneurial spirit, Elsa is involved in various ventures and initiatives. She co-hosts the 'Second Order Podcast' to explore the mindset and skills of successful entrepreneurs and is part of Stanford's Accel Leadership Program, which focuses on developing entrepreneurial leaders. She also expresses interest in starting her own company leveraging AI. polytechnique+2
Elsa has a solid academic foundation from prestigious institutions. She graduated Magna Cum Laude from École Polytechnique with a double major in Mathematics and Computer Science, including a semester abroad at Columbia University. Her current Master's degree at Stanford further solidifies her expertise in computational fields. join-fomo+1
Work
Education
Projects
Writing
Opportunistic Screening for Atrial Fibrillation With Continuous ECG Monitoring in the Emergency Department
January 1, 2025A publication where Elsa Bismuth is an author, focusing on the use of continuous ECG monitoring for atrial fibrillation screening in emergency department settings.
Integrated models for disease risk identification and stratification
Research on training prediction and survival models using multi-omics data for disease risk identification and stratification, aiming to create integrated models beyond single data types.
Predicting market value in football transfers
Research focused on identifying relevant parameters to monitor and predict the market value of football players, crucial for recruiting departments in football clubs.
Notes
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EBElsa Bismuth
is outstanding at designing and hosting non-generic events for small groups.Jan 11, 2026