Alberto Rosas

CEO

San Francisco, California, United States5 yrs 11 mos experience

Highly Stable

Key Highlights

CEO of Didit, focusing on online identity solutions.
Co-founder of a leading aesthetic medicine clinic in Barcelona.
Experience in developing metaverse technology.

Stackforce AI infers this person is a leader in healthcare technology and identity management.

Contact

Skills

Core Skills

Identity ManagementFraud DetectionHealthcare ManagementPatient ServicesTechnology DevelopmentStartup LeadershipMachine LearningData AnalysisHealthcare Technology

Other Skills

identity infrastructurefraud preventionaesthetic medicinewellness treatmentspatient caremetaverse technologystartup developmentdeep learningtime series analysissensor data processing

About

Building Didit to solve online identity. I love learning new things and reducing entropy in complex systems.

Experience

5 yrs 11 mos

Total Experience

2 yrs 2 mos

Average Tenure

1 yr 10 mos

Current Experience

Santé clínica estética

Co-Founder

Aug 2024 – Present · 1 yr 10 mos · Barcellona · On-site

Santé is a leading aesthetic medicine and wellness clinic in Barcelona, offering 68+ advanced treatments across injectables, anti-aging medicine, laser therapies, body contouring, hair restoration, and holistic wellness — delivered by a board-certified medical team of 7+ doctors and 30+ specialists focused on personalized, high-end patient care.
10,000+ patients treated · 4.9★ Google rating across 700+ reviews · Barcelona · santeclinics.com

aesthetic medicinewellness treatmentspatient carehealthcare managementpatient services

Didit (yc w26)

Chief Executive Officer

Sep 2023 – Present · 2 yrs 9 mos

Building the infrastructure for identity and fraud

identity infrastructurefraud preventionidentity managementfraud detection

Gamiumcorp

Co-Founder & CEO

Sep 2021 – Sep 2024 · 3 yrs

Developing metaverse technology. Exited

metaverse technologystartup developmenttechnology developmentstartup leadership

Universitat politècnica de catalunya

Machine Learning Researcher

Oct 2019 – Dec 2020 · 1 yr 2 mos

Researching best solutions for detecting, and evaluating Parkinson-related diseases using sensor data.
Time series analysis and decomposition.
Developing Machine Learning and Deep Learning models for the detection of Parkinson-related events.
Investigating and Implementing a full library for the Multiple Instance Learning framework.

machine learningdeep learningtime series analysisdata analysis