Marco Altini
PhD in Data Science, Founder of HRV4Training, Traveler, Passionate Runner, Immigrant.
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Bio
I am a scientist and developer mainly working at the intersection between health, technology and performance. I have a PhD (cum laude) in data science and a MSc (also cum laude) in computer science engineering.
Currently, I am leading product development (strategy, iOS and Android app development, web platform development) and research (clinical studies, insights, new features development from user generated data and large scale data analysis) at HRV4Training, a mobile platform using advanced signal processing and data analytics to measure physiology and optimize training, helping athletes of all levels improving performance.
I started HRV4Training in 2012, making it a tool that is today trusted by more than 50 000, including olympic medalists and professional teams. HRV4Training is the first and only app that can reliably measure heart rate variability (HRV) using the phone's camera.
Between 2014 and 2019 I led data science activities at Bloomlife, a digital health startup focusing on helping expecting mothers have a healthy pregnancy. During this period Bloomlife grew from 3 to 20 employees, raised over 8 M USD in capital, and pioneered data-driven pre-natal research. In 2019 I left Bloomlife to pursue a different career path. You can learn more about my research here.
As my interest has shifted from technology development to coaching and working with athletes aiming at improving their performance through a scientific approach, I will be going back to school for a master's degree in Human Movement Sciences between 2019 and 2020.
In 2015 I obtained my PhD cum laude (top 5%) in applied machine learning at Eindhoven University of Technology. My PhD research at TU/e focused on applying machine learning techniques to develop new methods for personalized assessment of physical activity and cardiorespiratory fitness using wearable sensors data. During this period, I've published more than 25 peer reviewed papers for international conferences and journals, and three patents, which have been licensed to multiple customers in the high-end fitness industry. You can find most of my research here.
Previously, I obtained my M.Sc. degree cum laude in computer science engineering in 2010 from the University of Bologna. Between 2009 and 2014 I worked at imec as part of the Human++ program, developing hardware, firmware, software and algorithms for Body Area Networks applications, imec funded my PhD at TU/e. Since 2012, I've been developing mobile apps using the phone's sensors to provide unique insights on the user's physiological status (such as heart rate and heart rate variability) without the need for external hardware. You can find out more in my blog.
From time to time, I also help other companies improving their products, see for example my work on Relative Effort with Strava.
Currently, I am leading product development (strategy, iOS and Android app development, web platform development) and research (clinical studies, insights, new features development from user generated data and large scale data analysis) at HRV4Training, a mobile platform using advanced signal processing and data analytics to measure physiology and optimize training, helping athletes of all levels improving performance.
I started HRV4Training in 2012, making it a tool that is today trusted by more than 50 000, including olympic medalists and professional teams. HRV4Training is the first and only app that can reliably measure heart rate variability (HRV) using the phone's camera.
Between 2014 and 2019 I led data science activities at Bloomlife, a digital health startup focusing on helping expecting mothers have a healthy pregnancy. During this period Bloomlife grew from 3 to 20 employees, raised over 8 M USD in capital, and pioneered data-driven pre-natal research. In 2019 I left Bloomlife to pursue a different career path. You can learn more about my research here.
As my interest has shifted from technology development to coaching and working with athletes aiming at improving their performance through a scientific approach, I will be going back to school for a master's degree in Human Movement Sciences between 2019 and 2020.
In 2015 I obtained my PhD cum laude (top 5%) in applied machine learning at Eindhoven University of Technology. My PhD research at TU/e focused on applying machine learning techniques to develop new methods for personalized assessment of physical activity and cardiorespiratory fitness using wearable sensors data. During this period, I've published more than 25 peer reviewed papers for international conferences and journals, and three patents, which have been licensed to multiple customers in the high-end fitness industry. You can find most of my research here.
Previously, I obtained my M.Sc. degree cum laude in computer science engineering in 2010 from the University of Bologna. Between 2009 and 2014 I worked at imec as part of the Human++ program, developing hardware, firmware, software and algorithms for Body Area Networks applications, imec funded my PhD at TU/e. Since 2012, I've been developing mobile apps using the phone's sensors to provide unique insights on the user's physiological status (such as heart rate and heart rate variability) without the need for external hardware. You can find out more in my blog.
From time to time, I also help other companies improving their products, see for example my work on Relative Effort with Strava.