Marco Altini - PhD, Data scientist, Entrepreneur
I'm leading data science activities at Bloomlife, a digital health startup focusing on helping expecting mothers have a healthy pregnancy. We are taking a data driven approach, combining data collected in clinical settings as well as consumer generated data to help shedding light on many poorly understood links between physiological changes naturally occurring during pregnancy, behavior and pregnancy outcomes.
I am also the creator of HRV4Training, a mobile platform using advanced signal processing and data analytics to optimize training, currently used by more than 25 000, 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, and uses HRV to optimize training programs and help prevent overtraining. HRV4Training has been among the top 10 best selling apps in more than 4 continents and 30 countries. You can find out more on the HRV4Training blog.
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. 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.
I am currently based in Amsterdam and you can reach me via email here.
I am also the creator of HRV4Training, a mobile platform using advanced signal processing and data analytics to optimize training, currently used by more than 25 000, 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, and uses HRV to optimize training programs and help prevent overtraining. HRV4Training has been among the top 10 best selling apps in more than 4 continents and 30 countries. You can find out more on the HRV4Training blog.
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. 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.
I am currently based in Amsterdam and you can reach me via email here.