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SELECTED PROJECTS

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This page contains a selection of the most interesting projects I had the opportunity to work on during my career.

 

You can initially scroll through some of my projects at Dolby, like our solution for generating personalized audio profiles optimized for your head and ear anatomy (PHRTF), my work on speech analytics, or the pair of headphones I built for gaze tracking.

Or you can read about my main research project at MIT, where I developed a noninvasive technology to monitor intracranial pressure in patients with brain injury. 

 

If you scroll to the very end, you will see a few images from my PhD thesis, dedicated to the development of a wearable device to monitor the fetus during pregnancy.   

Dolby Atmos Personalized Rendering @ Dolby Labs

I led the development of the computer vision and generative AI components of the Dolby Personalized Rendering, and shaped the scientific and algorithmic strategy of the entire research pipeline, from inception to final product.

Dolby Atmos Personalized Rendering uses a personalized HRTF (PHRTF) that is totally unique to your physique, to give you the most accurate spatial experience possible.

 

The PHRTF generation is obtained through a mobile capture of your head, that is processed to extract relevant anthropometric information of your ears, head, and torso. The anthropometric information is then converted into a personalized sound profile that is optimized for your physique. 

Dolby Atmos Personalized Rendering was released to the public in March 2022.

 

Speech Analytics for Dolby.io (2020-2022) @ Dolby Labs
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I led the team that developed and released a collection of algorithms for speech analysis, such as speaker diarization (segment audio and identify who speaks when), speaker identification (detect if and when a speaker participates in a conversation), speech emotion recognition (quantify emotion from speech), and speech content analysis (extract topic of conversation). 

 

The algorithms are part of the Dolby.io Speech Analytics API, one of the offerings of the Dolby.io Media APIs. Internal comparative analysis showed that Dolby diarization algorithm is one of the best performing algorithms for audio speaker diarization on the market. 

Headphones for gaze tracking (2019) @ Dolby Labs

I led the development of a pair of headphones for gaze tracking. The headphones are capable to decode gaze information using EOG measurement, leveraging foam-based electrodes on the cuff. The recorded EOG signal is then processed to generate real time gaze information, with no need of cameras  facing the user or dedicated eye-tracking hardware.  

The prototype was selected as the most innovative technology at Dolby IdeaQuest (internal competition for innovation) in 2019. 

Noninvasive brain monitoring (2013-2018) @ MIT

During my years as postdoctoral affiliate and research scientist at MIT, I developed a noninvasive technique for intracranial pressure estimation. 

I developed a lumped-parameter model to describe brain cerebrovascular behavior and a data acquisition system to collect data from neurosurgery intensive care units. I also designed and implemented a real time signal processing pipeline to acquire physiological signals, filter them, reject noisy sections, and estimate intracranial pressure using arterial blood pressure and cerebral blood flow velocity waveforms.

 

The technology was tested and deployed to two hospitals of the Boston area (Boston Children’s Hospital and Boston Medical Center).

 

My research work was featured by MIT News in August 2019.

Wearable fetal ECG monitor (2010-2013) @ Politecnico di Milano and MIT

During my PhD at Politecnico di Milano and MIT, I ideated, designed, and built a wearable device for fetal monitoring, with joint hardware/algorithm development.

 

I designed and engineered wearable sensors, and analog and digital electronics for fetal ECG measurement, conditioning, and transmission. I also developed digital algorithms for fetal ECG extraction, analysis, and classification. 

The device was tested and validated on a population of patients with IUGR (Intra Uterine Growth Restrictions) at Ospedale Federico II in Naples, Italy. 

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