I am a scientist with a unique multi-disciplinary background. I’m an astrophysicist, computer scientist, technologist, researcher, business leader, (and very soon entrepreneur). I’m a senior scientist in AI human-centric; I possess strong analytical and quantitative skills, with expertise in physics, physical chemistry, machine learning, and AI.
During my research career, I studied complex problems in astrophysics and astrochemistry that required critical thinking and advanced knowledge in the field. I am passionate about AI, and I have expanded my experience to AI.
I’m a scientist responsible for the development of new and novel ideas, from prototype phase to market. I’m a deep thinker, innovator, and technical entrepreneurial leader to build the next big idea!
With some years of experience in performing leading-edge research, I have experience in developing and implementing various radically new ideas from the idea phase to a prototype. I have the chance to help develop a new product from the very early stages in a fast-paced start-up-like environment and I want to invent the future. As a problem solver, I have the potential to impact a large enough portion of the world’s population.
I have experience in rapid ramp, scale-up, and transitioning ideas to products with significant experience in writing technical reports, papers, patents, and other written and oral communications.
Prior to my AI experience, I was a research scientist leading research in astrophysics, my research aims to uncover how physical and chemical processes affect the outcome of planet formation, especially the chemical habitability of nascent planets with a huge interest in “all things ice”, looking at how solid-state materials play a role in the processes of star and planet formation, combining laboratory experiments with major facilities use, to understand the formation, the evolution of molecules in the interstellar medium, the role of ice in interstellar chemistry, and exploit molecular dynamics simulations to understand the physical-chemical properties of ice in space.
And now I’m designing algorithms to solve AI problems and am interested in the problems of deep learning, computer vision, Reinforcement Learning applied to Human-Computer Interaction, and affective computing
– Deep Learning, Computer Vision, Deep Neural Network. Deep Reinforcement Learning, Open, NN, CNN, RNN, TensorFlow, Keras, Pytorch …
– Machine Learning, analysis method, and Statistics
– Astronomical Numerical Code, Spectroscopy, Mass spectrometry: TPD, IR Spectroscopy, Laser, UHV.