Andrea Tacchetti

Andrea Tacchetti
Graduate Student



Associated Research Thrust: 

I am a third year PhD student in the Electrical Engineering and Computer Science at MIT where I am part of the Computer Science and Artificial Intelligence Laboratory. I am advised by Tomaso Poggio in the Center for Brains, Minds, and Machines and I am part of the LCSL, a joint lab between MITand the Istituto Italiano di Tecnologia. I am interested in building systems that model and imitate how our visual cortex recognizes objects, actions and people in videos and static images under a wide variety of transformations. I also design algorithms that are able to learn from large amounts of labeled data.

In the Summer of 2014 I have worked as a Software Engineering and Research Intern at (Amazon, Inc) where I developed a Deep Learning system for object localization and recognition. In the Summer of 2013 I worked as a Data Scientist and Software Engineering Intern at Room 77, Inc (acquired by Google in 2014) where I designed and wrote algorithms for search results ranking and segmentation.

In the fall of 2013 I was a Teacher Assistant for Prof. A. Torralba's graduate level class Advances in Computer Vision (6.869). In the fall of 2014 I was a Teacher Assistant for Prof. L. Kaelbling's Machine Learning (6.867) graduate level class..

In 2010 I was part of the Equipment Controls and Electronic section in the Engineering Department at CERN where I developed a system to learn the minimum tracking error parameters for a complex control loop from measurements acquired on board.

race bikes for the MIT Cycling Tream where I also serve as treasusrer. In the past I have been the organizer of the Machine Learning Tea at MIT for which I have secured fundings from Google. Together with M. Gharbi I am writing a vision based iPhone app called Splitsy.



J. Mutch, Anselmi, F., Tacchetti, A., Rosasco, L., Leibo, J., and Poggio, T. A., Invariant Recognition Predicts Tuning of Neurons in Sensory Cortex, in Computational and Cognitive Neuroscience of Vision, Springer, 2017, pp. 85-104.
A. Tacchetti, Isik, L., and Poggio, T. A., Invariant representations for action recognition in the visual system., Vision Sciences Society, vol. 15, no. 12. Journal of vision, 2015.