|email:||atacchet [at] mit [dot] edu|
|Google Scholar Profile|
I am a fifth year PhD candidate 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 MIT and the Istituto Italiano di Tecnologia. I am interested in building systems that model and imitate how our visual cortex learns to recognize objects, actions and faces 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.
I spent the summer of 2016 as a Research Intern at Google DeepMind where I worked on systems that learn Newtonian mechanics from videos. In the summer of 2014 I have worked as a Software Engineering and Research Intern at A9.com (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.
I race bikes for the MIT Cycling Tream where I also serve as Vice President. 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 Sruthi Reddy Chintakunta I participated in the MIT 100K - The Entrepreneurship Competition in 2016.