Alexander Aminiemail: email@example.com
resume, google scholar
BioI am a PhD student at the Massachusetts Institute of Technology (MIT), in the Computer Science and Artificial Intelligence Laboratory (CSAIL), with Prof. Daniela Rus. I am a NSF Fellow and completed my Bachelor of Science and Master of Science in Electrical Engineering and Computer Science at MIT, with a minor in Mathematics.
My research focuses on building machine learning algorithms for end-to-end control (i.e., perception to actuation) of autonomous systems and formulating guarantees for these algorithms. I have worked on control of autonomous vehicles, formulating confidence of deep neural networks, mathematical modeling of human mobility, as well as building complex inertial refinement systems.
In addition to research, I am also a lead organizer and lecturer for MIT 6.S191: Introduction to Deep Learning, MIT's official introductory course on deep learning. In high school I was named the European Union Young Scientist of 2011 with my project entitled: Tennis Sensor Data Analysis: An Automated System for Macro Motion Refinement. I grew up in New York, and then moved to Dublin, Ireland, where I attended Castleknock College, and then returned to the US in 2012.
My professional resume can be found here.
|Oct 2018||Invited Talk and contributed papers at ICML 2019 Workshop for Autonomous Driving, and Reinforcement Learning in Real Life.|
|Mar 2019||Our paper Variational End-to-End Navigation and Localization has been nominated for the Best Paper Award at ICRA 2019 (top 0.1% of all submissions)|
|Jan 2019||Paper: Variational End-to-End Navigation and Localization has been accepted to ICRA 2019.|
|Jan 2019||Lecturer for the 2nd straight year of MIT 6.S191: Introduction to Deep Learning, MIT's official course on deep learning applications and foundations. [link] [video]|
|Dec 2018||Paper: Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure has been accepted to AAAI/ACM AIES 2019 [paper]|
|Oct 2018||Invited Talk at IROS in Madrid, Spain: Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing|
|Jun 2018||Paper: Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing has been accepted to IROS 2018 [paper]|
|Jun 2018||Graduation: Master of Science (MS) from MIT in EECS. Thesis: Robust Learning for End-to-End Autonomous Driving [thesis]|
|Mar 2018||Invited Talk at NVIDIA's GTC in San Jose, California: Learning Steering Bounds for Parallel Autonomy [talk]|
|Jan 2018||Lecturer for MIT 6.S191: Introduction to Deep Learning, MIT's official course on deep learning applications and foundations. [link] [video]|
|Jun 2018||Paper: Learning Steering Bounds for Parallel Autonomous Systems has been accepted to ICRA 2018. [paper]|
|Dec 2017||Invited Talk at the NIPS workshop on Bayesian Deep Learning (12% acceptance rate).|
|Nov 2017||Travel Award to present our paper, Spatial Uncertainty Sampling for End-to-End Control, at NIPS Bayesian Deep Learning (8% acceptance rate). [paper]|
|Jun 2017||Summer Internship starting my summer internship with NVIDIA's end-to-end self driving car team.|
|Jun 2017||NSF Fellowship. Awarded the National Science Foundation Graduate Fellowship (10% acceptance rate).|
|Jun 2017||Graduation: Bachelor of Science (BS) from MIT in EECS with a minor in Mathematics and concentration in Economics.|