ALEIX PARIS
Aerospace Engineer, Roboticist, and Computer Scientist
About me
I obtained my BSc in Aerospace Engineering and my BSc in Computer Science at Universitat Politècnica de Catalunya (Barcelona) in 2018, and my MSc in Aeronautics and Astronautics at the Massachusetts Institute of Technology in 2020 (GPA 5.0/5.0). At MIT, I specialized in autonomous systems, optimization, and machine learning. I was fully funded on a Research Assistantship at the Aerospace Controls Laboratory, where I researched on controls, planning, and estimation for autonomous micro aerial vehicles. My research interests also include machine learning, deep learning, computer vision, and autonomous vehicles.
After graduating, I researched at Amazon Prime Air on autonomous drone delivery and then joined Waymo, formerly Google's self-driving car project. I am a Software Engineer in the Behavior team, excited to make the roads much safer!
Projects
Roboticist in the Behavior team at Waymo, formerly Google’s self-driving car project. Developing and implementing algorithms in motion planning and decision making to build the world’s most experienced driver https://waymo.com/
Researched at Amazon Prime Air on the ambitious project of making fast (<30 min), efficient, and robust autonomous drone delivery a reality. By week 2-3 was already delivering results and developed code improvements of up to x30 in speed. In addition, I led research discussions between graduate interns in the fields of robotics, machine learning, and computer vision https://www.amazon.com/primeair
Paper published at the IEEE International Conference on Robotics and Automation (ICRA) 2020. The main contribution is a planning and control strategy that allows a quadrotor to land on a moving platform in challenging conditions, and is part of my M.S. thesis. The paper is available at https://arxiv.org/abs/1909.11071
Paper accepted at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2020. This work develops a novel wind, drag force, and interaction force estimation technique using bio-inspired sensors, an unscented Kalman filter and deep learning (LSTM). The paper, which is also part of my M.S. thesis, is available at https://arxiv.org/abs/2003.02305
In parallel with my main project, I implemented a distributed control algorithm for a drone formation, which I personally showed to the former CEO of Northrop Grumman and General Motors Kent Kresa. The paper was accepted to IEEE IROS 2020 and the IEEE RAS RA-L journal, and is available on https://arxiv.org/abs/2003.01851
Class project for MIT’s Principles of Optimal Control and Estimation (subject number 16.32). The project consists in finding the optimal control inputs for an autonomous drone to finish a race – which consists of a set of gates – as fast as possible. The code is publicly available on Github.
Class project for MIT’s Adaptive Control and Connections to Machine Learning (subject number 2.153). The project consists in an adaptive controller for a quadrotor which is robust to parametric uncertainties such as a rotor failure. The code can be found here.
Paper published to the 2019 IEEE Aerospace Conference. The work proposes a new method for joint power and bandwidth allocation in multibeam satellite systems using artificial intelligence techniques. This paper was part of my B.S. Thesis and it can be accessed here (official IEEE site) and here (publicly available).
Machine learning is a recent and very promising approach to find new medicines efficiently using fewer resources and time than traditional methods. In the context of MIT’s AI Cures, I developed MoleculRNN, a deep learning approach using recurrent neural networks (LSTM) to predict molecular activity against COVID-19 secondary infections. From hundreds of candidate molecules, this approach identifies the ~25% most promising, highly increasing the efficiency of medical discovery.
I am passionate about aerospace engineering, and flying was always a dream for me, so I obtained my Private Pilot License, PPL(A), in summer 2017. Since, then, I have flown from time to time both in Spain and in the USA, taking many people that enjoyed the amazing views. Check out my Instagram to follow this and my other adventures!
Speaking & media appearances
- Article at Business Insider España, about my studies and career.
- Keynote speaker at CYT BAQ CONGRESS 2020, about my research at MIT and the state of the art in robotics, with an audience of 250+ people.
- TV show “No pot ser”, from the Catalan public television, Televisió de Catalunya (TV3). The show is “a prime time show about the great revolution of our era”. I spoke about my research at MIT, the student life, and took the TV host flying above Boston. It was the most-watched TV program of that evening in the region (~7.5 million inhabitants).
- Interview at the National Radio of Spain (RNE). I was invited at “Solamente una vez” to talk about my research and the future of autonomous vehicles.
- Article at the Catalan newspapers Exterior.cat and Línia Horta, about my life story and research.
- Article at the Spanish newspaper “La Vanguardia”, about MIT students.
Contact me
- aleix@alum.mit.edu
- San Francisco Bay Area, CA, USA