Nadia Figueroa

I am a Robotics and Machine Learning researcher focused on endowing robots with the capabilities of learning, aiding and smoothly interacting with humans in unstructured and complicated tasks. Such tasks span from household activities like cooking and cleaning to difficult industrial tasks such as assemblies, carrying/lifting large objects, etc. To achieve this goal, my contributions leverage machine learning techniques with concepts from dynamical systems theory to solve salient problems in the areas of learning from demonstration, incremental/interactive learning, human-robot collaboration, multi-robot coordination, shared autonomy and control.

I hold a PhD in Robotics, Control and Intelligent Systems from EPFL, where I conducted my research at the LASA lab, under the supervision of Prof. Aude Billard. Prior to PhD studies, I spent time at the DLR's (German Aerospace Center) Robotics and Mechatronics Institute and at NYU Abu Dhabi. I obtained my bachelor's from Monterrey Tech and master's from TU Dortmund.

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• [Dec. 2019] I will be joining the Interactive Robotics Group at MIT CSAIL as a Postdoctoral Associate in January 2020.
• [June 2019] I successfully defended by PhD thesis entitled: "From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems" under the supervision of Prof. Aude Billard (EPFL).
-> The president of the jury was Prof. Jamie Paik (EPFL), the internal examinar was Prof. Melanie Zeilinger (ETH) and external examiners were Prof. Katherine J. Kuchenbecker (MPI) and Prof. Julie A. Shah (MIT).
• [May 2019] At ICRA 2019 I will be giving a tutorial on "Dynamical System-based Learning from Demonstration". Together with my advisor and colleagues we will present the DS-learning methods developed in the lab and how to use them for different applications.

• In December 2018, I gave a 30min talk at the SwissAI Machine Learning meetup at EPFL
• In November 2018, I gave a 12min talk at the Swiss Machine Learning Day (SMLD) at EPFL
• At Corl 2018, I gave a 4min spotlight presentation for my accepted paper.
• In August 2018, I gave a 45min Research Seminar at UT Austin, Texas
• In July 2018, I gave two lectures (lecture 1, lecture 2) + exercise session at the Tutorial on Dynamical system-based Learning from Demonstration at EPFL, which I co-organized / website
• At ICRA 2018, I gave a 12min talk at the Workshop in Machine Learning in the Planning and Control of Robot Motion / website
• At ICRA 2018, I gave a 12min talk at the Workshop on Cognitive Whole-Body Control for Compliant Robot Manipulation / website

• In Sept. 2019, my PhD thesis was nominated for the EPFL Doctoral Program distinction . This distinction is granted to a selection of very high quality theses, in order to highlight the doctoral candidates’ research work and their scientific merit. For each doctoral program, nominated graduates are selected on the basis of their oral examination. Then the program committee evaluates the nominees and rewards the best 8%.
• In Sept. 2019, my PhD thesis was also nominated for the the Asea Brown Boveri (ABB) Ltd. Award . The prize is awarded for particularly excellent master’s and/or doctoral work in the fields of energy and information technology and automation technology.
• In April 2017, our team (me + Sina Mirrazavi + Aude Billard) was selected as one of the Top 5 finalists in the KUKA Innovation Award / spotlight video
• At RSS 2016, we won (together with Sina Mirrazavi) the Best Student Paper award and were nominated for Best Conference Paper and Best Systems Paper.
• In 2016, I was selected as a Human-Robot Interaction Pioneer for the HRI Pioneers workshop which identifies and empowers the world’s top student researchers early in their careers.

The following research projects were funded by the European Union via : the FP7 project Robohow and/or the H2020 projects Cogimon and SecondHands . For a list of publications, checkout my Google Scholar profile or my epfl-lasa website.

Learning Complex Sequential Tasks from Demonstration: Uni-Manual and Bi-Manual Case Studies

Project pages:
• Learning and Execution of Complex Sequential Tasks: https://nbfigueroa.github.io/complex-seq-task-learning/





Learning Stable Dynamical System (DS) Representations of Complex Motions from Demonstrations: Task and Joint Space Approaches

Project pages:
• Task-Space DS: https://nbfigueroa.github.io/pc-gmm-ds-learning/
• Joint-Space DS: https://nbfigueroa.github.io/jtds-learning/












Locally Active Globally Stable Dynamical Systems for Manipulation, Navigation and Co-Manipulation

Project pages:
• Code for Learning and Execution of LAGS-DS: https://nbfigueroa.github.io/lags-ds-learning/









Development and Learning of Multi-Arm Coordination Strategies

Project pages:
• Multi-arm coordination strategies: https://nbfigueroa.github.io/multi-arm-coordination/









Dynamical System based Adaptive Grasping, Navigation and Co-Manipulation with Humanoid Robots

Project pages:
• DS-based iCub motion planing: https://epfl-lasa.github.io/iCub-Assistant/

Throughout my PhD I've been a teaching assistant for the following graduate courses:
MICRO-401 Machine Learning Programming (Fall 2016/Fall 2017)
Head Teaching Assistant and Main Syllabus Architect and Developer.
MICRO-570 Advanced Machine Learning (Spring 2016/2017)
Head Teaching Assistant and Tutorial Developer.
MICRO-455 Applied Machine Learning (Fall 2015)
Teaching Assistant.
Co-developer of ML_toolbox .

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