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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Invited Talks and Lectures
  • 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
Honors and Awards
  • 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.

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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