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Basics

Name: Erin Botti
Title: Robotics PhD
Specialties: Machine Learning, Human-Robot Interaction

Education

Skills

Programming Languages
Python, Java, R, MATLAB, C, C++, SQL, JavaScript
Tools & Libraries
Pytorch, ROS, ROS2, Scikit-learn, CUDA, Linux, Git, Jupyter Notebook, Pandas, Numpy, Matplotlib, AWS, Azure, Neo4j, Flask
Machine Learning & Artificial Intelligence
Deep Learning, Imitation Learning, Meta-Learning, Reinforcement Learning, Explainable AI (xAI), Neural Networks, Long Short-term Memory (LSTM), Transformers, Decision Trees, Search Algorithms, Clustering, Classification, Regression
Data Analysis
Quantitative Analysis, Qualitative Analysis, Statistics and Probability, User Studies

Research Experience

  • 2019 - Present
    Graduate Research Assistant
    Georgia Institute of Technology
    CORE Robotics Lab, Advisor: Matthew Gombolay
      Machine Learning Projects
    • LIFI Framework: Designed, trained, and tested a multi-head attention network, improving imitation learning and xAI. LIFI learns interpretable features from human interventions and significantly outperforms baselines for accuracy, trust, workload, and usability.
    • MIND MELD Architecture: Advanced imitation learning by integrating LSTMs, mutual information, and variational inference to learn from suboptimal demonstrators. MIND MELD outperforms baselines for accuracy, human trust, and workload [HRI 2022].
    • Reciprocal MIND MELD: Created an LSTM-based system to generate personalized explanations that teach users how to provide better demonstrations. Reciprocal MIND MELD automates training demonstrators and models the user's behavior changes [CoRL 2022].
    • Implemented full stack learning frameworks on robots and driving simulators using ROS, ROS2, Pytorch, and Python [RSS 2024, CoRL 2022, HRI 2022].
    • User Study Experiments
    • Designed, built, and executed human-subjects experiments to study user reactions to algorithms and technical systems with respect to trust, workload, and user satisfaction.
    • Performed advanced statistics and analytics on experiment data to validate hypotheses.
    • Conducted user studies with target populations, including older adults and people with mild cognitive impairment to understand diverse preferences.
    • Supervised and mentored junior lab members in designing experiments, writing papers, and lab best practices.

Industry Experience

  • 2017 - 2019
    Computer Engineer
    Johns Hopkins University Applied Physics Lab
    • Led a team of four engineers in developing and delivering a Neo4j database prototype, enabling multi-domain data comparison.
    • Implemented computer vision machine learning models to increase efficiency for reverse engineering embedded devices.
    • Designed and ran tests in a laboratory environment to thoroughly test and evaluate RF geolocation equipment before conducting tests in a real field environment.
  • 2015 - 2016
    Summer Intern
    Johns Hopkins University Applied Physics Lab
    • Implemented and extended a set of state-of-the-art image forensics tools.
    • Created a testing automation tool which significantly decreased testing time.

Teaching Experience

  • Spring - 2022
    Head TA: Graduate Teaching Assistant
    Georgia Institute of Technology
    Class: Robot Intelligence Planning – Professor: Matthew Gombolay
    • Managed a team of four TAs, created and graded homework assignments and exams, conducted office hours, and facilitated discussions on an online forum for a class of 90 students.
  • Fall - 2023
    Graduate Teaching Assistant
    Georgia Institute of Technology
    Class: Introduction to Robotics – Professor: Sean Wilson
    • Built and maintained Turtlebot robots, graded homework assignments and projects, conducted office hours, and facilitated discussions on an online forum for a class of 60 students.

Awards

  • 2022.03.01
    Best Technical Paper
    ACM/IEEE International Conference on Human-Robot
  • 2023.04
    TA of the Year
    School of Interactive Computing - Georgia Tech
  • 2023.2024
    P.E.O. Scholar Award
    P.E.O.
    The P.E.O. Scholar Awards were established in 1991 to provide substantial merit-based awards for women of the United States and Canada who are pursuing a doctoral-level degree at an accredited college or university. Scholar Awards recipients are a select group of women chosen for their high level of academic achievement and their potential for having a positive impact on society.
  • 2019.2021
    National Science Foundation Accessibility, Rehabilitation, and Movement Science Fellow
    National Science Foundation
    Traineeship program working in conjunction with Emory Medical Facility and the multi-disciplinary Robotics Ph.D. program at Georgia Institute of Technology. Fellowships are awarded to students dedicated to the advancement of the collaboration between healthcare providers and roboticists to advance and understand the constant and ever-changing intersection of technology and medicine.
  • 2019
    Georgia Robotics Fellowship Recipient
    Georgia Institute of Technology
    Award for women and underrepresented minorities in robotics. Individuals are selected based on a rigorous multi-selection criteria set, such as professional recommendations and academic achievement.

Languages

English
Native speaker
Spanish
Fluent