Sotabase

Career

· Researcher, Apple2025–
· Research Scientist, Toyota Research Institute2023–2025
· Research Intern, Apple2022–2023
· Research Intern, Google2022–
· Doctor of Philosophy - PhD (Computer Science), Georgia Institute of Technology2019–2023
· Research Assistant, Georgia Institute of Technology2019–2025
· Research Scientist I, Georgia Institute of Technology2017–2019
· Master of Science - MS (Computer Science), Georgia Institute of Technology2015–2017
· Associate Application Developer, at&t2014–2016
· Bachelor of Science - BS (Computational Media), Georgia Institute of Technology2010–2014

Publications (36)

Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning
International Conference on Artificial Intelligence and Statistics · 2020
106
cited
Explainable Artificial Intelligence: Evaluating the Objective and Subjective Impacts of xAI on Human-Agent Interaction
International journal of human computer interactions · 2022
72
cited
Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers
North American Chapter of the Association for Computational Linguistics · 2021
64
cited
Multi-UAV planning for cooperative wildfire coverage and tracking with quality-of-service guarantees
Autonomous Agents and Multi-Agent Systems · 2022
46
cited
Encoding Human Domain Knowledge to Warm Start Reinforcement Learning
AAAI Conference on Artificial Intelligence · 2021
42
cited
LanCon-Learn: Learning with Language to Enable Generalization in Multi-Task Manipulation
IEEE Robotics and Automation Letters · 2021
39
cited
Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User Demonstrations
Neural Information Processing Systems · 2019
38
cited
Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning
2019
33
cited
ProLoNets: Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning
arXiv.org · 2019
20
cited
Cross-Loss Influence Functions to Explain Deep Network Representations
International Conference on Artificial Intelligence and Statistics · 2020
19
cited
Learning Interpretable, High-Performing Policies for Autonomous Driving
Robotics: Science and Systems · 2022
18
cited
Towards Balancing Preference and Performance through Adaptive Personalized Explainability
IEEE/ACM International Conference on Human-Robot Interaction · 2024
17
cited
Safe Coordination of Human-Robot Firefighting Teams
arXiv.org · 2019
16
cited
Robot Classification of Human Interruptibility and a Study of Its Effects
ACM Trans. Hum. Robot Interact. · 2018
15
cited
Effects of explainable artificial intelligence in neurology decision support
Annals of Clinical and Translational Neurology · 2024
13
cited
Natural Language Specification of Reinforcement Learning Policies Through Differentiable Decision Trees
IEEE Robotics and Automation Letters · 2021
10
cited
Effects of Interruptibility-Aware Robot Behavior
arXiv.org · 2018
9
cited
Interpretable Reinforcement Learning for Robotics and Continuous Control
arXiv.org · 2023
9
cited
FedEmbed: Personalized Private Federated Learning
arXiv.org · 2022
7
cited
Interpretable Policy Specification and Synthesis through Natural Language and RL
arXiv.org · 2021
6
cited
Sotabase
Andrew Silva | Researcher Profile | Sotabase | Sotabase