Sotabase

Career

· Research Scientist, Sony AI2020–2021
· Assistant Professor, University of California, Santa Cruz2020–
· PhD Student, Massachusetts Institute of Technology (MIT)2015–2020
· Researcher, Palo Alto Research Center (PARC)2013–2015
· M.S., Computational and Mathematical Engineering, Stanford University2011–2013
· B.S., Computer Science and B.S., Mathematics, UC San Diego2006–2011

Publications (37)

Outracing champion Gran Turismo drivers with deep reinforcement learning
Nature · 2022
440
cited
Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations
arXiv.org · 2023
110
cited
Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data
The AI Magazine · 2015
74
cited
Autonomous Driving with Spiking Neural Networks
Neural Information Processing Systems · 2024
22
cited
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Neural Information Processing Systems · 2023
14
cited
Right this way: Can VLMs Guide Us to See More to Answer Questions?
Neural Information Processing Systems · 2024
9
cited
Co-simulation solutions using AA4MM-FMI applied to smart space heating models
International ICST Conference on Simulation Tools and Techniques · 2014
7
cited
Getting Up to Speed on Vehicle Intelligence
AAAI Spring Symposia · 2017
3
cited
Convolutional Neural Network Model for Diabetic Retinopathy Feature Extraction and Classification
Journal of student-scientists' research · 2023
2
cited
DANGER: A Framework of Danger-Aware Novel Dataset Generator Extension for Robustness Test of Machine Learning
2022
2
cited
A Framework for Generating Dangerous Scenes for Testing Robustness
2022
1
cited
MONITORING OPAQUE LEARNING SYSTEMS
2019
1
cited
Practical Lessons on Vector-Symbolic Architectures in Deep Learning-Inspired Environments
1
cited
Act-to-Ground: A Framework for Symbol Grounding in Planning Domains
Adapting Graph-Based Analysis for Knowledge Extraction from Transformer Models
An evidence-based neuro-symbolic framework for ambiguous image scene classification
A novel post-hoc explanation comparison metric and applications
International Conferences on Pattern Recognition and Artificial Intelligence · 2023
A Self-Monitoring Framework for Opaque Machines Extended
2019
Description Logic Concept Learning using Large Language Models
Explore the Loss space with Hill-ADAM
arXiv.org · 2025
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Leilani Gilpin | Researcher Profile | Sotabase | Sotabase