Sotabase

Career

· PhD in Computer Science, Stanford University2024–
· Research Scientist, Brown University, LUNAR Lab2023–2024
· Research Scientist, New York University, Human & Machine Learning Lab2023–2024
· Grader & Tutor, New York University, Courant Institute2020–2023
· Trainee, NIH, Training Program in Computational Neuroscience2020–2021
· Research Assistant, New York University, Human & Machine Learning Lab2019–2023
· B.A. in Mathematics, New York University2018–2023
· B.A. with Honors in Computer Science, New York University2018–2023

Publications (0)

A Developmentally-Inspired Examination of Shape versus Texture Bias in Machines
Annual Meeting of the Cognitive Science Society · 2022
18
cited
Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects
Neural Information Processing Systems · 2024
15
cited
Deep Neural Networks Can Learn Generalizable Same-Different Visual Relations
Proceedings of Cognitive Computational Neuroscience 2025 · 2023
6
cited
Modeling artificial category learning from pixels: Revisiting Shepard, Hovland, and Jenkins (1961) with deep neural networks
Annual Meeting of the Cognitive Science Society · 2021
3
cited
Addressing divergent representations from causal interventions on neural networks
arXiv.org · 2025
Diagnosing Bottlenecks in Data Visualization Understanding by Vision-Language Models
arXiv.org · 2025
Exploring the mechanisms that enable multimodal reasoning about data visualizations in vision-language models
Annual Meeting of the Cognitive Science Society · 2025
Modeling artificial category learning from pixels: Revisiting Shepard, Hovland, and Jenkins (1961) with deep neural networks
2021
Sotabase