Biography
I am currently a PhD student in the Department of Social & Decision Sciences at Carnegie Mellon University. I study how humans learn and make sequential decisions from experience, and I do so by building computational cognitive models of human and artificial decision making and through behavioral experimentation.
Visit my Academic website.
Download my CV.
Interests
- Sequential Decision Making
- Learning in Humans and Machines
- Computational Social Science
Education
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PhD Cognitive Decision Science, 2025
Carnegie Mellon University
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ScB Statistics with Honors, 2020
Brown University
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AB Behavioral Decision Sciences, 2020
Brown University
Skills
Statistics
R
Python
Experience
President
Undergraduate Researcher
PI: Steven Sloman. Studied trust in machines in the workplace through behavioral experimentation.
Undergraduate Researcher
PI: Matthew Nassar. Used reinforcement learning models to understand how place field remapping might be used to improve learning in dynamic environments through simulations of the multi-armed bandit task.
Undergraduate Researcher
Applied techniques from topological data analysis to music information retrieval.
Featured Publications
Recent Publications
(2021).
Hipsters and the Cool: A Game Theoretic Analysis of Identity Expression, Trends and Fads.
Accepted to Psychological Review.
(2021).
Diverse Experience Leads to Improved Adaptation: An Experiment with a Cognitive Model of Learning.
Virtual MathPsych/ICCM 2021.
(2020).
SuPP and MaPP: Adaptable Structure-Based Representations for MIR Tasks.
In ISMIR.
(2018).
SE and SnL Diagrams: Flexible Data Structures for MIR.
In ISMIR.
Teaching
Carnegie Mellon University
- Thinking in Person vs. Thinking Online, Prof. Danny Oppenheimer (Fall 2020)
Brown University
- NEUR 1660: Neural Computations in Learning and Decision Making (Spring 2020)
- CSCI 0100: Data Fluency for All, Head Teaching Assistant (Fall 2019)
- CLPS 0220: Making Decisions (Spring 2019)
- CSCI 1951A: Data Science (Spring 2019)
- PHP 1501: Essentials of Data Analysis (Fall 2018)
- APMA 1655: Statistical Inference I (Fall 2018)
- CSCI 0100: Data Fluency for All (Fall 2017)
