Nikolas McNeal

I am currently a second-year Ph.D. student in the Machine Learning program @ Georgia Tech, where I work with Ratan Murty. I am broadly interested in the computational principles underlying visual perception, particularly the relationship between representations from neural networks and humans. I obtained my undergraduate degree in Computer Science from The Ohio State University in 2023.

Papers

McNeal N., Deb M., Murty A.R.N. Small-scale adversarial perturbations expose differences between predictive encoding models of human fMRI responses. NeurIPS 2024 Workshop on Unifying Representations in Neural Models (UniReps)

Dipani A.*, McNeal N.*, Murty A.R.N. Linking faces to social cognition: The temporal pole as a potential social switch. PNAS (Commentary). 2024 [paper]

McNeal N., Huang J., Umoren A., Dai S., Dannenberg R., Randall R., Lee T.S. Relating Human Perception of Musicality to Prediction in a Predictive Coding Model. arXiv. 2023. [paper] [code]

Gutiérrez B., McNeal N., Washington C., Chen Y., Li L., Sun H., Su Y. Thinking about GPT-3 In-Context Learning for Biomedical IE? Think Again. EMNLP 2022 (Findings). Presented in Abu Dhabi, United Arab Emirates. [paper] [code]

* denotes equal contribution

Peer-reviewed abstracts:

• Shanahan D., Kang J., McNeal N. Understanding the Role of Schematic Knowledge in the Preference for Harmonic Asymmetry with Iterative Learning. International Conference on Music Perception and Cognition (ICMPC), 2023. Tokyo, Japan. Oral presentation.


• McNeal N., Kang J., Hay N., Shanahan D. Iterative learning suggests a preference for harmonic asymmetry. Society for Music Perception and Cognition (SMPC), 2022. Portland, Oregon. Oral presentation.


• McNeal N., Shevlin B., Krajbich I. What causes enhanced processing of high-value items? Poster at: 44th Annual Cognitive Science Society (CogSci), 2022. Toronto, Canada. [poster]

Teaching

TA @ Georgia Tech
• Fall 2023, Spring 2024, Fall 2024
    MATH 2552 Differential Equations [notes]

TA @ Ohio State
• Spring 2023
    MATH 4530 Quantitative Neuroscience

Mentorship

Directed Reading Program

The Directed Reading Program is a program in the Math department that pairs interested undergraduates with graduates students for independent study projects.
I have served as a mentor for the following semesters:

[Autumn 2023] Topic: Machine Learning for Modeling Dynamical Systems

[Spring 2024] Topic: Introduction to Machine Learning

Honors

• [2023] OSU CSE Undergraduate Research Award
• [2021] OSU Undergraduate Research Scholarship
• [2021] OSU Decision Sciences Collaborative Scholarship
• [2019] Eminence Fellowship (now Stamps Eminence Scholarship)