Max Kramer

Max Kramer
University of Chicago | UC · Division of Social Sciences

Bachelor of Arts

About

5
Publications
167
Reads
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Citations
Introduction
Undergraduate researcher with interests in applied Machine Learning in Psychology and Neuroscience Research. Member of 1step2life lab (Dr. Nancy Darling) and CASH lab (Dr. Kenneth Allen). Past summer fellow TarrLab (Dr. Michael Tarr) www.mkramerpsych.com
Skills and Expertise
Statistical Data Analysis
Data Science
Predictive Modeling
Machine Learning
Neural Networks and Artificial Intelligence
Additional affiliations
June 2019 - August 2019
Carnegie Mellon University
Carnegie Mellon University
  • Center for the Neural Basis of Cognition
  • Pittsburgh, United States
Position
  • Fellow
Description
  • Summer Research Fellow TarrLab - Dr. Michael J Tarr CNBC @ Carnegie Mellon University/University of Pittsburgh
September 2018 - May 2020
Oberlin College
Oberlin College
  • Department of Psychology
  • Oberlin, United States
Position
  • Lecturer
Description
  • Tutoring for : PSYC 200 Research Methods 1 PSYC 300 Research Methods 2
June 2018 - August 2018
Harvard University
Harvard University
  • The Music Lab
  • United States
Position
  • Remote Collaborator
Description
  • Summer remote collaborator for the Music Lab PI - Samuel Mehr Cataloged vocal musics of East Asia for the Natural History of Song project
Education
August 2020 - May 2022
University of Chicago
University of Chicago
Field of study
  • Computational Social Science
September 2016 - May 2020
Oberlin College
Oberlin College
Field of study
  • Psychology (M), Computer Science (m), Cognitive Science (conc), Statistical Modeling (conc)

Publications

Publications (5)
Negative Emotional Action Termination: an Empirical Validation
Presentation
Full-text available
  • May 2020
Validation of the Emotional Stop Signal Task. The ESST serves as an objective measure of emotion dysregulation, eschewing the need to rely on potentially biased self-report measures.
Figure 3.​ Prediction Accuracies of Model Architectures at N = 0, k...
Figure 4. ​ Performance Differences For All Models Between k = 1 and k...
Assessing the Feasibility of Machine Learning to Predict Chronic Pain in Adolescence
Thesis
Full-text available
  • May 2020
Chronic pain affects between 15 to 40% of adolescents worldwide. The impact and prevalence of chronic pain can be felt every day in terms of missed school days, strained familial relationships, and financial stress. While rehabilitation programs specifically designed for chronic pain management exist, they cannot always adapt to the idiosyncratic n...
Investigating the Role of Color in DCNN Sex Classification of Faces
Poster
Full-text available
  • Aug 2019
A Residual Neural Network model was employed on a subset of the VGGFace2 dataset to examine the role that color plays as a cue to sex classification. Results from Yip & Sinha (2002) were extended to a deep learning framework and preliminary analysis into the entanglement of color and sex in CNN representations was conducted.
Visualizing a Migraine: A neural network based approach to modeling cortical spreading depression
Presentation
Full-text available
  • Apr 2019
Ohio Undergraduate Psychology Research Conference 2019 Presentation by Max Kramer In collaboration with Nancy Darling, Rich Salter, and Keith Downing
A New View of Pain: Dynamic Systems Modeling of Chronic Pain and Functionality
Presentation
Full-text available
  • Apr 2018
Ohio Undergraduate Psychology Research Conference 2018 Presentation Presented by Max Kramer In collaboration with Nancy Darling, Rich Salter

Network

Projects

Projects (2)
BE(^2)SST: Bayesian Estimation of the Emotional Stop Signal Task
Archived project
Bayesian Parameter Estimation of the reaction time results of the Emotional Stop Signal Task (Allen & Hooley, 2015). Predictive modeling of output parameters and examination of the impact of valence coding in responses to the modified stimuli.
Emotional Response Inhibition and the functional theory of the p factor: A computational neuroscience approach to transdiagnostic risk for psychopathology
Archived project
Examine the independent and interactive effects of emotion reactivity (measured in multiple modalities) and incentive sensitivity to determine whether these factors additively contribute to the classification of specific forms of psychopathology. This project involves secondary analyses across several combined datasets including diverse clinical and non-clinical populations.