Jonathan Doriscar
Northwestern PhD candidate · M.S. Statistics and Data Science · Founder, MemwaMind
I build intelligent systems for human complexity.
I'm Jonathan Doriscar — a cognitive scientist, computational behavioral scientist, and founder working across memory, language, behavior, data, and AI.
I study how people think, remember, interpret information, and make decisions. I use experiments, statistics, text analysis, and computational methods to turn those questions into research and practical systems.
Hero terminal animation
A compact console lists Jonathan's focus, methods, public work, and current builder direction.
> focus cognition | data | language | judgment > methods experiments | statistics | text analysis | machine learning > public work Social Cognition | IPR working paper | JPSP | Nature Energy > building MemwaMind: memory, documents, review, professional work
focus
cognition | data | language | judgment
methods
experiments | statistics | text analysis | machine learning
public work
Social Cognition | IPR working paper | JPSP | Nature Energy
building
MemwaMind: memory, documents, review, professional work
How I work
How messy human material becomes interpretable.
I start with a human problem, choose a method that can transform the material, and then check what the result can actually support. The examples below separate the topic, the method, the public project, and the reason it matters.
From social attitudes to interpretable structure
large-scale attitude data + Project Implicit Race IAT worked examples + responses and items that may contain hidden structure becomes possible clusters, dimensions, and co-occurring response patterns that researchers can interpret with theory.
- Topic
- Social attitudes and belief patterns
- Method
- Unsupervised structure discovery
- Project anchor
- From Data to Discovery - Published in Social Cognition
- Takeaway
- Shows that Jonathan can bridge cognitive science, machine learning, and methods education without letting the model replace interpretation.
- Limits
- No fake axes, fake percentages, or model-performance claims; the public visual only shows how responses can settle into possible patterns.
Selected work
Projects where the method meets the question.
These case studies show the same habit in different settings: name the question, pick the evidence or design, choose the method, and keep the contribution tied to its public source.
Unsupervised Machine Learning for Social Cognition
Using unsupervised machine learning to reveal hidden patterns in human beliefs and attitudes.
Role: Lead author.
Why Reform Stalls
Modeling public justification, outrage, and reform discourse around police violence.
Role: Conceived and led the project; conceptualization, methodology, data curation, formal analysis, validation, investigation, visualization, and writing.
Historical Blame and Collective Responsibility
Understanding why people hold present-day groups responsible for past harms.
Role: Coauthor.
Founder project
MemwaMind
MemwaMind is an evidence-backed workspace for tax and accounting firms, designed to help professionals organize client knowledge, review documents, and prepare source-grounded work.
MemwaMind is currently being built and is presented here as a founder-led direction, not a product launch.
Open the source behind a claim.
Reviewing what a client has already sent.
Public record
Public sources behind the work.
Public pages and scholarly records show the training, research, and institutional context behind the work.
New Tools for Studying Bias and Belief
New Tools for Studying Bias and Belief
IPR coverage of the Social Cognition methods article.
IPR coverage of Jonathan's Social Cognition article on unsupervised machine learning methods for social cognition.
Open public page
Why Reform Stalls: Justification and Outrage as Competing Public Responses to Police Violence
Why Reform Stalls: Justification and Outrage as Competing Public Responses to Police Violence
IPR working paper source page, WP-25-31.
Public IPR working paper page for Jonathan's two-study project on justification, outrage, and reform discourse around police violence.
Open public page
TGS Spotlight: Jonathan Doriscar
TGS Spotlight: Jonathan Doriscar
TGS spotlight directory credential source.
Northwestern's Graduate School spotlight directory lists Jonathan as a PhD Candidate in Social Psychology and Master's Student in Data Science & Statistics.
Open public page
Selected publications and recognition
Selected publications and recognition.
From Data to Discovery: Unsupervised Machine Learning’s Role in Social Cognition
Social Cognition, 2025
Why Reform Stalls: Justification and Outrage as Competing Public Responses to Police Violence
Northwestern Institute for Policy Research Working Paper Series, WP-25-31, 2025
When the Specter of the Past Haunts Current Groups: Psychological Antecedents of Historical Blame
Journal of Personality and Social Psychology, 2024
Assessing How Energy Companies Negotiate with Landowners When Obtaining Land for Hydraulic Fracturing
Nature Energy, 2024
Recognition
Funding and honors.
National Science Foundation Graduate Research Fellowship
Competitive graduate fellowship supporting Jonathan's research training and work.
Edward Bouchet Graduate Honor Society Scholar
Honor recognizing scholarly achievement and broader commitments in graduate education.
Writing preview
Writing coming soon
Public essays on cognition, computation, product thinking, and careful research practice will live here.
Contact
Get in touch.
Reach out for research, data science, applied AI, product, or founder conversations.