Researcher · Designer · Builder

I turn complex questions into clear ideas and useful work.

I'm Diya Gupta. My work brings together careful research, thoughtful experimentation, and a bias toward making things that help people understand the world differently.

Selected work

Research with a point of view.

A flexible home for the projects that best represent how you think, what you notice, and what you contribute.

Mapping similarity to false memory

A computational cognitive-science study testing which representation of similarity best predicts when people remember words they never saw.

  • Cognitive science
  • NLP
  • ASI / ISEF
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A study that changed your perspective

Use this space to connect a rigorous process to a clear insight. Lead with the contribution, not the chronology.

  • Field study
  • Analysis
  • 2025
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An experiment, tool, or collaboration

Show the breadth of your practice with a project that bridges research and real-world application.

  • Experiment
  • Prototype
  • 2025
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Flagship research · ASI / ISEF

Research in progress

What makes a memory feel true?

In the Deese–Roediger–McDermott paradigm, people study a list of related words—such as bed, rest, and dream—then often remember a closely related word like sleep that was never shown. My research asks what kind of similarity best explains that effect.

Research question

Which representation of similarity best predicts published human false-recall and false-recognition rates across 55 DRM word lists when the memory equation is held fixed?

The approach

One memory model.
Six ways to define similarity.

Each DRM list contains 15 studied words and one unpresented “critical lure.” I calculate the similarity between every studied word and its lure, then compare six representational spaces under the same global-matching framework.

False recall and false recognition are treated as separate continuous outcomes. The final comparison will use held-out predictions and prespecified metrics—RMSE, MAE, Pearson correlation, and Spearman correlation—so each representation is evaluated on equal terms.

  1. 01Association strengthHow often one word brings another to mind
  2. 02Latent semantic analysisMeaning learned from patterns across documents
  3. 03Static word embeddingsGloVe geometry from large-scale language use
  4. 04Transformer embeddingsDistilBERT representations of the experimental words
  5. 05Phonological similarityHow much the words sound alike
  6. 06Orthographic similarityHow much their written forms overlap
55published DRM lists
825studied-word / lure pairs
2human-memory outcomes
6similarity representations

Writing & publications

Ideas, in public.

About

YOUR PHOTO

Curious by nature.
Rigorous by practice.

I'm a researcher interested in the space between evidence and action—how we ask better questions, make sense of complexity, and build more thoughtful futures.

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