PhdFit
Resume-aware faculty matching

Find professors who actually fit you

Review faculty evidence in public, then use the workspace to turn your background into a shortlist, outreach, and meeting prep.

Profile-awarePaper evidenceSix agents
Talia Konkle

Talia Konkle

· Professor of Psychology

Harvard University · Human Development and Psychology

Active 2006–2026

h-index32
Citations7.4k
Papers212104 last 5y
Funding$818k1 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

Faculty pageLab page
See your match with Talia Konkle — sign in to PhdFit.Sign in

About

Professor Talia Konkle leads the Konkle Lab at Harvard University, where her research broadly aims to understand how humans see and represent the world around them. Her work focuses on the organization of the human visual system and the biological constraints that guide this organization. She investigates how vision interfaces with action demands to enable interaction with the environment, as well as with conceptual representation to facilitate learning through visual experience. The lab's approach is grounded in the premise that the brain's connections are shaped by powerful biological constraints, making the spatial distribution of different types of information in the brain meaningful and informative about the system's representational goals. This perspective emphasizes the experience and needs of an active observer, deepening understanding of how behavioral capacities are embedded in the brain's local and long-range architecture, and how neural networks internalize the statistics of visual experience and the consequences of actions to realize functional visual representations.

Research topics

  • Artificial Intelligence
  • Computer Science
  • Machine Learning
  • Psychology
  • Cognitive psychology
  • Neuroscience
  • Cognitive science
  • Biology
  • Ecology
  • Management science

Selected publications

  • The neuroconnectionist research programme

    Nature reviews. Neuroscience · 2023 · 227 citations

    PublisherOA PDFDOI

  • A self-supervised domain-general learning framework for human ventral stream representation

    Nature Communications · 2022 · 136 citations

    1st authorCorresponding

    Anterior regions of the ventral visual stream encode substantial information about object categories. Are top-down category-level forces critical for arriving at this representation, or can this representation be formed purely through domain-general learning of natural image structure? Here we present a fully self-supervised model which learns to represent individual images, rather than categories, such that views of the same image are embedded nearby in a low-dimensional feature space, distinct…

    DOI

  • Sociality and interaction envelope organize visual action representations

    Nature Communications · 2020 · 81 citations

    Senior authorCorresponding

    Humans observe a wide range of actions in their surroundings. How is the visual cortex organized to process this diverse input? Using functional neuroimaging, we measured brain responses while participants viewed short videos of everyday actions, then probed the structure in these responses using voxel-wise encoding modeling. Responses are well fit by feature spaces that capture the body parts involved in an action and the action's targets (i.e. whether the action was directed at an object, anot…

    DOI

  • A large-scale examination of inductive biases shaping high-level visual representation in brains and machines

    Nature Communications · 2024-10-30 · 74 citations

    articleOpen accessSenior authorCorresponding

    The rapid release of high-performing computer vision models offers new potential to study the impact of different inductive biases on the emergent brain alignment of learned representations. Here, we perform controlled comparisons among a curated set of 224 diverse models to test the impact of specific model properties on visual brain predictivity - a process requiring over 1.8 billion regressions and 50.3 thousand representational similarity analyses. We find that models with qualitatively diff…

    PublisherOA PDFDOI

  • What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines?

    bioRxiv (Cold Spring Harbor Laboratory) · 2022 · 68 citations

    Senior authorCorresponding

    Abstract The rapid development and open-source release of highly performant computer vision models offers new potential for examining how different inductive biases impact representation learning and emergent alignment with the high-level human ventral visual system. Here, we assess a diverse set of 224 models, curated to enable controlled comparison of different model properties, testing their brain predictivity using large-scale functional magnetic resonance imaging data. We find that models w…

    DOI

Recent grants

Frequent coauthors

  • George A. Alvarez

    65 shared

  • Bria Long

    30 shared

  • Aude Oliva

    Massachusetts Institute of Technology

    29 shared

  • Emilie Josephs

    Massachusetts Institute of Technology

    21 shared

  • Jacob S. Prince

    Harvard University

    21 shared

  • Arturo Deza

    Massachusetts Institute of Technology

    19 shared

  • Timothy F. Brady

    18 shared

  • Alfonso Caramazza

    Harvard University

    16 shared

Education

  • B.A., Psychology

    University of California, Berkeley

    2005

  • M.A., Psychology

    University of California, Berkeley

    2007

  • Ph.D., Psychology

    University of California, Berkeley

    2011

Similar researchers at Harvard University

  • Resume-aware match score
  • Save to shortlist
  • AI-drafted outreach

See your match with Talia Konkle

PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.

Sign in to PhdFitHow it works
  • Free to start
  • No credit card
  • 30-second signup