Shreya Kapoor

Shreya Kapoor

Researcher @FAU Erlangen, Germany | Former Data Analyst at Max Planck Institute for Human Cognitive and Brain Sciences | BSc.(H) Physics and M.Sc. Life Science Informatics.

Posts by Collection

portfolio

Awards

Published:

  1. STIBET 1 Scholarship for international students (July-Nov. 2020), awarded by DAAD and the German Foreign Office to support my master’s thesis.
  2. 1st position at BR41N.io Designer’s Hackathon, Data Analysis for a project on EcoG Hand Pose Estimation (29-30 Apr. 2022).
  3. Golden Jubilee Award of Excellence in Sciences, Miranda House, University of Delhi (2018).
  4. Professor Savitri G Burman Award, Miranda House, University of Delhi (2017).
  5. G.Bhaskar Memorial Award, Delhi Public School RK Puram (2014).
  6. Gold medal for academic excellence, Delhi Public School RK Puram (2014).
  7. Red Tie for excellence in the field of technology, Delhi Public School RK Puram (2014).

Additional Training Courses

Published:

  1. High-Performance Data Analytics I, GWDG (20-21 Mar. 2022)
  2. NVIDIA GPU Programming Bootcamp organized in cooperation with Max Planck Computing Faculty (19-20 Oct. 2021) View Certificate
  3. Python for High-Performance Computing organized by Max Planck Computing Faculty (5-7 Oct. 2021)
  4. Sage Days 100, Department of Informatics, University of Bonn (22 July 2019-27 July 2019)

Conferences and Memberships

Published:

  1. Member, Women in Machine Learning Society (2023, 2024), sponsored by WiML for attending ICLR 2023.
  2. Member, Cognitive Science Society (2023, 2024) and reviewer, Cognitive Science Society (2024).
  3. Attendee and Poster Presenter, Cognitive Science Society meeting 26-29 July 2023 link to the poster presentation is here: mooney faces.
  4. Attendee and Presenter Graphics Vision and Machine Learning graphics.
  5. Poster Presentation Neuro AI talks in Osnabrück, organized by Tim Keatzmann Lab (2023).
  6. Attendee, at the International Symposium on Vision, Modeling, and Visualization (VMV).
  7. Presented a poster at the ICLR 2025 Re-Align workshop on the paper titled ‘Computer Graphics from a Neuroscientist’s perspective’
  8. Will be attending the M2L summer school in Split Croatia.

Reviewing Experience

Published:

  1. CogSci 2023
  2. CogSci 2024
  3. CogSci 2025
  4. Unireps workshop, Neurips 2024
  5. ACVSS 2025 (reviewed applications for the summer school)
  6. ICMI 2025 (3 papers reviewed)
  7. Unireps workshop 2025, Neurreps workshop 2025

posters

publications

A meta-analysis of mental rotation in the early years of life

Published in Developmental Science Journal, 2023

Mental rotation, the cognitive process of moving an object in mind to predict how it looks in a new orientation, is coupled to intelligence, learning, and educational achievement. On average, adolescent and adult males solve mental rotation tasks slightly better (i.e., faster and/or more accurate) than females. When such behavioral differences emerge during development, however, remains poorly understood. Here we analyzed effect sizes derived from 62 experiments conducted in 1705 infants aged 3–16 months. We found that male infants recognized rotated objects slightly more reliably than female infants. This difference survives correction for small degrees of publication bias. These findings indicate that gender differences in mental rotation are small and not robustly detectable in the first months of postnatal life

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Perception of Mooney Faces: Extreme Generalization through Inverse Rendering?

Published in Cognitive Science Society, 2023

Humans can successfully interpret images even when significant image transformations have distorted them. Such images aid in differentiating existing computational models for perception because models that predict similar results for typical stimuli may diverge when confronted with atypical stimuli. We propose an explanation of people’s ability to perceive a specific class of degraded stimuli that require extreme generalization capabilities: Mooney, or two-tone images of faces.

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Processing of scene intrinsics in the ventral visual stream for object recognition

Published in Cognitive Science Society, 2023

A hallmark of human vision is the ability to rapidly recognize objects in a complex naturalistic scene. However, the exact mechanisms behind the computational invariance of object recognition remain unknown. In this study, we investigate object constancy by estimating how the ventral visual stream processes shading, shadows, textures, and specularities.

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Building an Image Database with Searchable Metadata

Published in Computational Life Sciences - Data Engineering and Data Mining for Life Sciences, 2023

This chapter describes the process of building an Image Database with searchable metadata. Searching for an image greatly benefits from having useful metadata to accompany it. The proposed solution allows the user to save the picture together with its online location (url) and suitable metadata. The application then saves both the picture and its metadata in a SQLite database. This database can be queried and is accessible via a RESTful API service.

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Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders

Published in Journal of Biological Psychiatry, 2023

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. This review summarizes findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders.

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AMOR: Ambiguous Authorship Order

Published in SIGBOVIK 2024, 2024

This paper addresses the contentious issue of author ordering in scientific publications. The authors propose AMOR, a probabilistic system that randomly shuffles the author list each time a paper is viewed, eliminating distinctions such as co-first or co-middle authorship. Presented at SIGBOVIK 2024.

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When Large Language Models are More Persuasive Than Incentivized Humans, and Why

Published in arXiv preprint arXiv:2505.09662, 2025

This study compares the persuasiveness of large language models (Claude 3.5 Sonnet and DeepSeek v3) against incentivized human persuaders in real-time conversations. Results show that LLM persuasive superiority is context-dependent, varying with the truthfulness of persuasion attempts, the model used, and diminishing with repeated interactions.

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Computer Graphics from a Neuroscientist’s Perspective

Published in Second Workshop on Representational Alignment at ICLR 2025, 2025

A hallmark of human vision is to recognize objects in complex naturalistic scenes. This study proposes a tool to investigate human perception by using a computer graphics approach, using three-dimensional object meshes to render synthetic scenes and study how these scenes are represented in the brain.

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talks

teaching

Teaching Assistantship

Graduate Course, Bonn Aachen International Center for Information Technology, 2020

Summer Semester 2020

Intern Supervision

Graduate intern, Max Planck Institute of Human Cognitive and Brain Sciences, Leipzig, Germany, 2022

I supervised Elizaveta Ivanova, M.Sc., HSE University for a period of two months to work on application development for questionnares in Cognitive Neuroscience.

Teaching Assistantship

Graduate Course, Friedrich-Alexander-Universität Erlangen-Nüremberg, 2024

Winter Semester 2024
I held a lecture on Neuroimaging: An Overview for the course Computational Visual Perception under the supervision of Prof. Dr. Bernhard Egger.