Aakriti Kumar
Scholar

Aakriti Kumar

Google Scholar ID: XFM1ItgAAAAJ
Postdoctoral Researcher, Kellogg School of Management, Northwestern University
Computational Social ScienceHuman-Machine InteractionCognitive Science
Citations & Impact
All-time
Citations
563
 
H-index
8
 
i10-index
7
 
Publications
20
 
Co-authors
16
list available
Resume (English only)
Academic Achievements
  • Defended PhD thesis titled ‘Human Mental Models of Self, Others, and AI Agents’ in March 2024. Published paper 'The Calibration Gap between Model and Human Confidence in Large Language Models' in January 2024. Paper 'When Do Drivers Intervene In Autonomous Driving? Contrasting Drivers’ Perceived Risk Across Two Mobility Types' accepted for publication as a Late Breaking Report at Human-Robot Interaction 2023 in January 2023. Two papers published in Computational Brain & Behavior and NPJ Science of Learning in October 2022. Paper 'An Empirical Investigation of Reliance on AI-Assistance in a Noisy-Image Classification Task' accepted for publication as a full paper at HHAI 2022 in March 2022. Awarded fellowship by the Irvine Initiative in AI, Law, and Society for 2022 in December 2021.
Research Experience
  • Since August 2024, Postdoctoral Researcher at Kellogg School of Management and Northwestern Institute on Complex Systems (NICO), working with Dr. Matt Groh on developing AI tools for empathic communication and synthetic media detection. Most of 2023 as a Human-Computer Interaction Intern at Motional, advised by Dr. Krysta Chauncey. Summer 2022 internship at Honda Research Institute, hosted by Dr. Kumar Akash.
Education
  • PhD in Cognitive Science from the University of California, Irvine, advised by Dr. Mark Steyvers; Master’s degree in Statistics from UCI; B.Tech. in Engineering from IIT Madras, India.
Background
  • Research interests lie at the intersection of cognitive science and human-computer interaction. Gains insight into humans’ mental models of AI by designing robust behavioral experiments and developing computational cognitive models.
Miscellany
  • Motivated to bridge the gap between theoretical research and practical applications. Brings a unique interdisciplinary skill-set, making well-suited to undertake research at the intersection of social science and artificial intelligence.