Alice Zhang

ORCID: 0009-0005-5037-0995
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About
Contact & Profiles
Research Areas
  • Design Education and Practice
  • AI-based Problem Solving and Planning
  • Music Technology and Sound Studies
  • Music and Audio Processing
  • Diabetes Treatment and Management
  • Authorship Attribution and Profiling
  • Education and Critical Thinking Development
  • Innovative Teaching and Learning Methods
  • Public Relations and Crisis Communication
  • Robotic Path Planning Algorithms
  • Natural Language Processing Techniques
  • Explainable Artificial Intelligence (XAI)
  • Metabolism, Diabetes, and Cancer
  • Robot Manipulation and Learning
  • Sentiment Analysis and Opinion Mining
  • Computational and Text Analysis Methods
  • Misinformation and Its Impacts
  • Neuroscience, Education and Cognitive Function
  • Topic Modeling

Massachusetts Institute of Technology
2023-2025

Harvard University Press
2023

Hearing4all
2017

31 Degrees (France)
2017

Korea Advanced Institute of Science and Technology
2017

Nanyang Technological University
2017

University of Strathclyde
2017

University of Huddersfield
2017

Princeton University
2014

By building a mental model of how the world works and using it to forecast outcomes different actions, learner can make flexible choices in changing environments. However, while children adolescents readily acquire structured knowledge about their environments, relative adults, they tend demonstrate weaker signatures leveraging this plan actions. One explanation for these developmental differences is that prospectively simulate potential computationally costly, taxing cognitive control...

10.31234/osf.io/y3dzn preprint EN 2025-01-20

By building a mental model of how the world works and using it to forecast outcomes different actions, learner can make flexible choices in changing environments. However, while children adolescents readily acquire structured knowledge about their environments, relative adults, they tend demonstrate weaker signatures leveraging this plan actions. One explanation for these developmental differences is that prospectively simulate potential computationally costly, taxing cognitive control...

10.31234/osf.io/y3dzn_v2 preprint EN 2025-01-29

By building a mental model of how the world works and using it to forecast outcomes different actions, learner can make flexible choices in changing environments. However, while children adolescents readily acquire structured knowledge about their environments, relative adults, they tend demonstrate weaker signatures leveraging this plan actions. One explanation for these developmental differences is that prospectively simulate potential computationally costly, taxing cognitive control...

10.31234/osf.io/y3dzn_v1 preprint EN 2025-01-20

Children are adept statistical learners, capable of parsing streams structured input into meaningful units, but the explicit knowledge environmental structure that they acquire through experience often differs from adults. To date, however, it is unclear how developmental changes in learning mechanisms influence acquisition. address this question, we tested 110 children, adolescents, and adults, ages 8 - 22 years, on a predictive task, which experienced sequences stimuli with higher-order...

10.31234/osf.io/amvth_v1 preprint EN 2025-03-06

Humans are remarkably efficient at decision-making, even in "open-ended'' problems where the set of possible actions is too large for exhaustive evaluation. Our success relies, part, on processes calling to mind and considering right candidate When this process fails, however, result a kind cognitive puzzle which value solution or action would be obvious as soon it considered, but never gets considered first place. Recently, machine learning (ML) architectures have attained exceeded human...

10.31234/osf.io/jqhac preprint EN 2023-08-01
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