Asma Ghandeharioun
Asma Ghandeharioun, Ph.D., is a senior research scientist with the People + AI Research team at Google DeepMind. She works on aligning AI with human values through better understanding and controlling (language) models, uniquely by demystifying their inner workings and correcting collective misconceptions along the way. While her current research is mostly focused on machine learning interpretability, her previous work spans conversational AI, affective computing, and, more broadly, human-centered AI. She holds a doctorate and master’s degree from MIT and a bachelor’s degree from the Sharif University of Technology. She has been trained as a computer scientist/engineer and has research experience at MIT, Google Research, Microsoft Research, Ecole Polytechnique Fédérale de Lausanne (EPFL), to name a few.
Her work has been published in premier peer-reviewed machine learning venues such as ICLR, NeurIPS, ICML, EMNLP, AAAI, ACII, and AISTATS. She has received awards at NeurIPS and her work has been featured in Wired, Wall Street Journal, and New Scientist.
For more details, visit her personal page.
Her work has been published in premier peer-reviewed machine learning venues such as ICLR, NeurIPS, ICML, EMNLP, AAAI, ACII, and AISTATS. She has received awards at NeurIPS and her work has been featured in Wired, Wall Street Journal, and New Scientist.
For more details, visit her personal page.
Authored Publications
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DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
Chun-Liang Li
Brian Eoff
Rosalind Picard
International Conference on Learning Representations (ICLR) (2022)
Human-centric dialog training via offline reinforcement learning
Judy Hanwen Shen
Craig Ferguson
Agata Lapedriza
Noah Jones
Shixiang Gu
Rosalind Picard
Empirical Methods in Natural Language Processing (EMNLP) (2020)
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Brian Eoff
Rosalind Picard
ICCV Workshop on Interpreting and Explaining Visual Artificial Intelligence Models (2019)