Akash Bharadwaj

Carnegie Mellon University , 2017
M.S. , Computer Science
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Bay Area



Akash's research interests span AI, cryptography, privacy and education. He is a published author whose work has been published and featured at premier venues such as ACL, EMNLP, COLING, AAAI and ICML. He now works on building privacy preserving AI tools and techniques to protect peoples' identities in an increasing connected and open world and to ensure privacy regulations are followed across various data regimes despite profit motives incentivizing the opposite.


Carnegie Mellon University

M.S. , Computer Science

Class of 2017

Awards & Publications

2016 Phonologically Aware Neural Model for Named Entity Recognition in Low Resource Transfer Settings, EMNLP 2016
2020 To Test Machine Comprehension, Start by Defining Comprehension!, ACL 2020
2016 PanPhon: A Resource for Mapping IPA Segments to Articulatory Feature Vectors, COLING 2016
2017 Dravidian language classification from speech signal using spectral and prosodic features, International Journal of Speech Technology 2017
2016 Cross Modal Content Based Objective for Learning Adequate Multimodal Representations, ICML MVRL Workshop, 2016
2016 From Insights to Interventions: Informed Design of Discussion Affordances for Natural Collaborative Exchange, AAAI 2016 Spring Symposium
2014 Pre- dicting student learning from conversational cues, In International Conference on Intelligent Tutoring Systems, 2014

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