Scholar
Soroush Vosoughi
Google Scholar ID: 45DAXkwAAAAJ
Associate Professor of Computer Science, Dartmouth. Ex Postdoc/PhD at MIT. Ex fellow at Harvard
Citations & Impact
Citations
14,977
H-index
31
i10-index
73
Publications
20
Co-authors
171
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- Google Research Scholar Award (2022)
- Amazon Research Award (2019)
- Outstanding Paper Award at AAAI 2021
- Multiple best paper awards and nominations
- Research funded by NSF and NIH
- Industry grants from Google and Amazon
- Grants from Institute for Humane Studies and John Templeton Foundation
Research Experience
- Currently Associate Professor of Computer Science at Dartmouth
- Former postdoctoral associate at MIT
- Former fellow and later affiliate at the Berkman Klein Center, Harvard University
- Served as Technical Director of the 'Electome' project at MIT, developing tools to analyze election-related Twitter content; became an official partner of the Commission on Presidential Debates in 2016
- Technical advisor to Public Mind (formerly Because Humanity), 2021–2023
- Technical advisor to Cortico, 2016–2019
- Technical Associate Director at Dartmouth's Center for Precision Health and AI (CPHAI)
- Faculty member at Dartmouth's Institute for Security, Technology, and Society (ISTS)
- Affiliate faculty in Dartmouth’s QSS, QBS, and Arthur L. Irving Institute for Energy & Society
Background
- Associate Professor of Computer Science at Dartmouth College
- Leads the Minds, Machines and Society research group
- Research focuses on natural language processing (NLP) and machine learning
- Aims to understand and mitigate anti-social tendencies in large language models (LLMs), such as stereotypes, toxicity, and misalignment with human values
- Develops interpretability methods to demystify the 'black box' nature of LLMs
- Explores reinforcement learning for guiding pre-trained LLMs and grounding them via simulations
- Builds computational tools using LLMs and classical NLP to study social phenomena like political polarization, bias, propaganda, rumors, and hate speech (computational social science)
- Recently expanded research to visual-language models for richer cognitive modeling
- Applies LLMs to health and bioinformatics, drawing parallels between genomic sequences and language
