Scholar
John Thickstun
Google Scholar ID: RkuzIZMAAAAJ
Assistant Professor, Cornell University
Citations & Impact
Citations
2,700
H-index
15
i10-index
17
Publications
20
Co-authors
19
list available
Publications
Cited
0
Resume (English only)
Academic Achievements
- - Published paper 'Robust distortion-free watermarks for language models' in TMLR
- - Developed AI music creation tool Aria
- - Wrote blog posts on co-composing music using the Anticipatory Music Transformer
- - Responded to NSF’s Request for Information on the White House’s Development of an AI Action Plan
Research Experience
- - Assistant Professor at Cornell University (starting Fall 2024)
- - Previously a Postdoctoral Scholar at Stanford University
- - Involved in multiple research projects such as Anticipatory Music Transformer, Watermarking LLMs, etc.
Education
- - Postdoctoral Scholar at Stanford University, advised by Percy Liang
- - Ph.D. in the Allen School of Computer Science & Engineering at the University of Washington, co-advised by Sham Kakade and Zaid Harchaoui
- - Undergraduate in Applied Mathematics at Brown University, advised by Eugene Charniak and Björn Sandstede
Background
- Research interests include machine learning and generative models. Focuses on methods that control the behavior of models, both from the perspective of a user who hopes to use a model to accomplish concrete tasks, and from the perspective of a model provider or policymaker who hopes to broadly regulate the outputs of a model. Also interested in applications of generative models that push beyond the standard text and image modalities, including music technologies.
Miscellany
- - Has a strong interest in music technology and has developed related tools and techniques
