Dr. Christopher Manning: A professor at Stanford, Manning’s work on deep learning approaches to NLP has been groundbreaking. His Stanford NLP Group has released several influential models and tools, and his courses on NLP are widely regarded.
Dr. Yoav Goldberg: Based at Bar-Ilan University, Goldberg’s research covers syntactic and morphological parsing and machine learning models for NLP. He’s known for his critical insights on deep learning techniques in NLP.
Dr. Regina Barzilay: A professor at MIT, Barzilay’s work spans a range of NLP applications, from machine translation to developing algorithms that can predict disease onset from mammography images and patient narratives.
Dr. Emily Bender: A linguist by training and a professor at the University of Washington, Bender emphasizes the importance of linguistic knowledge in NLP. She’s also vocal about the ethical considerations in the field.
Jacob Devlin: As one of the minds behind BERT at Google, Devlin’s contributions have reshaped state-of-the-art benchmarks in various NLP tasks. BERT’s pre-training methodology is now a staple in modern NLP.
Dr. Kyunghyun Cho: Based at NYU, Cho’s work encompasses deep learning in NLP, especially sequence-to-sequence learning which powers machine translation, summarization, and more.
Dr. Ilya Sutskever: Co-founder and Chief Scientist at OpenAI, Sutskever’s work on sequence-to-sequence learning has been foundational for NLP. Under his lead, OpenAI launched GPT models, which are at the forefront of language generation tasks.
Dr. Graham Neubig: At Carnegie Mellon University, Neubig’s research touches on machine translation, speech processing, and more. He’s also known for developing several NLP tools and libraries.
Dr. Rachel Tatman: A data scientist at Kaggle, Tatman’s work on sociolinguistics and NLP bridges the gap between linguistic diversity and computational techniques. She’s also a strong advocate for inclusivity in AI.
Sebastian Ruder: A researcher at DeepMind, Ruder is known for his work on cross-lingual embeddings and transfer learning in NLP. His blog is a rich source of insights on recent NLP trends and developments.
