Scholar
Andrew Drozdov
Google Scholar ID: RsU18o4AAAAJ
Research Scientist, Databricks
Citations & Impact
Citations
802
H-index
12
i10-index
14
Publications
20
Co-authors
18
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - Drowning in Documents: Consequences of Scaling Reranker Inference, Mathew Jacob, Erik Lindgren, Matei Zaharia, Michael Carbin, Omar Khattab, Andrew Drozdov, arXiv, 2024
- - Retrieval-Enhanced Machine Learning: Synthesis and Opportunities, Fernando Diaz, Andrew Drozdov, To Eun Kim, Alireza Salemi, Hamed Zamani, SIGIR-AP, 2024
- - Thesis: Unlocking Natural Language Generalization with Adaptive Retrieval-based Methods, Andrew Drozdov, 2024
- - ReDMM: Retrieval Driven Memory Manager, Andrew Drozdov, 2024
- Reviewed 100+ papers at top AI/IR/NLP conferences, as well as supervised many papers as AC and SAC.
Research Experience
- Current: Research Scientist @ Databricks; Previously at Google and IBM; TA: CS 685, CS 696DS; Organizer: Data Science Tea
Education
- PhD: UMass Amherst CICS, Advisors: Andrew McCallum, Mohit Iyyer; MS: NYU CS, Mentors: Samuel Bowman, Kyunghyun Cho
Background
- Broadly interested in neural network-related topics including training, inference, in-context learning, knowledge distillation, and evaluation. Most of his work has been in natural language processing and information retrieval. Particularly excited about the emerging field of generative retrieval.
Miscellany
- Email: andrew.drozdov@databricks.com
