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University of Oxford
Data Scientist
June 25, 2026 – Present
self_play_picard
December 7, 2021 – October 20, 2022
Using self-play to augment multi-turn text-to-SQL datasets
View ProjectSVAMP
March 11, 2021 – June 30, 2022
NAACL 2021: Are NLP Models really able to Solve Simple Math Word Problems?
View ProjectTransformer-Computation-Analysis
October 6, 2020 – October 10, 2020
CoNLL 2020: On the Computational Power of Transformers and its Implications in Sequence Modeling
View ProjectTransformer-Formal-Languages
October 6, 2020 – October 10, 2020
EMNLP 2020: On the Ability and Limitations of Transformers to Recognize Formal Languages
View ProjectDiPS
March 31, 2019 – March 16, 2024
NAACL 2019: Submodular optimization-based diverse paraphrasing and its effectiveness in data augmentation
View ProjectpyDPP
October 13, 2018 – October 28, 2018
A python package for sampling from determinantal point processes
View Projectlibnmf
December 21, 2017 – October 19, 2018
Optimization and Regularization variants of Non-negative Matrix Factorization (NMF)
View ProjectReview-Miner
February 6, 2016 – June 3, 2017
A cross platform application for e-commerce product analysis
View ProjectCultural Fit Analysis
The candidate's profile shows a strong academic and research background, with numerous personal projects related to NLP and machine learning. This aligns well with roles requiring deep technical investigation and problem-solving. However, the lack of diverse project types (e.g., industry applications, team projects beyond academic collaborations) might indicate a need for adaptation to a more product-focused or collaborative industry environment. The current experience at the University of Oxford as a Data Scientist is a positive indicator of role alignment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a strong research focus and ability to contribute to academic publications.