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May 29, 2025 – November 4, 2025
EMNLP 2025 "LLMs are Better Than You Think: Label-Guided In-Context Learning for Named Entity Recognition"
View Projectsynthetic-clinical-qa
September 10, 2024 – December 9, 2024
ML4H 2024 Findings "Give me Some Hard Questions: Synthetic Data Generation for Clinical QA"
View Projectschema-to-json
May 23, 2023 – December 5, 2024
EMNLP 2024 Findings "Schema-Driven Information Extraction from Heterogeneous Tables"
View ProjectSynKB
February 11, 2022 – October 31, 2022
EMNLP 2022 Demo "SynKB: Semantic Search for Chemical Synthesis Procedures"
View ProjectProcBERT
August 26, 2021 – November 9, 2021
EMNLP 2021 "Pre-train or Annotate? Domain Adaptation with a Constrained Budget".
View Projecttextlabs-xwlp-code
February 25, 2021 – March 10, 2021
EACL 2021 "Process-Level Representation of Scientific Protocols with Interactive Annotation".
View ProjectPCNN-NMAR
March 6, 2019 – February 9, 2020
NAACL 2019 "Structured Minimally Supervised Learning for Neural Relation Extraction"
View ProjectPCNN-ATT-pytorch
December 19, 2018 – December 21, 2018
Pytorch reimplementation of PCNN-ATT model from Lin et. al. (2016)
View ProjectCSE5523MachineLearningProj
March 2, 2016 – April 25, 2016
Group Project for M. Belkin's CSE5523. Sentiment analysis theme.
View ProjectCultural Fit Analysis
The candidate's project history is exclusively focused on academic research and personal projects, primarily in NLP/ML. While this demonstrates strong technical depth, there is no information regarding experience in diverse team environments, industry-specific challenges, or cross-functional collaboration, which are often key aspects of cultural fit in a corporate Data Scientist role. The lack of professional experience or diverse project types limits the assessment of cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's profile primarily highlights technical research contributions without details on collaboration, communication, or project management in a team setting.