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Assessing your cultural and operational fit
agentic-timeline-summarizer
February 19, 2026 – Present
agentic-timeline-summarizer — GitHub repository
View ProjectAURA
August 2, 2025 – December 9, 2025
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models
View ProjectMemeSense
February 16, 2025 – Present
Accepted at Transaction of Machine Learning Research (TMLR)
View Projectwikipedia_enrichment
February 5, 2024 – August 18, 2025
Codebase for the COLING2025 paper REVerSum: A Multi-staged Retrieval-Augmented Generation Method to Enhance Wikipedia Tail Biographies through Personal Narratives
View ProjectContext_based_Quote_Extraction
December 5, 2023 – March 17, 2024
Codebase for the paper (Accepted at COLING2025 main): RA-MTR: A Retrieval Augmented Multi-Task Reader based Approach for Inspirational Quote Extraction from Long Documents
View ProjectAnnotator-Analysis-HateXplain
April 15, 2021 – February 23, 2023
Term Project in AI & Ethics course to analyse annotator influences in a rationale annotated dataset
View ProjectCS60075-Team-2-Task-1
April 9, 2021 – January 6, 2022
SemEval Task 1 - Lexical Complexity Prediction
View ProjectEvent-Timeline-Generation-from-Documents
December 11, 2020 – August 11, 2022
Code and Dataset for our ECML-PKDD paper
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic research and personal projects, primarily in Natural Language Processing and Machine Learning. While this aligns well with a Data Scientist role focused on research and development, the lack of diverse project types (e.g., industry applications, team projects beyond academic collaborations, full-stack development) might indicate a narrower scope of experience in broader software engineering practices or cross-functional team environments. The absence of work experience makes it difficult to assess adaptability to different organizational cultures.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong research-oriented mindset and the ability to contribute to cutting-edge AI/ML problems. However, without psychometric test results or interview data, it is difficult to assess soft skills like teamwork, communication, or stress handling. The focus on personal projects suggests self-motivation and initiative.