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Assessing your cultural and operational fit
Hate-Speech-Detection-and-Target-Identification-in-Devanagari-Languages
December 5, 2024 – December 5, 2024
Code for Parameter Efficient Fine-Tuning of LLMs for Hate Speech Detection and Target Identification in Devanagari Languages
View Projectevidence-backed-fact-checking-using-rag-and-few-shot-in-context-learning-with-llms
August 15, 2024 – October 4, 2024
Official Repository of the paper Evidence-backed Fact Checking using RAG and Few-Shot In-Context Learning with LLMs
View ProjectPose-Estimation-and-Object-Detection
February 9, 2024 – February 9, 2024
Pose-Estimation-and-Object-Detection — GitHub repository
View ProjectECE239_CI_rPPG
February 27, 2022 – March 10, 2022
Class project for UCLA ECE239 Computational Imaging (Course Instructor - Dr. Achuta Kadambi)
View ProjectGenomic_Imputation_using_Deep_Learning
November 28, 2021 – December 18, 2021
Genomic_Imputation_using_Deep_Learning — GitHub repository
View ProjectCan-Self-Reported-Symptoms-Predict-Daily-COVID-19-Cases
June 21, 2021 – June 21, 2021
Official code for the paper 'Can Self Reported Symptoms Predict Daily COVID-19 Cases?'
View Projectcovid19-fake-news-detection
October 31, 2020 – April 30, 2021
Official repository for data set and baselines for covid19 fake news data.
View ProjectTRAC-2
February 27, 2020 – October 29, 2020
Our system for TRAC-2 shared task on aggression identification
View ProjectCultural Fit Analysis
The candidate's projects are predominantly academic or personal research-oriented, focusing on specific NLP/ML problems. While this demonstrates initiative and technical interest, the lack of diverse project types (e.g., industry applications, open-source contributions beyond research papers, team projects) and limited information on work experience makes it difficult to fully assess cultural fit for a typical industry Data Scientist role. The projects align well with research-heavy data science roles.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, communication, or problem-solving approaches in a team setting.