A ML scientist who loves solving business problems with AI. My primary interest is Natural Language Processing (NLP) which I use to decrypt text for machines.
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UI-Screenshot-Classification-by-fine-tuning-CLIP
September 4, 2024 – September 4, 2024
This project implements a UI screenshot classification system by fine-tuning the OpenAI CLIP (Contrastive Language-Image Pre-Training) model. It classifies UI screenshots into 28 different app categories such as Sports, Travel, Dating, etc.
View ProjectMultimodal-Emotion-Recognition
June 25, 2024 – June 27, 2024
Multimodal-Emotion-Recognition — GitHub repository
View ProjectCustomer-Satisfaction-for-Airline-Travel
June 19, 2024 – June 19, 2024
The aim of this project is to analyze trends in customer feedback of airport and airline experiences.
View ProjectEmotion-Recognition-on-Accented-Speech-using-Domain-Adaptation
June 18, 2024 – June 18, 2024
The aim of this paper is to transfer a Speech Emotion Recognition (SER) model from standard English to Singaporean-accented English. We report on baselines and transfer experiments for the speech emotion recognition task on the MSP-Podcast and NSC speech datasets.
View ProjectQuestion-Answering-and-Question-Generation
June 18, 2024 – June 18, 2024
Question-Answering-and-Question-Generation — GitHub repository
View ProjectResearchPaper-NER
October 19, 2022 – October 29, 2022
ResearchPaper-NER — GitHub repository
View ProjectWord_Embeddings_with_PCA
October 25, 2018 – January 13, 2021
Word embeddings using PMI and PCA.
View ProjectLDA-Gibbs_Sampling
December 27, 2016 – June 18, 2024
Topic modeling using Latent Dirichlet Allocation and collapsed Gibbs Sampling in python 2.7
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic in nature, focusing heavily on research-oriented data science tasks. While this demonstrates initiative and technical curiosity, there is limited evidence of experience in collaborative, product-driven environments or diverse team settings. The 'team-19' project lists various web technologies, which suggests some breadth, but its description is generic. The overall fit for a typical industry 'Data Scientist' role, which often requires strong collaboration and business acumen, is moderate without further information.
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, problem-solving approaches, or communication style in a team setting.