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token-aware-hybrid-search
November 4, 2025 – December 6, 2025
PGTS with the SPAWN operation to enhance Qwen3b's reasoning in math domains
View ProjectMetaphorsOfMachine
April 30, 2025 – May 8, 2025
MetaphorsOfMachine is a research project for analyzing how users metaphorically frame AI in conversations. The project uses natural language processing and machine learning techniques to extract semantic frames, detect metaphors, and analyze patterns across demographic dimensions.
View Projectllm_synth_boost
April 25, 2025 – August 12, 2025
Investigating the impact of synthetic data on LLM perplexity via QLoRA finetuning
View Projectllm-retrieve-rank
April 21, 2025 – May 14, 2025
Investigates LLM prompt‐driven query expansion and re‐ranking to boost IR on TREC‐COVID. Compares zero‐shot, few‐shot, and chain‐of‐thought expansion with hybrid BM25 + dense retrieval. Adds LLM re‐ranking with natural explanations vs. cross‐encoder baselines, and extends to live web QA.
View ProjectIterative-Query-Refinement
March 19, 2025 – Present
In qualitative research, traditional random sampling may not capture the full diversity of large datasets. To address this, we propose an iterative query refinement pipeline that combines keyword and semantic search, keyword extraction, and query term optimization.
View ProjectMedical-Information-Retrieval
December 7, 2024 – December 7, 2024
Medical-Information-Retrieval — GitHub repository
View ProjectRetrieval-Augmented-Translation-with-Reflection
November 12, 2024 – November 28, 2024
Retrieval-Augmented-Translation-with-Reflection — GitHub repository
View ProjectScientific-Document-Summarization
September 23, 2022 – September 23, 2022
Scientific-Document-Summarization — GitHub repository
View ProjectAIML-Workshop
April 14, 2021 – October 28, 2021
Workshop for AIML covering introduction to python, ML and DL
View ProjectPointer-Generator-Networks
February 26, 2021 – July 24, 2024
A pipeline that summarizes text using a hybrid model of extractive and abstractive text summarization techniques.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong focus on research and development within AI/ML, particularly NLP and LLMs. This aligns well with a Data Scientist role that involves innovation and complex problem-solving. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback are available.