projects

During my career, I worked on many different projects. Below you see the selected ones. You WILL SEE REPEATED PROJECTS AS THEY WERE TAGGED BY CATEGORY.

Generative AI
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Advanced RAG & Flow Enginering

AI-powered social knowledge graph, integrating LLMs, RAG, and clustering pipelines to connect and recommend rare disease specialists.
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Biomedical Language Model

LLM-powered rare disease recognition from NIH-funded research using BioMedBERT, fine-tuned transformers, and graph analytics in Neo4j.
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Agentic AI HotelBot

AI-powered virtual concierge for luxury hotels using GPT, LangGraph agents, LlamaIndex, FastAPI, Redis, and Neon PostgreSQL. Supports room booking, FAQ search, and real-time availability. Deployed via Docker on Hugging Face and AWS ECS.
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Target Deconvolution

Generative AI-enhanced biomedical discovery using LLM fine-tuning, and phenotypic screening.
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It Can Be Our Project!

A collaborative AI-driven initiative tackling real-world challenges.

Extract Transform Load (ETL)
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Adverse Drug Event

ETL-Driven Knowledge Graph Construction for Improving Drug Safety and Pharmacovigilance in Rare Diseases
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Advanced RAG & Flow Enginering

AI-powered social knowledge graph, integrating LLMs, RAG, and clustering pipelines to connect and recommend rare disease specialists.

Natural Language Processing
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Media Resilience

Leveraged large-scale Twitter data, machine learning, and NLP techniques to quantify and compare social–psychological resilience across five countries.
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Community Resilience

AI-driven disaster resilience modeling through NLP, social sensing, and critical infrastructure data integration.
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Advanced RAG & Flow Enginering

AI-powered social knowledge graph, integrating LLMs, RAG, and clustering pipelines to connect and recommend rare disease specialists.
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Biomedical Language Model

LLM-powered rare disease recognition from NIH-funded research using BioMedBERT, fine-tuned transformers, and graph analytics in Neo4j.
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Target Deconvolution

Generative AI-enhanced biomedical discovery using LLM fine-tuning, and phenotypic screening.

Healthcare Data Science
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Adverse Drug Event

ETL-Driven Knowledge Graph Construction for Improving Drug Safety and Pharmacovigilance in Rare Diseases
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Thyroid Follow-Up Study

Thyroid Nodule Progression Analysis Using IBM MarketScan and Azure Databricks.
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Advanced RAG & Flow Enginering

AI-powered social knowledge graph, integrating LLMs, RAG, and clustering pipelines to connect and recommend rare disease specialists.
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Biomedical Language Model

LLM-powered rare disease recognition from NIH-funded research using BioMedBERT, fine-tuned transformers, and graph analytics in Neo4j.
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EMS Response

Data-Driven Insights into EMS Response and Outcomes using NEMSIS (2017–2021).
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Target Deconvolution

Generative AI-enhanced biomedical discovery using LLM fine-tuning, and phenotypic screening.

Energy Data Science
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Community Resilience

AI-driven disaster resilience modeling through NLP, social sensing, and critical infrastructure data integration.
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Energy market

Multi-Carrier Energy Market Optimization & Bayesian Uncertainty Quantification
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SmartGridGuard

Real-Time Anomaly Detection and Insulation Coordination in Power Transmission Networks