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ayesha_shahid17

AYESHA SHAHID

@ayesha_shahid17

ML Researcher, Healthcare AI, RAG and LLM Apps, Springer Published

Paquistão
Inglês, Urdu
Algumas informações são exibidas no idioma inglês.
Sobre mim
Published ML researcher (Springer Nature, 2026) specializing in healthcare AI, RAG applications, and production ML systems. I've trained 15+ model architectures, including BiLSTM, CNN, XGBoost, and LLMs across medical and NLP domains. I build RAG apps with LangChain and FAISS, ML pipelines with FastAPI and Docker, and deep learning models for classification and prediction. Every delivery is clean, documented, and production-ready, not just a notebook.... Saiba mais

Habilidades

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ayesha_shahid17
AYESHA SHAHID
offline • 
Tempo médio de resposta: 1 hora

Conheça meus serviços

Integrações de IA
I will build and deploy a production rag system
A partir deUS$ 90 /projetoMais detalhes

Experiência profissional

Self_Employed

Machine Learning Researcher

Self Employed • Autônomo

Dec 2023 - Present • 2 yrs 6 mos

Conducted supervised machine learning and deep learning research for clinical prediction and decision support systems across multiple medical domains, including diabetes, brain tumor detection, ASD classification, and cardiovascular disease risk. Published first-author research in the International Journal of Diabetes in Developing Countries (Springer Nature, 2026). Developed a stacked BiLSTM Decision Support System achieving 96% accuracy and 100% sensitivity on an independent clinical test set, outperforming all traditional ML and deep learning baselines. Built and deployed production ML systems, including a Diabetes Risk Prediction API (XGBoost + Random Forest ensemble, FastAPI, Docker) and a Medical RAG Assistant (LangChain, FAISS, Llama-3.3-70B, Streamlit), both live on HuggingFace Spaces. Trained and evaluated 15+ model architectures, including BiLSTM, LSTM, CNN-LSTM Hybrid, XGBoost, Random Forest, SVM, KNN, VGG16, ResNet50, and Explainable Boosting Machines across medical imaging, NLP, and tabular domains.