Research scientist | Image Analyst | Machine Learning | Computer Vision | Deep Learning | AI | Bioinformatics | NLP & LLMs | Focused on advancing cancer diagnostics using computational methods, deep learning, and medical imaging analysis.
- Deep Learning for Medical Imaging
- Breast Cancer Classification
- Bioinformatics & Computational Biology
- Natural Language Processing & Large Language Models (LLMs)
- Explainable AI & Model Evaluation
- Ethical & Responsible AI
- Machine Learning, Deep Learning, Artificial Intelligence
- High-Dimensional Data Analysis & Feature Engineering
- Experimental Design & Statistical Analysis
- Reproducible Research & Benchmarking
- Cloud-based ML Systems & MLOps
- Languages & ML: Python, PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM
- NLP & LLMs: Large Language Models (LLMs), Prompt Engineering, SpaCy, NLTK
- Biomedical & Data Analysis: Pandas, NumPy, Biopython, Medical Image Preprocessing
- MLOps & Cloud: Docker, Kubernetes, AWS, GCP
- Tools: Git, GitHub, Jupyter Notebook, Google Colab
- Comprehensive Performance Evaluation of Deep Learning Models for Optimizing Breast Cancer Classification on Mammogram Datasets
- An Empirical Evaluation of Zero-Shot, Few-Shot, and Fine-Tuned Pretrained Language Models for Sentiment Analysis in Software Engineering
- A Comprehensive Review of Datasets and Preprocessing Techniques in Deep Learning-Based Breast Cancer Classification
- Respectful Social Engagement: Facebook Hate Speech Classification for Bengali Language
🔗 Google Scholar: Link
📌 3+ peer-reviewed publications
Deep learning-based breast cancer classification using mammogram datasets, focusing on preprocessing pipelines, model benchmarking, interpretability, and reproducibility.
Empirical evaluation of zero-shot, few-shot, and fine-tuned large language models for sentiment analysis, hate speech detection, and ethical AI applications.
- LinkedIn: Link
- Google Scholar: Link
- Email: asharmin.cs@gmail.com