My Work
Machine Learning and AI
Expertise in developing AI solutions for real-time applications using supervised and unsupervised learning, CNNs, transformers, and generative models. Experience with tools like Python, PyTorch, Hugging Face, and Keras.
- Supervised & Unsupervised Learning
- Generative AI
- LLMs
- Transformers
Medical Imaging
Developed deep learning models for medical imaging, focusing on CT scan abnormality detection, improving polyp detection accuracy by 15%. Worked on synthetic image generation and 3D segmentation.
- 2D/3D Image Classification
- CT Scan Analysis
- CycleGAN for Synthetic Imaging
- Polyp Detection
Large Language Models (LLMs)
Hands-on experience in fine-tuning large language models for various applications such as text summarization, question answering, and dialogue generation. Proficient with Hugging Face, AWS SageMaker, and retrieval-augmented generation (RAG).
- LLM Lifecycle: Pre-training, Fine-tuning
- RAG and PEFT
- Transformers
Skills
Machine Learning & AI
- Supervised & Unsupervised Learning
- Neural Networks, CNNs, Transformers
- Generative Modeling
- Hyperparameter Tuning & Optimization
- Tools: PyTorch, TensorFlow, Keras, Hugging Face
Generative AI & LLMs
- Pre-training and Fine-tuning LLMs
- Text Generation, Summarization, Q&A
- Tools: Transformers, LangChain, AWS SageMaker
- Parameter-efficient Fine-tuning (PEFT)
- Retrieval-Augmented Generation (RAG)
Data Analytics & Processing
- Data Wrangling & Feature Engineering
- Exploratory Data Analysis (EDA)
- Data Visualization (Matplotlib, Seaborn, Power BI)
- Tools: Pandas, NumPy, SQL, Tableau
Image & Video Processing
- 2D/3D Image Classification & Segmentation
- Video Analysis
- Synthetic Image Generation (CycleGAN)
- Tools: OpenCV, scikit-image, PIL
Development & Deployment
- Building UIs with PySide, Gradio, PyQt
- Version Control with Git & GitHub
- Deploying using FastAPI, Docker, AWS EC2
About Me
I am a Ph.D. candidate in Electrical and Computer Engineering at the University of Louisville with expertise in machine learning, deep learning, and medical imaging. My work focuses on real-time AI solutions for healthcare and AI applications.
Download My Resume
Publications
- Multi-view network for colorectal polyps detection in CT colonography – ICIP24
- Affine Transform Recovery via Convolutional Neural Networks for Watermark Synchronization – Electronic Imaging 2024
- Accurate colon segmentation using 2D convolutional neural networks with 3D contextual information – ICIP 2024
- Colorectal Polyps Detection in Virtual Colonoscopy using 3D Geometric Features and Deep Learning – ISBI 2024
- An Automatic Colorectal Polyps Detection Approach For CT Colonography – ICIP 2023
- A Deep Learning Approach for Vehicle Detection – ICCES 2018
- A Novel Vehicle Detection System – ICCES 2018
Get in Touch
I'm available for AI, machine learning, computer vision, and LLM, for industry or research collaborations. Feel free to reach out to me via email.
Muhammed.a.yousuf@gmail.com