Zakaria Coulibaly
AI/ML Engineer Building the Future
Crafting intelligent systems that solve real-world problems through machine learning, deep learning, and artificial intelligence.
About Me
Full-Stack Developer with expertise in AI/ML, building intelligent systems that solve real-world problems.
Zakaria C.
Full-Stack Developer & AI/ML Specialist
Computer Vision, NLP, ML Pipelines
PyTorch, TensorFlow, React, Node.js
My Journey
As a Full-Stack Developer with deep expertise in AI/ML, my career path has been defined by building production-ready intelligent systems that solve complex business challenges. My technical foundation combines advanced computer vision and NLP capabilities with software engineering best practices, allowing me to develop AI solutions that scale effectively in real-world environments.
At UIUC's Computer Science program, I'm expanding my knowledge of how AI/ML can transform healthcare outcomes and business operations. My hands-on experience with PyTorch and TensorFlow enables me to implement end-to-end ML pipelines that deliver measurable impact. I've developed a particular strength in model optimization, deployment infrastructure, and long-term monitoring systems that ensure AI continues to provide value over time.
I'm passionate about technical leadership that bridges the gap between cutting-edge research and practical implementation, creating AI systems that not only perform well in controlled environments but thrive when solving real problems for real users.
Skills & Expertise
A comprehensive overview of my technical skills and expertise in AI, machine learning, and software development.
Machine Learning
Expertise in various machine learning algorithms, techniques, and frameworks for building intelligent systems.
Deep Learning
Specialized knowledge in neural network architectures and deep learning frameworks for complex pattern recognition.
Programming
Strong programming skills across multiple languages and frameworks for implementing AI/ML solutions.
Mathematics
Strong foundation in mathematical concepts essential for advanced machine learning and AI research.
Education
My academic journey in Computer Science, where I built a strong foundation in algorithms, data structures, and specialized in artificial intelligence and machine learning.
Master of Science in Computer Science
Pursuing advanced studies in Computer Science with a focus on artificial intelligence and machine learning. Developing expertise in deep learning architectures, computer vision, and natural language processing.
Achievements
- GPA: 4.0/4.0
- Member of ACM Student Chapter
Key Courses
Bachelor of Science in Computer Science
Completed undergraduate studies in Computer Science with a strong foundation in algorithms, data structures, and software engineering.
Achievements
- Minor: Mathematics
- Societies: NSLS, UPE, ACM
- Dean's List for some semesters
Key Courses
Professional Certifications
Continuous learning is essential in the rapidly evolving field of AI and machine learning. Here are some of the professional certifications I've earned to stay at the cutting edge.
Timeline
My academic journey in computer science, building a strong foundation in algorithms, data structures, and specializing in artificial intelligence and machine learning.
MS in Computer Science
Pursuing advanced studies at University of Illinois at Urbana-Champaign with focus on AI and machine learning. Relevant coursework includes Deep Learning, Computer Vision, and Natural Language Processing.
BSc in Computer Science
Graduated from Penn State University with a strong foundation in computer science fundamentals, algorithms, and data structures. Completed minor in Mathematics.
Research Interests
My current research interests in artificial intelligence and computer vision, focusing on areas where I aim to make future contributions.
Computer Vision & Deep Learning for Healthcare Applications
Exploring how computer vision techniques can improve medical imaging analysis, disease detection, and patient monitoring systems. Particularly interested in developing models that can work with limited labeled data and provide explainable results for clinical settings.
Efficient Deep Learning & Machine Learning Architectures
Investigating methods to create more efficient neural network & ML architectures that maintain high accuracy while reducing computational requirements. Focus on model compression, knowledge distillation, and hardware-aware neural architecture search.
Multi-Modal Learning Systems
Researching approaches that combine multiple data modalities (vision, text, audio) to create more robust and comprehensive AI systems. Interested in cross-modal transfer learning and attention mechanisms for integrating information across modalities.
Technical Blog
Sharing insights, tutorials, and deep dives into AI and machine learning concepts, techniques, and applications.
A comprehensive guide to understanding transformer architecture and its applications in natural language processing for beginners.
Learn how to implement the YOLO (You Only Look Once) object detection algorithm from scratch using PyTorch.
Explore the best practices for implementing MLOps in your organization to streamline machine learning model development and deployment.
Contact Information
Interested in collaborating or have questions about my work? Feel free to reach out through any of the channels below.
I'm currently available for freelance work, consulting, and full-time positions in AI and machine learning.
Direct Contact
Location
United States
Available for remote work worldwide
Availability
Open to new opportunities
Response time: Within 24 hours
Online Presence
Preferred Contact Method
The best way to reach me is via email. For urgent matters, please use LinkedIn messaging.