Ergin ALTINTAS

I’m a Senior DevOps Engineer and AI Researcher with a deep passion for Free/Libre/Open Source Software and expertise in Cybersecurity who also loves to write code. With a Ph.D. in Computer Engineering, I specialize in Natural Language Processing (NLP), Machine Learning, and Deep Learning.

Certificates

With multiple certifications, I combine cutting-edge AI research with practical DevOps and software solutions to build secure, scalable, and innovative systems. My expertise spans AI, cloud infrastructure, real-time embedded systems, and high-performance computing.

I have extensive experience in various programming paradigms, including embedded development, scripting, web development, and high-level algorithmic design. My expertise also extends to architectural patterns, distributed systems, and scalable software design, enabling me to build efficient, resilient, and maintainable solutions.

Although Python is my preferred language, over the years, I have worked with a broad spectrum of programming languages, including: C/C++, C#, Go, Java, and Pascal. I am also particularly interested in Rust and WebAssembly as I believe that they represent the future of secure, high-performance, and portable computing.

Check out my resume for more details on my background and experience.

Resume

Education

PhD in CE, 2023
Ege University
MSc in CE, 2005
Naval Sciences and Engineering Institute
BSc in CE, 1999
Turkish Naval Academy

Interests

Deep Learning
Large Language Models
Linux & Open Source
Cybersecurity
WebAssembly

Recent Posts

AI in Software Development and DevOps Lifecycle

Nov 21, 2024

AI in Software Development and DevOps: Trends, Tools, and the Road Ahead Artificial Intelligence (AI) is revolutionizing software development and DevOps, offering capabilities that enhance productivity, streamline workflows, and foster innovation. Open-source solutions like Aider and Ollama exemplify how AI can seamlessly integrate into daily practices, enabling teams to deliver robust and efficient software solutions faster. This article explores the latest trends, tools, and future possibilities of AI in software development and DevOps.

The Challenges of Building Language-Specific AI Models

Nov 17, 2024

The Challenges of Building Language-Specific AI Models Developing AI models for agglutinative languages like Turkish presents unique challenges. In this post, I’ll share my experiences and insights into creating a language-specific tokenizer and the impact it has on model performance. Understanding Agglutinative Languages Agglutinative languages, such as Turkish, Finnish, and Hungarian, build words by attaching affixes to a root in a highly systematic manner. A single word can encapsulate what might require multiple words or an entire phrase in non-agglutinative languages like English.

Deep Learning: Trends and Future Directions

Nov 14, 2024

Deep Learning: Trends and Future Directions The landscape of deep learning is evolving rapidly. In this article, I will discuss the current trends in deep learning research and speculate on the future direction of AI, especially in the context of Natural Language Processing. Deep learning has become the backbone of many breakthroughs in Artificial Intelligence (AI), and its application to Natural Language Processing (NLP) has revolutionized how machines interact with human language.