About Me

As an instructor, my goal is to bridge the gap between theory and practical implementation. I want students to understand not only how a technology works, but also how and why it can be applied to solve real-world problems. I draw heavily from my experience building production systems and working with AI technologies, and I aim to make complex technical concepts approachable through practical examples and real engineering perspectives.

Whether you are beginning your journey into mechatronics, robotics, electronics, and intelligent automation, exploring Reinforcement Learning, or looking to understand how AI can be applied to enable robots and autonomous systems to learn, adapt, and make decisions, I hope my courses will help you develop practical skills and the confidence to turn concepts into real-world robotic and automated systems.

I believe the best way to learn engineering is to build, experiment, learn from failures, and continuously improve — and that is the approach I bring to my teaching.

I am a Senior Backend Engineer, Technical Lead, and technology enthusiast with more than a decade of experience designing, building, and operating high-performance software systems in real-world production environments.

Throughout my career, I have worked across e-commerce, fintech, and AI-driven products, helping organizations build reliable and scalable systems that solve meaningful business problems. My experience spans backend engineering, microservices, cloud-native development, distributed systems, and data pipelines.

I have extensive hands-on experience with AWS, Docker, Kubernetes, Prometheus, and Grafana, as well as programming languages including Go, Python, Rust, and Java. I take a pragmatic approach to technology and believe that the right tool is the one that best solves the problem rather than following a particular technology or framework simply because it is popular.

My work in AI-focused teams has included the productionization of machine learning models, including Federated Learning and Reinforcement Learning systems, with deployments across servers, mobile phones, and embedded platforms.

Alongside my professional engineering career, I am currently studying for an MPhil in Mechatronics Engineering, where my focus is on applying Reinforcement Learning techniques to robotics and automation. This work allows me to explore the intersection of software engineering, artificial intelligence, electronics, control systems, robotics, and automation, with a particular interest in developing intelligent systems that can learn from interaction with their environment and improve their behavior through experience.

I hold a BSc. in Computer Science and bring a pragmatic, data-driven approach to engineering. I value strong ownership, clear communication, collaboration, and practical problem-solving.

My professional experience has taught me that technology is ultimately about solving problems and creating value. Through my courses, I hope to share that perspective with students while helping them develop the technical foundations, practical skills, and engineering mindset needed to turn ideas into working solutions — particularly in the exciting fields of mechatronics, robotics, electronics, intelligent automation, and Reinforcement Learning.