Md. Abdullah Al Mamun is an experienced software engineer and DevSecOps Manager with a strong research and development background in Artificial Intelligence (AI), Machine Learning (ML), and emerging Generative AI (GenAI) technologies. Over the past decade, his academic pursuits, industry roles, and technical contributions have consistently intersected with the evolving field of intelligent systems.

With a B.Sc. in Computer Science & Engineering from RUET and currently pursuing an M.Sc. in Computer Science and Engineering from Bangladesh University of Professionals, Mamun combines theoretical depth with practical insights. His formal education is bolstered by numerous industry-recognized certifications in Data Science, AI, and Machine Learning from platforms such as IBM, Coursera, and Simplilearn.

Mamun’s research portfolio demonstrates early and continuous engagement with AI. He has published several peer-reviewed papers in international journals and conferences, including studies on Bangla speech recognition using Hidden Markov Models, automatic speaker identification using MFCC and Vector Quantization, and optical character recognition through Multi-Layer Perceptron Neural Networks. These works emphasize his foundational expertise in pattern recognition, speech processing, and supervised learning techniques.

In his professional capacity, Mamun has applied AI-driven solutions to real-world problems. Notably, at Datasoft Systems, he led the development of an AI-powered chatbot integrated with Google’s ML tools for microfinance applications serving over 165 NGOs. His current role at Robi Axiata Limited includes incorporating secure development practices into application systems via DevSecOps, where AI tools play a growing role in threat detection and anomaly analysis.

Technically proficient in a wide range of AI and ML frameworks, Mamun regularly works with Python libraries such as TensorFlow, Keras, Scikit-learn, and PyTorch. He leverages these tools in projects involving speech synthesis, OCR, and pattern recognition. His development experience extends to modern full-stack environments, allowing him to integrate AI solutions seamlessly across web and cloud infrastructures including AWS, GCP, and Azure.

Mamun has also reviewed AI-focused publications, such as “Hands-On Markov Models with Python,” evidencing his engagement with ongoing academic and practical discourse in probabilistic modeling. As GenAI technologies gain momentum, his foundation in neural networks and probabilistic models positions him well to explore applications like language generation, intelligent automation, and personalized digital services.

Mamun’s multi-disciplinary approach—spanning software engineering, academic research, and AI deployment—makes him a dynamic contributor to the AI and ML ecosystem. His blend of theoretical research, hands-on project execution, and leadership in software development ensures his continued impact on the advancement and ethical application of AI technologies.