Mohamed Abdelaal

Dr.-Ing. Mohamed Abdelaal is an AI Architect for Adabas & Natural at Software AG in Stuttgart, Germany, where he drives AI innovation within one of the world’s most established enterprise data management ecosystems. With over 12 years of experience in artificial intelligence, generative AI, and IoT solutions, Mohamed specializes in identifying high-impact AI use cases, designing scalable AI architectures, and modernizing mission-critical enterprise applications.

In his current role, Mohamed focuses on making enterprise data—often locked in decades-old mainframe systems—accessible to modern AI agents and large language models. His work encompasses developing agentic workflows, semantic RAG pipelines, and enterprise-grade integration solutions that connect legacy databases to AI platforms. He collaborates closely with customers to translate business objectives into actionable AI features and guides product development from innovation labs through ISO-compliant production releases.

Prior to his current role, Mohamed spent over four years as a Senior Research Scientist at Software AG (2020-2024), leading publicly funded projects, including KompAKI (AI competence center) and IML4E (Industrial Machine Learning for Enterprises), where he served as national coordinator. He managed collaborations with 30+ academic and industry partners across Europe, including TU Darmstadt, Siemens AG, and Fraunhofer. His research produced automated data engineering tools that improved ML model accuracy by up to 15% and developed comprehensive MLOps frameworks for trustworthy AI.

Earlier, as a Postdoctoral Researcher at the University of Stuttgart (2016-2020), Mohamed led the DFG-funded ComNSense project and taught graduate-level courses on embedded systems and distributed computing.

Mohamed holds a Ph.D. in Computer Science (Dr.-Ing.) from the University of Oldenburg, Germany, an M.Sc. in Electrical Engineering from Port Said University, Egypt, and a B.Sc. from Suez Canal University (graduating first in his class). He has published over 40 papers in top-tier venues, including VLDB, EDBT, SIGMOD, and UbiComp, and holds multiple patents in areas including ML-oriented data quality systems and automated data cleaning.

His contributions have been recognized with the ITEA Award of Excellence for Standardization (2025), Software AG’s Elevating Excellence Award in Innovation (2022), and Best Paper Runner-up Awards at DEEM@SIGMOD 2023 and IJCAI 2023.

Mohamed is an accomplished speaker at international conferences and industry events, including MLOps meetups, on leveraging large language models for data engineering. He serves as a reviewer for IEEE Access, ACM Transactions on IoT, and other prestigious venues.

Mohamed is fluent in English and Arabic, with conversational proficiency in German (B2). Learn more at mohamedyd.github.io or on LinkedIn.