Prof. Dr. Alejandro García

Prof. Dr. Alejandro García is Dean of the School of Computing & Data Science at ICS AI University, where he leads the School's academic strategy, research portfolio, faculty development, international partnerships, and industry collaboration. He is an internationally recognised scholar in computer science, data science, high-performance computing, and digital innovation, with more than twenty-four years of experience spanning academia, scientific research, and university leadership across Europe, North America, and Asia.

Born and educated in Spain, Prof. García earned a Bachelor of Engineering in Computer Engineering from the Universidad Politécnica de Madrid, where he graduated with the highest academic distinction. His early interest in large-scale data systems and parallel computation took him to ETH Zürich, where he completed a Master of Science in Data Science, and subsequently to the Universitat Politècnica de Catalunya (BarcelonaTech), where he was awarded a Doctor of Philosophy in Computer Science for research on scalable data analytics over distributed architectures.

Following his doctorate, Prof. García was appointed Postdoctoral Research Fellow at Carnegie Mellon University's School of Computer Science, working at the intersection of machine learning, systems research, and high-performance computing. He later completed an Executive Leadership Programme in Digital Transformation & Innovation at the University of Cambridge Judge Business School, strengthening his expertise in institutional strategy, technology governance, and cross-sector innovation.

Prof. García has held academic appointments at leading European and international universities, including visiting professorships at the Massachusetts Institute of Technology, EPFL, and the National University of Singapore. He has served as scientific advisor to European research councils and has contributed to the design of national digital strategies, big data policy frameworks, and European Union research programmes on data-driven innovation and trustworthy computing.

His research programme sits at the frontier of machine learning, big data analytics, cloud infrastructure, high-performance computing, knowledge graphs, and digital twin technologies. He has authored more than 165 peer-reviewed publications, nine authored books, and over 32 book chapters, and has delivered 88+ invited keynotes at premier venues including IEEE International Conference on Data Engineering, ACM SIGMOD, ACM KDD, and the International Supercomputing Conference. His scholarship has attracted more than 24,500 citations and an h-index of 73.

As principal investigator, Prof. García has led over forty-two research projects and secured more than nineteen international grants from the European Commission's Horizon Europe programme, national research councils, and industry consortia. He established a distinguished record in translational research, working with global technology firms, financial institutions, telecommunications operators, and public-sector organisations to deploy data platforms, cloud infrastructure, and analytics systems at production scale.

Prof. García has supervised more than forty-eight doctoral candidates, many of whom now hold senior academic, research, and technology leadership positions across four continents. He is a passionate mentor and a strong advocate for interdisciplinary doctoral training, open science, and equitable access to advanced computing education. His teaching portfolio spans computer science, data science, big data analytics, cloud computing, distributed systems, high-performance computing, data engineering, machine learning, and doctoral research methodology.

His leadership philosophy is grounded in academic excellence, interdisciplinary collaboration, ethical responsibility, and international openness. He believes that computing and data science education must combine deep theoretical foundations with hands-on engineering practice, computational literacy, and a strong ethical compass. Under his leadership, the School of Computing & Data Science is expanding its programme portfolio, investing in modern computing laboratories and data platforms, strengthening industry alliances, and deepening its international research partnerships.

Prof. García serves on international advisory boards, accreditation panels, and standards committees on computer science, data science, and digital innovation. He is a Senior Member of IEEE and the Association for Computing Machinery (ACM), a member of the IEEE Computer Society, the European Association for Data Science, and the Big Data Value Association (BDVA). He advises ministries, universities, and industry consortia on digital transformation, national data strategy, and the responsible adoption of artificial intelligence in the data economy.

His vision for the School of Computing & Data Science is to establish it as a globally recognised centre for computing education, applied data science research, and cross-sector innovation — preparing a new generation of technology leaders capable of solving global challenges through computing, data analytics, and responsible digital innovation. He is committed to building an inclusive, ambitious, and internationally connected School that stands among the leading computing schools in the world.