Sandra Vucevic

Overview

Sandra Vucevic is a Visiting Lecturer in the School of Policy and Global Affairs (SPGA) at City St George's, University of London, where she specialises in teaching quantitative research methods. With a multidisciplinary background in applied computer engineering, technology entrepreneurship, research methods, blockchain innovation, and higher education pedagogy, she brings a distinctive, practice-led perspective to her teaching.

Sandra's approach to education is grounded in the belief that learning is a lifelong journey, not a destination. This philosophy is reflected both in her own diverse educational journey across multiple disciplines and in her teaching methods, which aim to make complex statistical concepts accessible to students from different backgrounds. She is passionate about demystifying quantitative methods by translating technical content into clear, practical applications that resonate with learners at all levels.

Her professional experience covers both theory and practice, including work with government agencies and high-stakes stock exchange environments where data analysis informs critical decision-making. Sandra is an entrepreneur who has spent the past decade managing independent education consulting ventures alongside her academic work, applying practical strategies to help individuals improve their professional skills. Her experience across the public, private, academic, and entrepreneurial sectors shapes her classroom approach and enables her to connect theoretical ideas to real-world applications.

Teaching

Sandra joined City, St George's, University of London in 2020, initially as an MSc student in Research Methods. She progressed to become a Visiting Lecturer and currently leads the modules "Learning from Social Data" (SG1021) and "Regression Analysis" (SG3093). She also contributes to the teaching team for "Social (Justice) Research: Qualitative and Quantitative Approaches" (SG1027), and has previously taught on "Data and the Social World" (SG1022) and "Introduction to Political and Economic Data Analysis" (IP1041). Additionally, Sandra supervises dissertations for Q-Step students and has previously taught with the postgraduate teaching team at the London School of Economics (LSE) within the Department of Methodology.

Research Interests

Sandra's research has concentrated on public attitudes towards emerging technologies. She was involved in UCL's "Driverless Futures?" project, which investigated public perceptions of AI and autonomous vehicles in both the UK and the US. Her dissertation analysed attitudes towards robotics and AI across Europe, using advanced quantitative methods and complex survey analysis to understand how citizens interact with technological change. Looking ahead, Sandra is intrigued by the transformative potential of AI in education and learning, especially its ability to personalise learning experiences and reshape pedagogical strategies. She also maintains a strong interest in cryptocurrencies and blockchain technology, examining their wider social, economic, and policy implications.

Professional Development

Sandra is a Fellow of the Higher Education Academy (FHEA) and holds a PGDip in Academic Practice. She is currently pursuing an MA in Academic Practice at LEaD, demonstrating her strong commitment to pedagogical excellence and innovative teaching. Throughout her academic career, she has received numerous scholarships and awards, including the Chevening Scholarship, the Montenegrin National Academic Excellence Award, and the Coinbase Scholarship.

_{Last Updated: 07-04-2026}

Qualifications

• Teaching Excellence Award, City, University of London, United Kingdom, April 2026
• MA Academic Practice, City, University of London, United Kingdom, 2022 - 2026
• PGDiploma Academic Practice, City, University of London, United Kingdom
• MSc Blockchain and Digital Currency, University of Nicosia, Cyprus
• MSc Research Methods, City, University of London, United Kingdom
• MSc Technology Entrepreneurship, University College London, United Kingdom
• SpecApp (=MSc) Applied Computer Engineering, Faculty of Electrical Engineering, University of Montenegro, Montenegro
• BApp (=BSc) Applied Computer Engineering, Faculty of Electrical Engineering, University of Montenegro, Montenegro

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