Sandra Vucevic

Overview

Sandra Vucevic is a Lecturer in Quantitative Sociology at City St George’s, University of London. Her teaching and research sit at the intersection of technology, society, and data literacy. An entrepreneur with a multidisciplinary background spanning applied computer engineering, blockchain innovation, and higher education pedagogy, she brings a distinctive perspective to examining how social data and emerging technologies shape the social world, including questions of inequality, power, trust, and participation.

A passion for demystifying quantitative methods lies at the heart of Sandra’s teaching. Recognising that statistics and programming can initially feel daunting, she brings clarity to complexity, helping students turn unfamiliar concepts into skills they can use with confidence. Drawing on professional experience across public service and financial markets, she uses real-world examples to help students understand not only how to apply statistical methods, but also how to evaluate evidence critically and use social data responsibly.

Teaching

Sandra joined City St George’s in 2020 as a student on the MSc Research Methods programme. She became a Visiting Lecturer in 2021 and was appointed as a full-time Lecturer in Quantitative Sociology in 2026. Her commitment to supporting and inspiring students has been recognised with a Teaching Excellence Award, which she won following nominations from her students.

In the 2026/27 academic year, Sandra is module leader for the following modules:

• SG1021: Working with Statistics
• SG2045: Quantitative Analysis of Social Research Data
• SG2046: Quantitative Data Placement
• SG3093: Regression Analysis

Alongside these, she contributes to the teaching team for SG1027: Social (Justice) Research: Qualitative and Quantitative Approaches.

Sandra combines established quantitative methods with contemporary digital tools in her teaching. Students gain hands-on experience with SPSS, R, and Python while developing skills in emerging areas such as AI prompt engineering. She also supervises quantitative dissertation projects, including those of Q-Step students and has previously contributed to several other data-focused modules at City St George’s (SG1022, IP1041). At the London School of Economics and Political Science (LSE), she taught postgraduate students on core modules in the Department of Methodology (MY451, MY551, MY464).

Research Interests

Sandra’s research examines how people understand and respond to emerging technologies. Her MSc dissertation used complex survey data to investigate public attitudes towards robotics and artificial intelligence across the European Union, including differences between countries and population groups. In a separate project, she contributed to UCL’s Driverless Futures?, exploring public perceptions of artificial intelligence and autonomous vehicles in the UK and the US. Her developing research agenda extends this focus to the role of AI in higher education and the wider social, economic, and policy implications of blockchain and decentralised technologies.

Professional Development

Committed to continuous pedagogical development and innovation in higher education, Sandra is completing an MA in Academic Practice through Learning Enhancement and Development (LEaD). As part of the programme, she is researching her own teaching through self-reflective practice, examining and refining her approach in the classroom. She is also a Fellow of the Higher Education Academy (FHEA).

Her academic and professional work has been recognised through numerous scholarships and awards, among them a Chevening Scholarship, the Montenegrin National Academic Excellence Award, and a Coinbase Scholarship.

 

Last Updated: August 2026

Qualifications

• MA 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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