معرفی
Ivan Smirnov is a computational social scientist currently serving as the AI Lead in Research and Researcher Training at the Graduate Research School, University of Technology Sydney (UTS). He is also an External Faculty Member at the Complexity Science Hub in Vienna. His work spans the intersection of AI, sociology, and education, with a focus on Generative AI's role in research and doctoral training.
- University: University of Technology Sydney
- School: Graduate Research School
- Previous Positions: Assistant Professor, University of Mannheim; Group Leader, Higher School of Economics, Moscow
Smirnov’s research explores how digital traces and machine learning can illuminate social dynamics such as inequality, gender bias, and academic performance. He employs computational methods to study topics like online toxicity, student wellbeing, and the digital representation of gender. His methodological expertise includes natural language processing, social network analysis, and predictive modeling using social media data.
His recent publications reveal a consistent trend in using large-scale digital data to address pressing social questions, particularly in education and mental health. He frequently publishes in leading interdisciplinary journals such as Proceedings of the National Academy of Sciences, EPJ Data Science, and Royal Society Open Science, and presents at major conferences including IC2S2 and ICWSM.
His scientific contributions have been recognized through media coverage in Nature, MIT Technology Review, and The Times, as well as a Best Course Award at HSE for his pioneering teaching in computational social science.
- Best Course Award at Higher School of Economics
- Media features in Nature, MIT Technology Review, The Times, ABC TV
Smirnov is actively involved in research leadership and training, having led AI initiatives at UTS and co-organized the Summer Institute in Computational Social Science. He has secured funding from the European Commission and the Russian Science Foundation. He supervises research students and has developed the open educational course Getting Started with Generative AI in Research, reflecting his commitment to empowering the next generation of researchers. He also contributes to the academic community through peer review for top conferences and journals.
He is affiliated with professional groups including the Human-AI Collaborative Knowledgebase for Education and Research (HACKER) and the SDG Classification Expert Group, and leads initiatives focused on integrating AI into research training and supporting HDR student wellbeing.
