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Dr

Ivan Smirnov

Research Consultant

SoCSS Discipline of Digital and Social Media

BIO

Ivan Smirnov is a computational social scientist exploring the evolving relationship between technology and society. His current focus is on Generative AI: he both conducts research on GenAI and employs GenAI to conduct research. He is particularly interested in exploring AI‘s potential role in improving doctoral students’ wellbeing and helping them navigate the hidden curriculum in academia.

 

Beyond his research, Ivan is deeply committed to empowering the next generation of scientists through teaching, social entrepreneurship, and the development of open educational resources, such as the open course Getting Started with Generative AI in Research.

 

Dr Smirnov is GRS-lead for for AI in Research and Researcher Training. He is also an External Faculty Member at the Complexity Science Hub, Vienna. Prior to joining UTS, he served as an Assistant Professor at the University of Mannheim and led a research group at the Higher School of Economics, Moscow.

 

His research has been regularly presented at flagship conferences in his field, such as IC2S2 and ICWSM; published in leading journals, including Proceedings of the National Academy of SciencesEPJ Data SciencePNAS Nexus, and Royal Society Open Science; and featured in major Australian and international media outlets: ABC TVMIT Technology ReviewThe Times, and Nature.

UNIVERSITY OF TECHNOLOGY SYDNEY ORGANISATIONAL UNITS MEMBERSHIP

ACADEMIC POSITIONS

  • Assistant Professor
    University of Mannheim, Business School, Germany1 Aug 2022 - 15 Oct 2023
  • Research Fellow
    RWTH Aachen, Chair for Computational Social Science and Humanities, Germany20 Sep 2020 - 31 Jul 2022
  • Group Leader
    Higher School of Economics, Computational Social Science Group, Moscow, Russia1 Jan 2018 - 31 Aug 2020

LANGUAGES

  • English
    Can read, write, speak, understand and peer review
  • French
    Can read, write, speak and understand
  • Russian
    Can read, write, speak and understand
  • German
    Can read and understand

PROFILE TYPE

  • Academic

AVAILABILITY

  • Masters Research or PhD student supervision
  • Media enquiries
  • Collaborative projects

DISCIPLINES