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Dr Bikesh Raj Upreti

Lecturer in Business Information Sy

School of Business
Faculty of Business, Economics and Law
b.upreti@business.uq.edu.au

Overview

Bikesh Raj Upreti is a Lecturer in the Department of Business Information Systems at the University of Queensland (UQ) in Brisbane, Australia. He completed his doctoral degree from Aalto University School of Business, Helsinki. His doctoral dissertation, " Untangling the Application of Text-mining Methods in Information Systems Domain", focused on developing applications to uncover insights from the large-scale text data. After graduating, he continued as a postdoctoral researcher and visiting scholar at the Department of Information Service Management, Aalto Business school, before joining the University of Queensland.

Bikesh's research interests are in the areas of applied computational methods and quantitative inquiry of inter-disciplinary phenomena. He has applied advanced machine learning, deep learning and other analytical tools for large-scale behavioural and predictive analytics set in Information systems, marketing, finance, and political discourses. His work has been published in several journals (European Journal of Information systems, Industrial Marketing Management, Journal of Travel Research, Electronic Markets) and peer-reviewed conference proceedings (ICIS, HICSS, and Bled).

His work has won the inaugural edition of the Paper-at-hon competition at ICIS 2017, the Best paper award at the Bled conference 2019, and the nomination for the best paper award at HICSS 2020. He also actively serves as a reviewer for the journals such as (European Journal of Information systems, Decision Sciences, Internet research and Information & Management, and International Journal of Information Management) and conferences (ICIS, ECIS, HICSS, AMCIS, PACIS).

Publications

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Supervision

  • Enhancing Patient Satisfaction through Natural Language Processing (NLP): Unveiling the Depth and Uniqueness of Clinician Notes in Teleconsultation Platforms

    Doctor Philosophy

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Available Projects

  • Understanding the impacts of fake news and misinformation on social media

    Users face challenges of preserving their preferences when interacting with other community members. These interactions also get infiltrated by the fake news and misinformation campaigns pursued by bots or other social media users. Using machine learning and NLP techniques, we aim to build a theoretical model for explaining behavioral changes in online communities and explore how online discourses and fake news impact them. We will carry mix-method research to analyze data from popular social media on a sociopolitical topic, applying tools from NLP and network science. We will uncover the nuances of user interaction and the roles played by fake news and misinformation campaigns. This project builds upon the existing theories in the information systems and requires engaging in both the qualitative and quantitative methods.

    Supervisors: Bikesh Raj Upreti (UQ), Arapan Kar (IIT-Delhi), Stan Karanasios (UQ)

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Publications

Book Chapter

  • Knowledge-driven approaches for financial news analytics

    Upreti, Bikesh Raj, Back, Philipp Martin, Malo, Pekka, Ahlgren, Oskar and Sinha, Ankur (2019). Knowledge-driven approaches for financial news analytics. Network Theory and Agent-Based Modeling in Economics and Finance. (pp. 375-404) edited by Anindya S. Chakrabarti, Lukáš Pichl and Taisei Kaizoji. Singapore, Singapore: Springer Singapore. doi: 10.1007/978-981-13-8319-9_19

Journal Article

Conference Publication

Other Outputs

PhD and MPhil Supervision

Current Supervision

  • Enhancing Patient Satisfaction through Natural Language Processing (NLP): Unveiling the Depth and Uniqueness of Clinician Notes in Teleconsultation Platforms

    Doctor Philosophy — Associate Advisor

    Other advisors:

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Understanding the impacts of fake news and misinformation on social media

    Users face challenges of preserving their preferences when interacting with other community members. These interactions also get infiltrated by the fake news and misinformation campaigns pursued by bots or other social media users. Using machine learning and NLP techniques, we aim to build a theoretical model for explaining behavioral changes in online communities and explore how online discourses and fake news impact them. We will carry mix-method research to analyze data from popular social media on a sociopolitical topic, applying tools from NLP and network science. We will uncover the nuances of user interaction and the roles played by fake news and misinformation campaigns. This project builds upon the existing theories in the information systems and requires engaging in both the qualitative and quantitative methods.

    Supervisors: Bikesh Raj Upreti (UQ), Arapan Kar (IIT-Delhi), Stan Karanasios (UQ)

This staff member is a UQ Expert for media in the following fields:

Artificail Inteligence, Social Media analytics, Big data, Information Systems

They are happy to lend their expertise to your articles or broadcasts and share their research discoveries and insights with the community via media channels.

For additional assistance with story ideas, general advice and information or help with seeking further experts, please email the UQ Media Team or telephone (07) 3365 1120.

Links

ORCID: 0000-0002-5632-4720

Google Scholar ID: i6kX3eQAAAAJ

Personal Profile: Link

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