Special Offer: Get 50% off your first 2 months when you do one of the following
Personalized offer codes will be given in each session
Name
Dr. Arash Hajikhani
Title
Research team leader: VTT technical research centre of Finland and Adjunct Professor at LUT University (Finland)
Bio
Dr. Arash Hajikhani is a Research Team Leader in the Quantitative Science and Technology Studies area at VTT Technical Research Centre of Finland and an Adjunct Professor at LUT University, Finland. His research specializes in innovation and technology management, with a particular emphasis on quantitative and data-driven methods for measuring and assessing Science, Technology, and Innovation systems. He also worked as Visiting Scholar at The Scandinavian Consortium for Organizational Research facilitates, Stanford University and The Georgia Tech Scheller College of Business.
As an advocate for Generative AI, Dr. Hajikhani actively explores its applications in the research domain, observing its adaptability, opportunities, and challenges. He is passionate about promoting responsible AI use, serving as an educator to teach and showcase practical, ethical AI use cases. With over a decade of practical experience, Dr. Hajikhani has utilized data analytics methods such as text analytics, network analysis, and machine learning to transform big data into actionable insights that enhance decision-making processes. His work focuses on leveraging novel and large-scale data sources to design informative metrics that capture economic, societal, and technological shifts.
Dr. Hajikhani's contributions to automating data-driven insights for identifying technological change and innovation systems have been published in top-tier journals, including Scientometrics, Journal of Business Research, Technological Forecasting and Social Change, Journal of Cleaner Production, and the Association for Computing Machinery. Additionally, he shares his expertise through open-source code repositories, furthering the accessibility and impact of his work.
As an advocate for Generative AI, Dr. Hajikhani actively explores its applications in the research domain, observing its adaptability, opportunities, and challenges. He is passionate about promoting responsible AI use, serving as an educator to teach and showcase practical, ethical AI use cases. With over a decade of practical experience, Dr. Hajikhani has utilized data analytics methods such as text analytics, network analysis, and machine learning to transform big data into actionable insights that enhance decision-making processes. His work focuses on leveraging novel and large-scale data sources to design informative metrics that capture economic, societal, and technological shifts.
Dr. Hajikhani's contributions to automating data-driven insights for identifying technological change and innovation systems have been published in top-tier journals, including Scientometrics, Journal of Business Research, Technological Forecasting and Social Change, Journal of Cleaner Production, and the Association for Computing Machinery. Additionally, he shares his expertise through open-source code repositories, furthering the accessibility and impact of his work.
