Workshop: Natural Language Processing for Innovation Management

Date: June 5, 2026
Location: Hengqin

Fee: 700 HKD

Associate Professor Filippo Chiarello from the University of Pisa will host a Natural Language Processing Workshop (NLPW) on June 5, 2026, in Hengqin. This hands-on workshop is designed to introduce participants to the application of Natural Language Processing (NLP) techniques within the context of innovation management.

Purpose of the NLPW

This workshop is designed to equip participants with both foundational knowledge and practical skills in NLP, with a special focus on applications in innovation management. Through a full-day, hands-on agenda, the workshop introduces participants to key NLP concepts, from text preprocessing and encoding methods to advanced techniques.

Participants will gain an understanding of how text analytics and large language models (LLMs) like GPT and BERT can be applied to analyze innovation-related data. The interactive sessions aim to bridge the gap between computational tools and innovation research, empowering attendees to apply NLP methods to their own academic or industry projects. By the end of the workshop, participants will be familiar with the NLP pipeline, understand the capabilities and limitations of modern language models, and be able to apply NLP techniques to extract insights from unstructured text data in the context of innovation.

Prerequisites and Materials

There are no strict prerequisites to attend the workshop. However, for the extended practical sessions, a basic understanding of Python and/or R will be helpful. All participants will receive the slides and source code (R and Python) used during the workshop.

Agenda

About the Workshop Host

Dr. Filippo Chiarello is an Associate Professor of Strategic and Competitive Intelligence at the University of Pisa. His research interests encompass Natural Language Processing (NLP), Innovation Management, and Human Resources Management, with a particular focus on the intersection of technology and strategic decision-making. He is a proud member of the Business Engineering 4 research group, where he contributes to the development of data-driven approaches in business and innovation studies. Dr. Chiarello’s work bridges advanced computational techniques with practical applications, enabling organizations to harness unstructured data for strategic insights and competitive advantage.