Insight Explorer
Photo by rawpixel on UnsplashInsights Explorer is an AI-powered text analytics tool that uses your open-ended feedback to identify top themes, create headlines, and generate helpful summaries. This feature can help you understand large text datasets faster than ever, and is a great starting point for analysts working with unstructured feedback data.
Any type of project with open text fields can be used for generating insights. That includes:
- Survey projects
- Imported Data projects
- CX Dashboards
- Engagement
- Lifecycle
- Ad Hoc Employee Research
- Ticket Datasets
- XM Discover projects
Mohammed Khalilia (محمد عبد الستار قاسم) is a researcher, computer scientist, and data scientist with a PhD in Computer Science from the University of Missouri. Following his doctorate, he joined Georgia Tech’s Computational Science and Engineering school and Emory University as a Postdoctoral Fellow, where his research spanned predictive modeling, relational cluster analysis, and health and nursing informatics.
He then spent nearly five years at Amazon, working across Amazon Web Services (AWS) and Amazon Studios in natural language processing (NLP), speech synthesis, and computer vision. In 2018, he was part of the team that launched Comprehend Medical, Amazon’s NLP service for clinical and biomedical text. At Qualtrics, he developed the company’s first fine-tuned large language model, trained synthetic sampling model, and worked on conversational machine learning, and active learning.
He is also an adjunct professor at Birzeit University, where he teaches NLP courses for doctoral students.