How to use AI (SciSpace) for Literature Search and Review
Conducting an effective literature search and review is foundational to academic research. However, with the growing volume of scientific publications, identifying relevant studies, synthesizing evidence, and structuring a coherent review can be both time-consuming and complex.
In this webinar, we will explore how SciSpace can support researchers in streamlining literature discovery and review workflows. The session will demonstrate how AI-assisted tools can help researchers efficiently find relevant papers, extract key insights, and organize evidence into a structured literature review.
In this session, you will learn how to:
🔎 Discover relevant research papers more efficiently
📚 Understand complex academic articles and extract key insights
🧠 Identify key theories, concepts, and research gaps
📊 Organize and synthesize literature systematically
✍️ Build a structured and well-supported literature review
The focus will be on practical workflows that researchers can apply directly in their own work—from early-stage exploration to developing a strong theoretical foundation.
About the Speaker
Dr. Abolghasem Sadeghi-Niaraki is an Associate Professor in the Department of Computer Science and Engineering at Sejong University, Republic of Korea, and a Fellow at the Harvard Spatial Data Lab. He is an internationally recognized scholar in Geo-AI, spatial data science, and extended reality (XR), with over 17 years of academic experience.
He has authored more than 200 peer-reviewed publications, holds over 50 patents, and has been recognized among the Top 2% of Scientists worldwide (Stanford–Elsevier, 2024, 2025). His research focuses on integrating artificial intelligence with geospatial systems, human-centered computing, and immersive technologies