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Samira Zad

Natural Language Processing (NLP) Text Mining Semantic Analysis Emotion Detection

About

Dr. Samira Zad is an Assistant Teaching Professor at the Knight Foundation School of Computing and Information Sciences. She was an instructor at the Department of Computer Science and Electrical Engineering at Florida Atlantic University. She received her Ph.D. degree from FIU in 2022 (supervised by Dr. Mark Finlayson). During her Ph.D., she received a scholarship from the Department of Homeland Security to support her Ph.D. She also received her M.S. from Northeastern Illinois University in computer science in 2016. Her area of expertise is in natural language processing, machine learning, text mining, semantic analysis, and emotion detection.

Research Performance Summary

19
Total Papers
916
Total Citations
12
H-Index
2020-2025
Active Research Span

First Recorded Paper

Systematic evaluation of a framework for unsupervised emotion recognition for narrative text

Year: 2020

Citations: 32

Venue: Proceedings of the first joint workshop on narrative understanding

Latest Recorded Paper

Integrating Machine Learning into Healthcare: Enhancing Predictive Analytics for Patient Outcomes

Year: 2025

Citations: 0

Venue: N/A

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2025
5
2022
2
2021
11
2020
1

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 14
Journal 0
Book 0

Top Coauthors

Zad Heidari Uzuner

Research Impact by Period

2025-2026

Period Stats
Papers 5
Citations 34
Avg. Citations / Paper 6.8
H-Index 2

2020-2024

Period Stats
Papers 14
Citations 882
Avg. Citations / Paper 63
H-Index 11

Contact and Professional Links

Contact Information

szad@fiu.edu

Detected Research Keywords

Review Graph Neural Graph Neural Network Neural Network Text Network Text Classification Empirical Study Graphsage Study Graphsage Word2vec Graphsage Word2vec Algorithms Word2vec Algorithms Graph Algorithms Graph Multiclass Graph Multiclass Classification