Prof. Dr. Narjes Nikzad Khasmakhi

Profile

Narjes Nikzad was a postdoctoral researcher at TH Köln (University of Applied Sciences). She jointly worked with the Institute of Data Science, Engineering, and Analytics (IDE+A), and the Institute of Information Science.

One of her primary areas of focus lies in conversational systems, where she leverages her expertise to develop intelligent dialogue agents capable of engaging in natural conversations with users.

In addition to that, she is deeply engaged in advancing the field of knowledge representation and knowledge graphs. By harnessing the power of structured data, she aims to construct comprehensive knowledge graphs that capture the relationships between entities and concepts. These knowledge graphs serve as invaluable resources for a wide range of applications, including information retrieval, question-answering systems, and knowledge-based recommendation engines.

Furthermore, she has a strong bias toward topics that help unleash the power of natural language processing (NLP), and knowledge graphs, and enable these subjects to shine in other domains. Her professional collaboration includes researchers from both academia and industry.

Feel free to connect with her.

List of Publications

2024

Large Language Models: A Survey.
2024.
Shervin Minaee, Tomas Mikolov, Narjes Nikzad, Meysam Chenaghlu, Richard Socher, Xavier Amatriain and Jianfeng Gao.
[doi]  [BibTeX] 

2023

Text Simplification of Scientific Texts for Non-Expert Readers.
In: SimpleText@CLEF-2023, volume abs/2307.03569, series CEUR Workshop Proceedings. 2023.
Björn Engelmann, Fabian Haak, Christin Katharina Kreutz, Narjes Nikzad-Khasmakhi and Philipp Schaer.
[doi] [pdf]  [BibTeX] 
ConvGenVisMo: Evaluation of Conversational Generative Vision Models.
In: ICML 2023 Workshop Artificial Intelligence and Human-Computer Interaction. 2023.
Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu, Nabiha Asghar, Philipp Schaer and Dietlind Zühlke.
[doi] [pdf]  [BibTeX] 

2022

Deep Learning-based Text Classification: A Comprehensive Review.
ACM Comput. Surv., 54(3):62:1-62:40, 2022.
Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad, Meysam Chenaghlu and Jianfeng Gao.
[doi]  [BibTeX] 
Automatic personality prediction: an enhanced method using ensemble modeling.
Neural Comput. Appl., 34(21):18369-18389, 2022.
Majid Ramezani, Mohammad-Reza Feizi-Derakhshi, Mohammad Ali Balafar, Meysam Asgari-Chenaghlu, Ali-Reza Feizi-Derakhshi, Narjes Nikzad-Khasmakhi, Mehrdad Ranjbar-Khadivi, Zoleikha Jahanbakhsh-Nagadeh, Elnaz Zafarani-Moattar and Taymaz Akan.
[doi]  [BibTeX] 

2021

Cy: Chaotic yolo for user intended image encryption and sharing in social media.
Inf. Sci., 542:212-227, 2021.
Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi, Narjes Nikzad-Khasmakhi, Ali-Reza Feizi-Derakhshi, Majid Ramezani, Zoleikha Jahanbakhsh-Nagadeh, Taymaz Rahkar-Farshi, Elnaz Zafarani-Moattar, Mehrdad Ranjbar-Khadivi and Mohammad Ali Balafar.
[doi]  [BibTeX] 
BERTERS: Multimodal representation learning for expert recommendation system with transformers and graph embeddings.
Chaos, Solitons & Fractals, 151:111260, 2021.
Narjes Nikzad-Khasmakhi, Mohammad Ali Balafar, M Reza Feizi-Derakhshi and Cina Motamed.
[BibTeX] 
ExEm: Expert embedding using dominating set theory with deep learning approaches.
Expert Syst. Appl., 177:114913, 2021.
Narjes Nikzad-Khasmakhi, Mohammad Ali Balafar, Mohammad-Reza Feizi-Derakhshi and Cina Motamed.
[doi]  [BibTeX] 
Phraseformer: Multimodal Key-phrase Extraction using Transformer and Graph Embedding.
CoRR, abs/2106.04939, 2021.
Narjes Nikzad-Khasmakhi, Mohammad-Reza Feizi-Derakhshi, Meysam Asgari-Chenaghlu, Mohammad Ali Balafar, Ali-Reza Feizi-Derakhshi, Taymaz Rahkar-Farshi, Majid Ramezani, Zoleikha Jahanbakhsh-Nagadeh, Elnaz Zafarani-Moattar and Mehrdad Ranjbar-Khadivi.
[doi]  [BibTeX] 
Multimodal price prediction.
Annals of Data Science:1-17, 2021.
Aidin Zehtab-Salmasi, Ali-Reza Feizi-Derakhshi, Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu and Saeideh Nabipour.
[BibTeX] 

2020

Covid-Transformer: Detecting COVID-19 Trending Topics on Twitter Using Universal Sentence Encoder.
CoRR, abs/2009.03947, 2020.
Meysam Asgari-Chenaghlu, Narjes Nikzad-Khasmakhi and Shervin Minaee.
[doi]  [BibTeX] 
A Model to Measure the Spread Power of Rumors.
CoRR, abs/2002.07563, 2020.
Zoleikha Jahanbakhsh-Nagadeh, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Taymaz Rahkar-Farshi, Meysam Asgari-Chenaghlu, Narjes Nikzad-Khasmakhi, Ali-Reza Feizi-Derakhshi, Mehrdad Ranjbar-Khadivi, Elnaz Zafarani-Moattar and Mohammad Ali Balafar.
[doi]  [BibTeX] 

2019

The state-of-the-art in expert recommendation systems.
Eng. Appl. Artif. Intell., 82:126-147, 2019.
Narjes Nikzad-Khasmakhi, M. A. Balafar and Mohammad-Reza Feizi-Derakhshi.
[doi]  [BibTeX] 

2016

A novel keyed parallel hashing scheme based on a new chaotic system.
Chaos, Solitons & Fractals, 87:216-225, 2016.
Meysam Asgari Chenaghlu, Shahram Jamali and Narjes Nikzad Khasmakhi.
[BibTeX] 

Dr.Narjes Nikzad Khasmakhi

Role
External Partner
Mail
narjes.nikzad@gmail.com
Room
B4.280