Israa

Ph.D candidate in
Computer Science

01

Know
About me

I am a Computer Science and Engineering Ph.D candidate at the University of Texas Arlington. My main research area is natural language processing, precisely, fact-checking.

I proudly belong to our beloved IDIR Lab , a nice place where we cook automatic fact-checking using data mining, NLP and AI methods, under the supervision of Dr. Chengkai Li.

At IDIR, we fight fake news, propaganda, and other forms of misinformation.

In March 2020, I was awarded - NSF Graduate Research Program Fellowship (GRPF) - National Science Foundation.
In April 2020, I was awarded an honorable mention - NCWIT Collegiate Award - National Center for Women and Information Technology, and January 2021, I was awarded an honorable mention - NCWIT collegiate award

02

My
Experience

  • August 2018 - Present

    University of Texas Arlington, Texas

    Ph.D student, Teaching Assistant, Research Assistant

    Fact-checking
    Studying methods of truth discovery using NLP and ML methods.

  • June 2022 - December 2022

    Intel Research Labs

    Graduate Research Intern

    Researched and experimented with different methods for multi-modal document grounded retrieval to aid an automatic task-guidance system. Research problems included unimodal and multimodal spec item retrieval for task-guidance and dynamic transcript segmentation for spec item retrieval.

    Leveraged Human In The Loop (HITL), model uncertainty estimation, and active learning in model creation and development.

    Applied the explored methods and new models to different domains including kitchens and manufacturing.

  • May 2021 - September 2021

    Apple Inc.

    Ph.D Machine Learning Engineering Intern

    Researched and heavily experimented different ML-based ASR architectures and models for Siri virtual assistant in collaboration with the ASR team at the Siri organization, which eventually lead to a relative improvement of 9% over the existing English ASR model.

  • December 2015 - July 2018

    Qatar Computing Research Institute (QCRI), Qatar

    Research Assistant

    Led a team of three scientists to study the detection of propaganda devices in textual data. Roles included the development of the full system pipeline and demo in addition to the collection and processing of the data set, developing and running experiments, collecting, analyzing and discussing results with the team, in addition to discussing and implementing ways of improving the performance of the system. Study details and demo at :https://proppy.qcri.org/

    Collaborated with the fact-checking team to build a cross-lingual claim-spotting system. Roles included the development of the full pipeline and demo, developing and running experiments, collecting and discussing results with the team. Find demo at : https://claimrank.qcri.org/

    Contributed to the development of a cross-lingual (Arabic-English) named-entity recognizer. Roles included partial development of the pipeline.

    Contributed to the study of fact-checking through source credibility by collecting the Arabic data sets.

    Developing systems that demonstrated the research work conducted at QCRI, such as community question-answering in the medical domain, cross-language community question answering, automated fact-checking, and propaganda detection in news articles.

    Developed systems that demonstrated research work conducted at QCRI, such as cross-language community ques-tion answering in the medical domain and cross-language fact-checking in community forums.

    Contributed to the development of the ”Jalees e-reader” Windows application. Roles included the development of front-end and back-end of the e-book store, selected features in the e-book reader, in addition to creating interactive content in the form of .epub. Find more at : http://www.jaleesreader.com/.

    Developed and maintained the Arabic Language Technologies team website.

  • September 2015 - January 2016

    University of Texas A&M, Qatar

    Part-time Research Assistant

    Developed a visual light decoder as a mobile application, a part of a study on Visual Light Communication System. Roles included the development of the Android decoder app, contributing to the design of the experiments, in addition to collecting and reporting results.

  • September 2013 - January 2015

    Jordan University of Science and Technology, Jordan

    Part-time Instructor

    Taught two programming credit courses : VB.NET and C++. Roles included teaching, posting and maintaining regular office hours, preparing and submitting syllabi and course outlines, serving on divisional committees as assigned, participating in college meetings and events, in addition to writing, supervising, and grading exams.

  • September 2011 - January 2013

    Jordan University of Science and Technology, Jordan

    Teaching Assistant

    Taught non-credit lab-based programming courses. Roles included teaching, posting and maintaining regular office hours, in addition to supervising, and grading exams.

03

My
Education

  • August 2018 - Present

    University of Texas Arlington, Texas

    Ph.D in Computer Science

    GPA: 4.0

  • January 2011 - August 2013

    Jordan University of Science and Technology, Jordan

    M.Sc in Computer Science

    GPA: 91.2%

  • September 2007 - December 2010

    Mutah University, Jordan

    B.Sc in Computer Science

    GPA: 87.15 %

04

Proudly contributed to the following projects:



1. A Dashboard for Mitigating the COVID-19 Misinfodemic
University of Texas at Arlington

Aims to build a dashboard that aggregates various metrics from various sources related to COVID19 and to present geographically-relevant social media posts and hospital information.

Publication: Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohammed Samiul Saeef, Paras Pathak and Chengkai Li. ” A Dashboard for Mitigating the COVID-19 Misinfodemic.” Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, 2021.


Find more about the project here

2. Jalees E-book Reader
Qatar Computing Research Institute

Jalees is an English and Arabic e-reader that supports ePub2, ePub3.

The Jalees Reader supports ebook files, from PDF to ePub, ePub2 and ePub3, including interactive content and embedded audio and video files.

Characteristics include a clean, simple design, an intuitive library offering Carousel and Tile modes, right-to-left and left-to-right user interfaces for reading, and a morphological search function for Arabic.

Jalees was developed by members of the Arabic Language Technologies team at the Qatar Computing Research Institute, in Doha, Qatar. Find out more about our research by visiting www.jaleesreader.com, or send an email to tellmemore@jaleesreader.com.






3. Community Question Answering in the Medical Domain
Qatar Computing Research Institute

a Demonstration of the research done in:

Romeo, Salvatore, Giovanni Da San Martino, Yonatan Belinkov, Alberto Barrón-Cedeño, Mohamed Eldesouki, Kareem Darwish, Hamdy Mubarak, James Glass, and Alessandro Moschitti. "Language processing and learning models for community question answering in Arabic." Information Processing & Management (2017).






4. Fact-checking in Community Forums -Demo
Qatar Computing Research Institute

a Demonstraction of the research done in:

Mihaylova, Tsvetomila, Preslav Nakov, Lluis Marquez, Alberto Barron-Cedeno, Mitra Mohtarami, Georgi Karadzhov, and James Glass. "Fact checking in community forums." In Thirty-Second AAAI Conference on Artificial Intelligence. 2018.





5. ClaimRank
Qatar Computing Research Institute

A mutilingual ranking system that scores sentences in text based on their priority for fact-checking. To try the demo, visit : claimrank.qcri.org . This work is published as:

Jaradat, Israa, Pepa Gencheva, Alberto Barrón-Cedeño, Lluís Màrquez, and Preslav Nakov. "ClaimRank: Detecting Check-Worthy Claims in Arabic and English." In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pp. 26-30. 2018.





6. Proppy
Qatar Computing Research Institute

A propaganda detection system that scores news articles based on their liklihood of having propagandistic content. To try the demo, visit proppy.qcri.org . This work is published as:

Barrón-Cedeño, Alberto, Giovanni Da San Martino, Israa Jaradat, and Preslav Nakov. "Proppy: A system to unmask propaganda in online news." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 9847-9848. 2019.





05

Publications

  • Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohammed Samiul Saeef, Paras Pathak and Chengkai Li. ” A Dashboard for Mitigating the COVID-19 Misinfodemic.” Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, (2021).

  • Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo,Jisun An, Haewoon Kwak, and Todor Staykovski, Israa Jaradat, Georgi Karadzhov, Ramy Baly, Kareem Darwish, James Glass, Preslav Nakov."Tanbih: Get To Know What You Are Reading".Proceedings of EMNLP-IJCNLP Demo Track" (2019).

  • Barrón-Cedeño, Alberto, Giovanni Da San Martino, Israa Jaradat, and Preslav Nakov. "Proppy: A system to unmask propaganda in online news." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 33. (2019).

  • Barrón-Cedeno, Alberto, Israa Jaradat, Giovanni Da San Martino, and Preslav Nakov. "Proppy: Organizing the news based on their propagandistic content." Information Processing & Management (2019).

  • Israa Jaradat, Pepa Gencheva, Alberto Barrón-Cedeño, Lluís Màrquez, and Preslav Nakov. "ClaimRank: Detecting Check-Worthy Claims in Arabic and English." In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pp. 26-30. (2018).

  • Joty, Shafiq, Preslav Nakov, Lluís Màrquez, and Israa Jaradat. "Cross-language learning with adversarial neural networks." In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pp. 226-237. (2017)

06

Contact Me

Email

israa.jaradat@mavs.uta.edu

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