Graduate Research Assistant at R.I.T.
I am a third year Ph.D. student in Computing and Information Science at the Golisano College of Computing and Information Sciences, Rochester Institute of Technology (RIT) under the advisement of Prof. Matt Huenerfauth. My research goal is to build technologies that address real-world problems by integrating data-driven methods and human-computer interaction. I am interested in investigating human needs and challenges that may benefit from advancements in artificial intelligence. My research involves the application of machine learning and analytics research to benefit people with disabilities, especially assistive technologies that model human communication and behavior such as sign language avatars.
Abhishek Mhatre, Sedeeq Al-khazraji, Matt Huenerfauth. 2019 (to appear). "Evaluating Sign Language Animation through Models of Eye Movements." Journal on Technology and Persons with Disabilities, California State University, Northridge.
Abhishek Kannekanti, Sedeeq Al-khazraji, Matt Huenerfauth. 2019 (to appear). "Design and Evaluation of a User-Interface for Authoring Sentences of American Sign Language Animation." 21st International Conference on Human-Computer Interaction, Orlando, Florida, USA.
Sedeeq Al-khazraji, Larwan Berke, Sushant Kafle, Peter Yeung, and Matt Huenerfauth. 2018. "Modeling the Speed and Timing of American Sign Language to Generate Realistic Animations." The 20th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '18),
Best Paper Award.
Conference acceptance rate of 26%
Sedeeq Al-khazraji. 2018. "Using Data-Driven Approach for Modeling Timing Parameters of American Sign Language." In Proceedings of the Doctoral Consortium of the 20th ACM International Conference on Multimedia Interaction.
Sedeeq Al-khazraji, Sushant Kafle, and Matt Huenerfauth. 2018. "Modeling and Predicting the Location of Pauses for the Generation of Animations of American Sign Language." In Proceedings of the 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community, The 11th International Conference on Language Resources and Evaluation (LREC 2018),
Jigar Gohel, Sedeeq Al-khazraji, Matt Huenerfauth. 2018. "Modeling the Use of Space for Pointing in American Sign Language Animation." Journal on Technology and Persons with Disabilities, California State University, Northridge.
Dhananjai Hariharan, Sedeeq Al-khazraji, Matt Huenerfauth. 2018. "Evaluation of an English Word Look-Up Tool for Web-Browsing with Sign Language Video for Deaf Readers." Universal Access in Human-Computer Interaction, Lecture Notes in Computer Science.
Sedeeq Al-khazraji and Matt Huenerfauth. 2017. Modeling the Distribution of Spatial Reference Points Established in Space by American Sign Language Signers in a Motion Capture Data Corpus. 10th
Annual Graduate Showcase, Rochester, New York, USA. November 3, 2017. Poster Presentation.
Best Poster Award
Sedeeq Al-khazraji and Matt Huenerfauth. 2017. Modeling the Speed and Timing of American Sign Language to Generate Animations. Effective Access Technologies Conference, Rochester, New York, USA. April 21, 2017. Poster Presentation.
Sedeeq Al-khazraji and Matt Huenerfauth. 2017. Modeling the Speed and Timing of American Sign Language to Generate Animations. Move 78 Retreat on Artificial Intelligence, Rochester Institute of Technology, Rochester, New York, USA. February 17, 2017. Poster Presentation.
Ph.D. Candidate - Rochester Institute of Technology, 2015 -
M.S. - University of Mosul, 2008 - 2011
Master’s Thesis: Implementing Real-Time Appliances in Heterogeneous Operating Systems.
B.S. - University of Mosul, 2000 - 2004
Graduated with Honors, achieving the second highest GPA among all graduating students of the Department of Computer Sciences.
Built state-of-the-art AI applications using PyTorch deep neural networks.Deep Learning GitHub Repository
Completed Stanford University's Machine Learning course on Coursera.Jupyter Notebooks and Matlab Codes
Completed 4 out of 11 courses.my edX profile
Created predictive models for American Sign Language (ASL) animations using Python and XML. Applied feature engineering on sentence syntax to predict appropriate ASL speeds and timing transitions. Trained classifiers using Python and Matlab to predict natural pauses: Linear-Chain CRF, Tree Based, and SVM models. The final model outperformed the baseline with 80% F1-Score accuracy. Identified appropriate signing speed through a Gradient Boosted Regression Trees model using Python and R. The final model outperformed state-of-the-art rule-based models with a 23.8% lower RMSE score. Visualized the locational distribution of the three most common pointed clusters in ASL. Implemented a Gaussian Mixture Model (GMM) of 3D motion capture data in Python.
Managed and collaborated with a full-stack platform team of user experience researchers, designers, and software engineers. Supervised master students in system GUI design and backend programming of the EMBR system.
Udacity & Dubai Future Foundation: Tutored students on SQL, statistics, and data analysis at the "One Million Arab Coders" initiative.
National Science Foundation (NSF-REU): Mentored undergraduate students on research methods and statistics.
Taught a wide range of courses in Computer Sciences (Software Programming, Structured Programming, Distributed Databases, Linux Operating System, etc).
Taught industry training workshops on SQL server and C# for government employees.
Served on various university committees.
Developed multiple applications for companies and large government organizations, e.g. the Department of Education for the City of Nineveh. Gathered user requirements, defined system functionality, and wrote code in Visual C#, VB.NET, ASP.NET, and C++ using various database management systems (e.g. Microsoft SQL Server). This project increased employee productivity in record automating and improved human resources department functionality.
Developed applications for individual customers and small businesses. Gathered user requirements, defined system functionality, and wrote code in Visual Basic and C++ using database management systems such as SQL Server, Oracle, and Microsoft Access.
Presented at ACM SIGACCESS Conference on Computers and Accessibility
R.I.T Graduate Showcase
Full scholarship and stipend support for Ph.D. study
Ranked 2nd out of 73 students (Top 5%) in the College of Computer Sciences and Mathematics for B.S. study
If you have any questions please do not hesitate to contact me.
Phone +1 (585) 406-8767
102 Lomb Memorial Drive
70-1620 Computing and Info Sciences
Rochester, NY 14623