M. Alizadeh and B. Di Eugenio. Augmenting Visual Question Answering with
Semantic Frame Information in a Multitask Learning Approach. In Proceedings of the
14th IEEE International Conference on Semantic Computing (ICSC 2020), San Diego, CA,
February 3-5. (Nominated for Best Paper Award)
M. Alizadeh and B. Di Eugenio. A Corpus for Visual Question Answering
Annotated with Frame Semantic Information. In Proceedings of the 12th Language Resources
and Evaluation Conference (LREC 2020). Marseille, France, May 11-16.
M. Alizadeh and B. Di Eugenio. Incorporating Verb Semantic Information
in Visual Question Answering through Multitask Learning Paradigm.
International Journal of Semantic Computing (IJSC), 2020, 25 pages.
O. AlZoubi, B. Di Eugenio, D. Fossati, N. Green, and M. Alizadeh.Learning
Recursion: Insights from the ChiQat Intelligent Tutoring System. In Proceedings of the
12th International Conference on Computer Supported Education (CSEDU 2020). May 2-4.
R. Harsley, N. Green, M. Alizadeh, S. Acharya, D. Fossati, B. Di Eugenio, O. AlZoubi.
Incorporating Analogies and Worked Out Examples as Pedagogical Strategies in a Com-
puter Science Tutoring System. Proceedings of the 47th ACM Technical Symposium on
Computer Science Education (SIGCSE). Memphis, TN, USA, 2016
N. Green, D. Fossati, B. Di Eugenio, R. Harsley, O. AlZoubi, M. Alizadeh. Student
Behavior with Worked-out Examples in a Computer Science Intelligent Tutoring System.
3rd International Conference on Educational Technologies. Florianopolis, Santa Catarina,
B. Di Eugenio, N. Green, O. AlZoubi, M. Alizadeh, R. Harsley, D. Fossati. Worked-
out Examples in a Computer Science Intelligent Tutoring System. The 16th Annual
Conference on Information Technology Education. Chicago, IL, 2015
O. AlZoubi, D. Fossati, B. Di Eugenio, N. Green, M. Alizadeh, R. Harsley. A Hybrid
Model for Teaching Recursion. The 16th Annual Conference on Information Technology
Education. Chicago, IL, 2015
. Green, O. AlZoubi, M. Alizadeh, B. Di Eugenio, D. Fossati, R. Harsley. A Scalable
Intelligent Tutoring System Framework for Computer Science Education. 7th International
Conference on Computer Supported Education (CSEDU'15). May 2015
M. Alizadeh, B. Di Eugenio, R. Harsley, N. Green, D. Fossati, O. AlZoubi. A Study
of Analogy in Computer Science Tutorial Dialogues. 7th International Conference on
Computer Supported Education (CSEDU'15). May 2015
Alizadeh, M., Ebadzadeh, M., Kernel Evolution for Support Vector Classification, IEEE Workshop on
Evolving and Adaptive Intelligent Systems, Paris 2011.
Babaeian, A., Alizadeh, M ., WordNet Based Features for Predicting Brain Activity Associated with
Meanings of Nouns, NAACL-HLT 2010, Los Angles, Workshop on Computational Neurolinguistics, pages
Natural Language Processing (NLP) Lab, University of Illinois at Chicago
Visual Question Answering (VQA), Deep Learning Researcher (January 2017 - August 2020)
Created a novel dataset (imSituVQA) annotated with semantic frame information.
Proposed a hyper-class augmented CNN-LSTM model in order to incorporate semantic frame information
NLP for Educational Technology, Research Assistant (August 2013 - December 2015)
Annotated tutorial dialogues to analyze and extract effective pedagogical strategies.
Collaboratively, developed an intelligent tutoring system for computer science education (Chi-Qat tutor).
Collaboratively, tested the system among 200+ undergraduate computer science students.
AT&T Labs, Data Scientist , Middletown, NJ (June 2016 - December 2018)
Collaborated in design and development of a large-scale machine learning pipeline with PySpark.
Designed and executed different experiments in order to improve pattern discovery and anomaly detection.