About Me

Parsa Abbasi is a graduate student in Artificial Intelligence at Iran University of Science and Technology, where he conducts research focused on enhancing graph attention networks for relational graphs. His research aims to advance existing architectures like RAGAT by proposing and developing a model with fewer training parameters to prevent overparameterization. Additionally, he explores dynamic attention mechanisms to effectively capture the relational information within the graph.

Parsa received his BSc in Computer Engineering from the University of Guilan, where he explored areas such as natural language processing and deep learning. During his undergraduate studies, Parsa co-authored a research paper on designing sentiment analysis models using deep learning architectures for low-resource Persian language.

Driven by his passion for the field, Parsa seeks to pursue a PhD in AI to continue his research and further advance the field.

  • Graph Neural Networks
  • Relational Graphs
  • Natural Language Processing
  • Deep Learning
  • MSc in Artificial Intelligence, 2020 - Ongoing

    Iran University of Science and Technology

  • BSc in Computer Engineering, 2015 - 2019

    University of Guilan


Programming Languages

python (proficient), java (experienced), matlab and c++ (amateur)

Machine/Deep Learning

keras, pytorch, scikit-learn, imbalanced-learn, h2o

Data Science

numpy, pandas, plotly, matploblib, sql


Data Scientist and Instructor (Part-time)
Feb 2022 – Present Tehran, Iran
  • Conducting an online Machine Learning course, which included lectures, coding assignments, quizzes, and a beta-testing process consisting of guiding and monitoring a team of more than 10 beta-testers.
  • Led the update and debug procedures for the Data Analysis course, working with a team of three debuggers to enhance the course material and fix bugs.
  • Improved the automatic grading system for the Data Analysis course to provide more detailed feedback to students.
  • Guided students in both the Data Analysis and Machine Learning courses, answering more than 450 clarifying questions and receiving excellent feedback from students (4.9/5.0 average rating).
  • Gained expertise in designing educational materials, developing course content and objectives, mentoring learners, and optimizing course feedback mechanisms, all while working with diverse teams.
IUST Data Mining Lab
Natural Language Processing Researcher
Dec 2020 – Dec 2021 Tehran, Iran
  • Researched Abstractive Text Summarization using cutting-edge deep learning architectures, specifically transformer-based models.
  • Deployed a highly successful model that achieved exceptional Rouge scores in generating Persian news headlines.
Guilan NLP Group
Natural Language Processing Researcher
Oct 2018 – Jul 2019 Rasht, Iran
  • Presented a Sentiment Analysis system for Persian language, utilizing deep learning and machine learning models such as Bi-LSTM, CNN, and SVM, and incorporating NLP concepts such as word2vec and fasttext.
  • Designed innovative text data augmentation techniques to enhance the performance of sentence-level binary classification and multiclass classification, yielding accuracy rates up to 91% and 67%, respectively.
  • Co-authored a research paper which was presented at the Fifth National Conference on Computational Linguistics, Linguistics Society of Iran.
University of Guilan
Distributed System Intern
Jul 2018 – Sep 2018 Rasht, Iran
  • Implemented an effective Distributed System based on the MPI model, providing parallel computing for computer engineering students.
  • Demonstrated proficiency across various tools and methodologies, including Networking, SSH, NFS, and MPICH, among other relevant technologies.

Recent Publications

Quickly discover relevant content by filtering publications.
(2020). DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus. arXiv.

PDF Cite Code Dataset

(2019). Presenting A Sentiment Analysis System Using Deep Learning Models On Persian Texts (In Persian). In the 5th National Conference on Computational Linguistics of Iran.

PDF Cite Dataset DOI

Teaching Experience

Quera Data Analysis Bootcamp
Apr 2023 – Apr 2023 Online
  • Delivered engaging instruction on data wrangling and visualization using essential Python libraries, including NumPy, Pandas, Matplotlib, Seaborn, and Plotly to learners of various levels. Demonstrated the practical applications of each tool by providing coding examples based on real-world scenarios.
  • Also provided instruction on web scraping concepts and tools, to impart knowledge about data acquisition from web pages.
Quera Data Analysis Bootcamp
Instructor and Mentor
Dec 2022 – Feb 2023 Online
  • Instructed on various machine learning algorithms that are helpful for data analysis tasks and more interpretable, such as decision tree and K-NN algorithms
  • Taught web scraping concepts and tools, including BeautifulSoup, Scrapy, and Selenium, to a diverse group of students, providing coding demonstrations and examples from real-world scenarios.
  • Successfully led and coordinated a team of five students through exercises and projects, including developing an agile plan to ensure timely completion of their work.
  • Evaluated team projects by assessing presentations, critiquing proposed solutions, implementation strategies, and final outcomes, while providing constructive feedback and assigning scores based on objective criteria.
  • Collaborated closely with other mentors and organizers and actively participated in weekly discussions to evaluate course objectives and improve student engagement.
Quera Deep Learnin]«g Bootcamp
Workshop Instructor
Quera Deep Learnin]«g Bootcamp
Mar 2022 – Mar 2022 Online
  • Conducted an engaging workshop on deep learning techniques for image processing, leveraging Convolutional Neural Networks (CNNs), ResNet, and U-Net architecture.
  • Developed and identified challenging hands-on projects to provide participants with practical, real-world experience in solving complex image processing tasks, such as Image Classification and Image Segmentation.
University of Guilan
Natural Language Processing Teaching Assistant
University of Guilan
Oct 2019 – Jan 2020 Rasht, Iran
University of Guilan
Language and Automata Theory Teaching Assistant
University of Guilan
Mar 2018 – Jun 2018 Rasht, Iran
  • Provided educational materials, including weekly homework assignments.
  • Conducted weekly clarification sessions to ensure students understood course material.
  • Instructor: Dr. Seyed Mohammadhossein Shekarian
University of Guilan
Data Structure Teaching Assistant
University of Guilan
Sep 2017 – Dec 2017 Rasht, Iran


Throughout his academic journey, he has completed various online courses. However, in recent years, he has been relying on several learning resources, such as Youtube videos, online articles, academic papers, and books, to acquire knowledge.

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