About me

I’m a Computer Engineering graduate from Amirkabir University of Technology (AUT) in Iran. My interest in AI began during high school, where I was fascinated by its potential to transform the world. This passion led me to focus on AI throughout my studies at AUT, allowing me to gain a deep understanding of this growing field.

What makes my approach unique is that I don’t limit myself to one specific area of AI. I believe in exploring different concepts like Data Mining, Computer Vision, NLP and Trustworthy AI. This broader perspective helps me come up with new ideas and tackle a variety of challenges.

With a solid foundation in these areas, I’m always eager to continue learning and apply my skills to solve new problems in the AI landscape.

Main Research Interests

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    Data Mining & Deep Learning

    I am passionate about leveraging data mining and deep learning approaches to solve complex problems across various domains. My primary focus lies in applying these algorithms to time series data, gaining valuable insights from spatio-temporal patterns.

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    Computer Vision

    Working with images has always been one of my core interests, leading me to explore different computer vision tasks. I have completed several projects in areas such as Object Detection, Face Reconstruction, and Image Classification.

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    Trustworthy AI

    I am passionate about Trustworthy AI because it addresses the real-world challenges of deep learning models. My interests include tackling problems like out-of-domain generalization, adversarial attacks and defenses, and anomaly detection, especially in vision models.

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    Human Computer Interaction

    In addition to the software side, I found working with microcontrollers and sensors to be incredibly fascinating. In my first academic paper, we developed an end-to-end approach to detect Persian Sign Language glosses. I believe this area holds immense potential for advancing human-computer interaction.

Resume

Education

  1. Amirkabir University of Technology, Tehran, Iran 2019 — 2024

    Computer Engineering

    GPA: 18.16/20 = 3.83/4

  2. Allameh Helli High School (NODET), Tehran, Iran 2016 — 2019

    Mathematics & Physics

    GPA: 19.45/20 = 4/4

Research Experience

  1. Undergraduate Research Assistant Dec 2023 — Aug 2024

    Amirkabir Uni. of Tech. - Dr. Ehsan Nazerfard

    For my Bachelor's thesis I developed a data mining system to extract offensive chance creation patterns in football teams. The project included:

    • - Preprocessing Statsbomb ball-event data to extract relevant time series data

    • - Applying time series clustering algorithms to group data based on spatial features

    • - Ranking the clusters based on user relevance

    • - Utilizing sequence matching algorithms to identify and rank offensive tactical patterns

    • - Implementing a visual dashboard enhance project usability for target users

  2. Undergraduate Research Assistant Jan 2022 — Apr 2024

    Amirkabir Uni. of Tech. - Dr. Hamed Farbeh

    In my first academic paper, my colleagues and I developed a cutting-edge sign language recognition system. Our main contributions included:

    • - Designing a specialized sign language glove equipped with Arduino and five flexible sensors

    • - Collecting the largest Persian Sign Language dataset at the time.

    • - Implementing an end-to-end deep learning framework for accurate sign language recognition using CTC loss function

    • - Introducing a novel ensembling algorithm for grammar-agnostic sequence-to-sequence tasks

  3. Undergraduate Research Assistant Feb 2022 — Jun 2022

    Amirkabir Uni. of Tech. - Dr. Reza Safabakhsh

    As part of the ‘Research and Technical Representation’ course at AUT, I conducted an in-depth study on classic edge detection algorithms for grayscale images . The research included:

    • - Conducting a comprehensive literature review on traditional edge detection methods

    • - Implementing algorithms such as Sobel, Prewitt, Roberts Cross, LoG, Boolean Function, and Canny using OpenCV, followed by a comparative analysis of their performance

Work Experience

  1. Artificial Intelligence Intern, AI Medic Jul 2022 — Sep 2022

    Tehran, Iran

    • - Studied various CNN architectures such as LeNet, AlexNet, VGGNet, GoogleNet, and ResNet.

    • - Implemented a CAPTCHA recognision system using Tensorflow.

    • - Ranked in the top 3 out of 50+ interns, securing a full-time job offer.

  2. Backend Developer, Danio Mar 2022 - May 2022

    Tehran, Iran

    • - Developed APIs using Django REST framework.

    • - Deployed backend and frontend servers using Docker.

  3. Backend Developer, Farazpardazan Mar 2021 — Aug 2021

    Tehran, Iran

    • - Developed Ayandeh Bank Customer Club web app APIs using Spring framework.

    • - Worked with databases like MySQL and PostgreSQL and optimized queries.

    • - Learned agile software development method.

Freelance Projects

  1. Perfume Recommendation System May 2024 — Oct 2024

    Tehran, Iran

    A system for recommending perfumes to customers in perfume shops

    • - Utilized clustering algorithms to cluster perfumes based on their accords and notes.

    • - Implemented a recommendation system based on users preference.

  2. Detecting Parasites in Pets Microscopic Images Sep 2022 - April 2023

    Berlin, Germany (Remote)

    An object detection system to detect and locate pets parasites in microscopic images

    • - Utilized object detection models (YOLO, Faster RCNN, RetinaNet) to detect pets parasites.

    • - Designed a Flask web server to upload the samples and recieve the results.

    • - Deployed the project on an Amazon EC2 instance. (Delievered to a real laboratory)

Teaching Experience

  1. Elementary Image Processing Fall 2023

    Dr. Hamed Azarnoush

  2. Principles of Computational Intelligence Spring 2023, Fall 2023

    Dr. Mohammad Mehdi Ebadzadeh

  3. Internet of Things Spring 2023

    Dr. Siavash Khorsandi

  4. Advanced Programming Spring 2021

    Dr. Hossein Zeinali

  5. Fundamentals of Programming Fall 2020

    Dr. Hossein Zainali


Certificates

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      Neural Networks and Deep Learning

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      Structuring Machine Learning Projects

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      Improving Deep Neural Networks

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      NLP with Classification and Vector Spaces

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      NLP with Probabilistic Models

Public Projects

Publications

  • PenSLR: Persian end-to-end Sign Language Recognition Using Ensembling

    Arxiv

    PenSLR: Persian end-to-end Sign Language Recognition Using Ensembling

    Sign Language Recognition (SLR) is a fast-growing field that aims to bridge communication gaps between the hearing-impaired and others. Solutions for Persian Sign Language (PSL) are limited to word-level interpretations, underscoring the need for a system that can interpret complex gesture combinations in an end-to-end manner.

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