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MohammadJavad Ardestani


Computer Engineering student
Amirkabir University of Technology - Tehran Polytechnic


Hello there!
I'm Mohammad Javad Ardestani, a senior undergraduate student studying Computer Engineering at the Amirkabir University of Technology, majoring in Artificial Intelligence and minoring in Computer Networks. I am fascinated by Deep Learning, and Machine Learning applied to Natural Language Processing and Computer Vision. I have two years of research experience in these fields.
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Education

Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
B.Sc. of Computer Engineering, Major in Artificial Intelligence and Minor in Computer Networks.
GPA: 3.95/4 (18.87/20)
Duration: Fall 2018-Winter 2023 (Expected)
Sattari High School (NODET), Tehran, Iran
High School Diploma, Mathematics and Physics.
GPA: 4/4 (20/20)
Duration: Fall 2014-Spring 2018

Research Experience

Research Intern, AGH University of Science and Technology, Krakow, Poland (July 2022-Now)
Supervisor: Dr. Lukasz Sztangrety, Applied Computer Science and Modelling Department
  • Different neural networks are trained by balanced datasets to simulate multi-variable functions.
  • Adaptation algorithms are customized to overcome overfitting in Incremental Learning.
  • Neural networks are adopted with online samples of only one class without overfitting.
Research Assistant, Amirkabir University of Technology, Tehran, Iran (June 2021-Now)
Supervisor: Dr. Hossein Zeinali, Computer Engineering Department
  • Large-size book embeddings are represented by using a CNN model and Transfer Learning methods.
  • Similarity score is estimated by SVR, KNN, and different document similarity techniques.
  • Content-based book recommender system is implemented using CUDA parallel computing.
  • An efficient retrieval system implemented to find similar paragraphs in books for a paragraph query.
Research Intern, Institute For Research In Fundamental Sciences, Tehran, Iran (June 2020-March 2021)
Supervisor: Dr. Dara Rahmati, , Computer Science Department
  • Tensor-based methods were developed for non-binary Decision-Making problems.
  • Matrix-based methods were upgraded for Random Walk process in binary decision-making problems.

Skills

Programming Languages: Python, C, C++, MATLAB, Java, Go, Bash.
AI Tools/Frameworks: PyTorch, TensorFlow, Keras, Scikit-learn, OpenCV, NumPy, Pandas, Matplotlib
Tools: Git, Docker, Arduino, Postman
Operating Systems: Ubuntu, MacOS, Windows
Web Programming: Flask, Django, HTML5, CSS, JavaScript
Typesetting Tools: Vim, Latex, Microsoft office(Word, Powerpoint, Excel), Prezi

Languages

Persian: Native
English: Full professional proficiency

Notable Projects

Medical Image Processing
Python Image Processing Transfer Learning CNN
In this Image processing project, I used a CNN classifier to classify COVID-19 Infected Lung Xray images from Healthy Lung Xray images.
  • A Classifier is implemented for detecting COVID-19 Infected based on ’Lung X-ray images’.
  • Pre-trained DenseNet-121 is used as the model's core as a means to Transfer Learning.
  • generalization evaluated by a selection of samples from three different data sets
Report | Code
Data Mining Projects
Python Data Mining Tensorflow XGBoost ARM Clustering
This repository contains five different projects. In each of these projects, essential subjects of Data Mining are covered.
  • Using XGBoost classifier for Diabetes Detection
  • Iris dataset analysis by Pandas and scikit-learn
  • Classification by neural networks in Tensorflow
  • Association Rule Mining by Apriori algorithm
  • Clustering by DBSCAN and K-means
Report | Code
NLP with Classification and Vector Spaces Course Projects
Python NLP LSH Naive Bayes Logistic Regression
This project contains Implementations of this NLP course. It divided into Four parts:
  • Translation as linear transformation
  • Sentiment analysing using Logistic Regression
  • Classification using Naive Bayes Classifier
  • Finding the most similar tweets using Locality Sensitive Hashing
Report | Code
Information Retrieval System
Python NLP ElasticSearch Ranked Retrieval
This is project is implemented for ISNA news agency dataset in four phases:
  • Boolean retrieval and spell correction systems are implemented using the Elasticsearch.
  • Tokenizer and normalizer functions are implemented for Persian texts.
  • Champions list and heapsort methods are used for efficient query responding and ranked retrieval.
  • K-means and KNN algorithms are used to speed up query responding.
Report | Code
Evolutionary Helicopter Game
Python Evolutionary Algorithems MLP
In this game, helicopters, as an evolutionary model, can determine when to move upward and downward to overcome all obstacles.
  • MLPs are considered entities in the evolution process that make decisions for movements.
  • ANNs are fed by the horizontal and vertical distance of the first obstacle and the helicopter location.
  • The roulette wheel is used for next-generation selection
  • The next-generation population is generated by the crossover method and mutated by Gaussian noise
Report | Code
ANN Framework From Scratch for Handwritten Digit Recognition
ANN Pattern Recognition Adversarial Attack
In this project, I developed an ANN framework from scratch that can be used to train and evaluate Fully Connected Neural Networks for different tasks.
  • An adaptable framework is implemented to define fully connected neural networks.
  • An FCNN is trained and evaluated to classify MNIST dataset.
  • The Impact of adversarial attacks is measured by shifting digit pattern matrices.
Report | Code
Classic AI Projects
Python CSP Backoff Models BFS IDS A*
  • Sudoku tables are solved as a Constraint Satisfaction Problem using the backtracking algorithm.
  • Poets are identified by calculating probabilities using Unigram, Bigram, and Backoff models.
  • Colored cards are sorted by BFS, IDS, and A* with a heuristic function.
Report | Code

Presentations

Convolutional Neural Networks
  • Data Mining Course
  • Dr. Ehsan Nazerfard
  • Amirkabir University of Technology
Slide | Report
Introduction to Neural Networks and Word Embedding
  • Information Retrieval Course
  • Dr. Ahmad Nickabadi
  • Amirkabir University of Technology
Slide | Video
An Analysis of IoT Cyber Security Techniques Driven By Machine Learning
  • Research and Technical Presentation Course
  • Dr. Reza Safabakhsh
  • Amirkabir University of Technology
Slide | Report | Video
Decision Making Methods
  • Startup Development Course
  • Dr. Hamed Ghanadpour
  • Amirkabir University of Technology
Slide | Video
Tensor Method For Analyzing Multi-Dimensional Diffusion Models
  • IPM Intern's Seminars
  • Dr. Dara Rahmati
  • Institute for Research in Fundamental Sciences (IPM)
Slide

Notable Courses

Related Courses, Amirkabir University of Technology
  • Data Mining (19.8/20)
  • Information Retrieval (20/20)
  • Principles of Computational Intelligence (19/20)
  • Artificial Intelligence (20/20)
  • Data Structures and Algorithms Design (20/20)
  • Principles of Cloud Computing (20/20)
  • Computer Networks (19.6/20)
  • Operating Systems (19.5/20)
  • Research and Technical Presentation (19.2/20)
  • Software Engineering I & II (20/20)
    • Online Courses, Coursera

    Teaching Experience

    Teaching Assistant, Amirkabir University of Technology
    • Information Retrieval, Dr. Ahmad Nickabadi | Fall 2021, Spring 2022
    • Computer Architecture, Dr. Hamed Farbeh Spring 2022
    • Algorithm Design, Dr. AliReza Bagheri | Fall 2021
    • Applied Linear Algebra, Dr. Mostafa Haghir Chehraghani | Spring 2021
    • Applied Linear Algebra, Dr. Ehsan Nazerfard | Fall 2020
    • Principles Of Programming, Dr. Bahador Bakhshi | Fall 2019
    Part Time Instructor, Tehran Institute of Technology (MFT)
    • Artificial Intelligence and Machine Learning | Fall 2021-Now
    • Python Programming | Fall 2020-Now
    • C, C++ Programming | Fall 2019-Fall 2020

    Honers & Awards

    Extra Curricular & Leadership