Iran University of Science and Technology

(Sep 2016 - Sep 2020)

B.Sc. Computer Engineering with concentration on SE

• Ranked 4th among Iran Universities based on QS Ranking
• GPA (Last two years via 68 credits): 3.85/4 (18.20/20)
• GPA (All 142 credits): 3.73/4 (17.51/20)

Farzanegan (NODET)

(Sep 2009 - Jul 2016)

MidSchool, HighSchool, PreUniversity

• National Organization for Development of Exceptional Talents
• GPA: 4/4

Cloud Computing Center Administrator

(Jun 2019 - Present)

Working as a Cloud Administrator in Cloud Computing Center of Iran University of Science and Technology:

• Installing and configuring OpenStack and some of its important tools and services such as: Nova, Neutron, Ceilometer, Gnocchi, Cinder, KeyStone, Glance, ...
• Preparing and configuring some Operating Systems like Windows as a Cloud-Ready image
• Serving IaaS to other laboratories

ChillinWars Developer

(Sep 2018 - Feb 2019)

• ChillinWars is the Iran University of Science and Technology’s AI contest. It’s been held every year in Iran as a well-known programming contest in the form of artificial intelligence implementation
• Working as a full-stack developer of Junior Game of this competition in 2018 -2019 with its exclusive framework

• Data Transmission
  (Instructor: Dr. Ahmad Akbari)
• Embedded Systems TA
  (Instructor: Dr. AmirMahdi Hosseini)
• Software Engineering TA
  (Instructor: Dr. Behrooz Minaei)
• Software Engineering TA
  (Instructor: Dr. Mehrdad Ashtiani)
• Database TA
  (Instructor: Dr. Eisa Zarepour)
• Data Structure TA
  (Instructor: Dr. Hossein Rahmani)
• System Analysis TA
  (Instructor: Dr. Mehrdad Ashtiani)
• Programming Basics TA
  (Instructor: Dr. Zeinab Movahhedi)

Back-end Developer at Iran Tourism Bank

(Apr 2021 - Present)

• Developed Back-End services for a Digital-Banking project based on Spring Boot and Spring frameworks
• Developed an API-Gateway-Manager for REST and gRPC
• Migrated the previous admin dashboard to a new one based on React js framework

Back-end developer of ”Teachent” Project

(Feb 2018 - Jun 2018)

• ”Teachent”: An application of a friendly startup with contribution of 5 developers

Security and Performance aware virtual machine placement in Cloud Computing centers

• Provided an algorithm to choose the best host for virtual machines in a way that they become safe against attacks and also increase performance in Cloud Computing environments

Peer to Peer file transfer

• Established two channels including Signaling channel and Data channel to transfer files between two peers
• Transfered file is done by Data channel which uses WebRTC

Long Polling

• Implemented Long Polling using XHR to see posts sent from someone dynamically with no refresh needed

Socket Programming

• Implemented a HTTP Web server using sockets
• Implemented a Client-Server communication via Socket Programming in which a client sends a matrix to another one by server and after multiplying the matrix by itself, server returns the result to the first client

Stream Processing

• Exchange Information Analysis with Stream Processing using Apache Storm

Implemented MPI (Message Passing Interface)

• Multiply huge matrices using multiple nodes
• Calculate the integral by the trapezoidal approximation method using distributed systems

Heart Diseases Recognition

• Implemented Decision Tree using Python and Sickit-learn to detect if someone is suffering from heart disease or no

Fraud Detection

• Implemented a SVM classification model to detect fraud

Evar Framework

• Implemented a Framework that others can develop websites like Divar and eBay

Pop vs. Traditional lyrics recognition

• Data collection, Data Extraction, Pre Processing, and primary data analysis
• Data Splitting, Implemented Language Model’s train phase, Implemented Perplexity calculation, Implemented Text Generation using Language model
• Implemented Naive-Bayes Classifier, Implemented Maximum Entropy (MaxEnt) Classifiers using Mallet and comparing these two approaches

Different Phonetics Detection

Solved ”Inverted Pendulum” using Fuzzy Logics

Image classification using Multi-Layer Perceptron for Hoda Data Set (Like MNIST but in Persian) using Numpy, Keras

Designed a noise-robust model using Hopfield Network for image detection

Function approximation using RBF (Radial Basis Function)

Gender Recognition using signal Processing and signal-based feature

Dual-Tone Multi-Frequency (DTMF) signaling

Yes-No Detection simulation practice