CV

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General Information

Full Name Omid Sadeghnezhad
Date of Birth 2nd February 1997
Languages Reading, writing and speaking competencies for English, Native Persian.

Research Interests

  • Generative Adversarial Networks and Diffusion models especially in computer vision and image processing fields
  • Object Detection and Tracking models
  • Image processing and computer vision
  • Signal processing and analyzing

Research Experience

  • Evolutionary Algorithms and implementing Symbiotic Organisms Search algorithm (SOS) - 2023
  • GAN Developments survey and Analyze the Latent space. (Basic GAN, DCGAN ACGAN, WGAN, BigGAN, PGGAN, STYLEGAN, STYLEGAN2, StarGAN, SEAN) - 2022
  • Theories of Multimodal deep learning - 2021
  • Clothes virtual try-on models survey. (ACGPN, SwapNet, CP-VTON-PLUS) - 2020
  • Image harmonization and blending methods (Dovenet, DeepImageBlending), Brightness transfer (global and local transfer), color transfer methods (mean-std transfer, Lab mean transfer, and pdf transform), and color constancy with image to image translation (pix2pix, CycleGAN, and contrastive-unpaired-translation) - 2020
  • Image depth extractions (monoDepth, Pydnet) and salient object detection models (Basnet, U2Net, PoolNet, CPD) - 2020

Education

  • 2020-2023
    Master
    K. N. Toosi University of Technology
    • Artificial Intelligence.
    • Seminar
      • Generative Adversarial Networks (GAN) Survey
  • 2015-2020
    Bachelor
    Shahrood University of Technology
    • Electrical and Electronics Engineering

Experience

  • 2021-present
    Machine Learning Engineer
    Parstech.Co
    • Description 1.
    • Description 2.
    • Description 3.
      • Sub-description 1.
      • Sub-description 2.
  • 2020-2021
    Machine Learning Engineer
    TaraTech.Co
    • Description 1.
    • Description 2.
  • 2019-2020
    Internship
    Telecommunication Company of Iran

Skills

Coding
Python, sql, C, C++, LATEX
Databases
MYSQL, SQlite, Redis
ML Frameworks
Pytorch, Scikit-Learn
Misc.
Multi Processing and Threading Programming , Managing Shared Memory in Python , Implementing API with FastAPI , Data Transferring with SocketIO , Task Queuing and Management with Celery , Image and Video Processing with OpenCV , Video Streaming and Create Pipeline with Gstreamer , Deep Neural Networks Implementation with PyTorch , Docker Container for DevOps , Version Controling with Git

Projects

  • 2022-present
    Parstech Video Intelligent Assistant
    Intelligent Security Assistant
    • AI assistance to process and analyze videos with modules like human detection, face recognition, and license plate recognition. I deeply worked on human detection and restriction area application, Camera handling and streaming, DevOps, and microservices of this application.
    • Features
      • Human detection and tracking
      • Video Processing with OpenCV
      • FastAPI implementation for APIs
      • Gstreamer and OpenCV cores for the Camera management service
      • Task queueing and workflow management with Celery
      • Containerized services
      • In-Memory data transfer with Redis and python shared memory
      • Multi-Processing and Multi-Threading features implemented
  • 2022
    LipReading model on Persian Dataset
    • Train a LipReading model on the Persian dataset.
  • 2021
    Personal Protective Equipment (PPE)
    Implementation of a system to identify personal safety equipment
    • A program to identify workers’ safety equipment in workshop and construction environments, such as gloves, helmets, glasses, masks, safety vests, warning capabilities for people who enter prohibited areas, fire detection, and identification of work tools.
    • Features
      • Human detection and tracking
      • Pose estimation to check human body status
      • Body part localizer for head, hands, and chest
      • Equipment classifiers models
      • Pipeline implementation to estimate human fall
      • Faster functions with numba jit compiler
  • 2021
    Pressure Ulcer
    • Analysis of pressure sensor data of hospital beds for prediction and diagnosis of bed sores.
    • Features
      • Body Segmentation Models.
      • Pose estimation model for pressure sensor data
      • Video processing with OpenCV
      • Signal Capturing from human poses
  • 2021
    Cardiac Medical Data Augmentation
    • Train ACGAN on real Cardiac Medical Data in order to generate fake data for augmentation.
  • 2021
    Human localization
    • In two categories of foreground and background images, it takes a personal image from the foreground, and in order to place it in the background image, it first finds the right place then masks the image and places it in the background, and then corrects the color and light also improves the image by a model.
    • Features
      • Depth Estimation
      • Image brightness correction & Color correction models
      • Object detection models to find humans and other objects in the Image.
      • Image Perspective calculation
      • Image blending
  • 2021
    OCR
    • Optical Character Recognition on German administrative forms.
    • Features
      • Use tesseract and self-trained text recognition neural network.
      • Use Clustering algorithms to find lines.
      • Use OpenCV and Image processing methods to find information blocks.

Interests

  • Guitar
  • Video Game
  • Ping Pong
  • Natrue Lover
  • Psychology & Philosophy