Data Scientist & AI Developer

Programming: Python (TensorFlow, PyTorch, OpenCV, Numpy, Pandas), C++, SQL, MATLAB
AI Frameworks: Transformers, Generative Adversarial Networks (GANs), Self-Supervised Learning
Cloud Platforms: Google Cloud Platform (Vertex AI), AWS
Tools: Git, Anaconda, HalCon MvTec, Pycharm, Overleaf

Education

M.Sc., Automated Engineering Montreal (2020 - 2022)
- Focus: Self-supervised learning, unsupervised algorithms, and computer vision without manual annotations.
M.Sc., Information Technology Engineering Rasht (2013 - 2015)
- Focus: Evaluating edge detection methods in remote sensing images using fuzzy logic.
B.Sc., Software Engineering Rasht (2008 - 2012)

Developed and implemented ML techniques to enhance client solutions and existing products.
Automated data preprocessing and analysis pipelines using Google Cloud Platform (Vertex AI).
- LeadCast

Taught Data Science, Python Programming, and Machine Learning.
Designed and delivered courses, emphasizing time series analysis and wearable device data processing.
Mentored students on data science projects and practical applications.

Built Computer Vision and Image Processing solutions, including a pix2pix GAN for high-quality image synthesis.
- Glare Correction
- Color Correction
Developed data augmentation pipelines and AutoEncoder-based architectures for state-of-the-art image generation.

Led deep learning initiatives for creating high-quality, scalable holograms from images.
Integrated TensorFlow and PyTorch within robust MLOps frameworks to optimize model scalability and efficiency.

Enhanced defect detection accuracy in semiconductor fabrication using CNNs and transfer learning.
Applied GAN-based data augmentation to improve training dataset diversity.

Utilized GANs for data augmentation to enhance anomaly detection models.
Conducted comparative studies on unsupervised generative models, including VAEs and GANs, for high-quality image generation.

Simultaneous Detection of Regular Patterns in Ancient Manuscripts Using GAN-Based Deep Unsupervised Segmentation. ICPR Workshops, 2021. Publication
A Two-Stage Unsupervised Deep Learning Framework for Degradation Removal in Ancient Documents. ICPR Workshops, 2021. Publication
Overcoming Limited Dataset Issues in the Semiconductor Domain Using Deep Learning. NEWCAS Conference, 2019. Publication)
Evaluation of Fuzzy Edge Detection in Remote Sensing Images. Master’s Thesis, 2015.