CV

Education

• MSc in Computer Science University of Winnipeg, Winnipeg, Canada July. 2022(Expected) Thesis Title: Robust field plant identification through indoor imagery using novel image augmentation and adversarial networks algorithms Advisor: Dr. C. Henry, Dr C.Bidinosti

• BSc in Engineering Science, Mathematical Engineering University of Tehran Awarded Winter 2018
  Thesis Title: Deep learning architectures and their utilities, Advisor: Dr. Mahmoud Shabankhah

Research Interests

Computer Vision, Object Detection, Data Mining, Natural Language Processing- Experienced Data Scientist with a demonstrated history of working on projects encompassing Computer Vision, Image Processing and Digital Agriculture. Skilled in Machine Learning Algorithms, Data Mining, Data Analysis and Supervised and Unsupervised learning.

Work experience

• Mitacs Accelerate Intern GPU Educational Lab, University of Winnipeg Sep. 2019–present Member of the digital agriculture research project, Improving detection metrics of field crops with data Augmentation Using Generative Adversarial Networks, object detection and computer vision algorithms

• Lab assistant, Applied Statistics for Data Science PACE, University of Winnipeg Nov2021-Dec2021
• Lab assistant, Data Acquisition for Data Science PACE, University of Winnipeg Jan2022-Feb2021

• Exam Proctor (Math, Physics, Accessibility Services) University of Winnipeg Sep2021-present

• Teaching Assistant for parallel programming University of Winnipeg Sep 2021-present

• I.T consulting and Translator ADA Hamrang Andisheh Farda Aug2016– Jun 2018 Translation and correspondence with foreign clients

• Undergraduate Intern at NLP lab of University of Tehran Tehran, Iran Summer 2014
  Implementing and designing methods in python to extract and store information from Wikipedia’s infoboxes to be later used for an experimental search engine

Programming and Technical Skills

• Python, Matlab, Java, C/C++, Keras, Tensorflow, Pytorch, Numpy, AWS, Docker, CSS, Cuda, SQL, JSON.

Projects

• Optimization of security measures in Cloud service providers allocation Spring 2020 through a Tabu search algorithm within the multi-goal programming paradigm

• Learning in the presence of dataset unbalancedness in computer vision Spring 2020 for digital agriculture plant classification task using VGG-19 and ResNet-50 as base models

• Optimized and time-efficient quick select algorithm through parallelization using Fall 2019 CUDA
• Designed an accurate & robust image segmentation tool in Java using maximal Fall 2019 graph flow algorithms (Ford-Fulkerson and Edmond-Karp algorithms)

Selected Graduate Courses

• Parallel Programming, Advanced Machine Learning, Advanced algorithms, Data Structures, Advanced Programming, Logic for CS, Artificial Intelligence, Internet Algorithm, Operation Research, Linear Algebra