Curriculum Vitae

York University – M.A.Sc in Electrical and Computer Engineering

• Supervised by Prof. Nikolaus Troje and co-supervised by Dr. Marcus A. Brubaker
• Thesis: Viewpoint synthesis for real-time applications in telecommunication
• GPA: 8.75 (9.0 scale)

University of Tehran – B.Sc. Electrical Engineering

• Supervised by Dr. Reshad Hoesseini.
• Thesis: Obtaining Car Specifications in License Plate Tracking System
• GPA: 18.59 (20.00 scale)
• Rank 3^rd out of approximate 110 undergraduate students.

University of Tehran – Minor. Computer Engineering

• GPA: 17.00 (20.00 scale)
• Passed a number of Computer Engineering Courses.

Machine Learning Resarcher - 3D Computer Vision at Huawei

• Invent state-of-the-art AI and computer vision algorithms to be published in top AI/CV conferences.
• Design and implement AI/CV solutions to real-world problems and land them in various Huawei products.
• Support R&D in the domains of 3D digitalization, 3D geometry and texture editing, human motion synthesis, 3D character animation and human-machine interaction.

Machine Learning Engineer Technical Advisor at Vector Institude

• ML Engineer Technical Advisor for the Data Readiness and Model Deployment (DaRMoD) program.
• Supported startups in developing and implementing ML proof-of-concepts across various domains.
• Conducted hands-on tutorials and hosted weekly office hours to provide technical guidance.

Machine Learning Engineer Technical Advisor at Vector Institude

• Collaborated with business clients to define an LLM use case tailored to meet their business needs.
• Provided support to clients in deploying their LLama 3.1 model on the GCP using Terraform.
• Created tailored presentations to assist clients in understanding and implementing solutions.

Machine Learning Engineer Intern Ubisoft La Forge (Toronto)

• Designing a generative solution for constructing face models, reducing the time required for creating a face model by more than 90%..
• Integrated different generative models (GAN) in the pipeline, including StyleGAN, Real-ESRGAN, and Pix2Pix, implemented in Pytorch
• Executed model training for large-scale datasets on GPU cluster servers.
• Programmed an automated pipeline for artifact removal from a face model, eliminating human intervention and saving over 95% of processing time using Pytorch.
• Provided bi-weekly reports to managers, delivering updates on project progress and key metrics.
• Facilitated knowledge transfer sessions for new interns, imparting essential skills and insights to accelerate their onboarding process.
• Collaborated with a team of esteemed research scientists on multiple projects aimed at publishing papers in prestigious conferences

Research Assistant at BioMotion Lab / Computational Vision and Imaging Lab / Vector Faculty Affiliate Researcher.

• Advised by Prof. Nikolaus Troje & Dr. Marcus A. Brubaker
• Implemented a real-time pipeline for Novel View Synthesis for Telecommunication Systems with generative AI using Pytorch and OpenCV.
• Structured a real-time pipeline capable of swapping faces in a telecommunication system. [Demo]
• Communicated regularly by comprehensively documenting the latest findings (models, paper, algorithm) with supervisors.
• Stayed abreast of the latest advancements in the field by regularly reviewing and incorporating insights from newly published research papers into ongoing projects.

Machine Learning Engineer at HARA AI

• Supervised by Dr. Reshad Hosseini
• Collaborated with a team of Machine Learning Engineers to develop a Traffic violation verification system. [Project Page]
• Developed a deep network model, classifying color and vehicle type with 90.77% accuracy.
• Integrated Pytorch models to OpenCV (C++) to reduce the execution time by 75%.
• Maintained consistent communication with stakeholders through weekly reporting.

Machine Learning Intern at HARA AI

• Advised by Dr. Reshad Hosseini
• Contributed with the NLP research team to develop a speech-to-text (Persian Language) model for a Smart Call Center.
• Processed 5GB of unstructured textual data gathered from scrapping the newspaper website.
• Applied feature extraction techniques, specifically Mel-Frequency Cepstral Coefficients (MFCC) and Mel spectrogram, to analyze audio signals using the Librosa python library.

Developer Intern at TaarLab

• Advised by Dr. Mehdi Tale Masouleh
• Developing an application for controlling robots based on commands from a phone.
• Programming IR-sensor for detecting and measuring the robots movement.
• Improved the position accuracy by using IR sensors instead of motor encoders.

Project Manager

• Managed a team of 11 members from a broad range of disciplinaries.
• Had 2 site trips to the region, in order to fully understand the needs.
• Communicated with the Woburn Community members in weekly meetings to receive their feedback to achieve maximum satisfaction.
• Building two Compost Bins designed in a way that is best suited for the school children in the community.
• Provided Brochures and Education Materials to increase knowledge and awareness about composting.

• Mitacs Accelerate Fellowship Recipient ($30k). [link](2023)

• Awarded $6000 for York Graduate Scholarship (2021)

• Ranked 3^rd out of approximate 110 undergraduate students (Ranked 2nd in Control branch), school of Electrical and Computer Engineering, University of Tehran. (2020)
• Ranked 394^th among more than 156,000 participants in Nationwide Universities Entrance Exam (B.Sc.). (2016)
• Ranked 23^th in Sharif National Student Competition. (2015)
• Ranked 3^rd in the country at the second stage of Paya Scientific League in physics. (2015)

• TensorFlow Developer Professional Certificate (4 Courses)(link)
• Generative Adversarial Networks (GANs) Specialization (3 Courses)(link)
• Generative AI with Large Language Models(link)

• Google Data Analytics Professional Certificate (8 Courses) (link)

• Uplimit Building AI Products with OpenAI (link)

• Fundamentals of Accelerated Computing with CUDA Python (link)

• Data Visualization (link)

• Enterprise Design Thinking (link)

• Python, Matlab, C/C++.

• Pytorch, Keras, NumPy, scikit-learn, SciPy, Pandas.

• Microsoft Word, Microsoft Excel, Microsoft Powerpoint, LaTeX.

• BigQuery (SQL), HTML/CSS.

Master of Ceremonies (MC) for Toronto Machine Learning Society (TMLS)

• Master of Ceremonies at Toronto Machine Learning Summit, facilitating and introducing five talks, fostering an interactive learning environment and ensuring smooth event execution.

Master of Ceremonies (MC) for Toronto Machine Learning Society (TMLS)

• Master of Ceremonies at Toronto Machine Learning Summit, facilitating and introducing five talks, fostering an interactive learning environment and ensuring smooth event execution.

Executive Member of EECS Graduate Student Association

• Holding events and social gatherings.
• Presenting Seminars and talk.

Teacher for a Non Profit Organization

• Taught Physics for 3 hours per week in each class.
• Managed 4 different classes, each class was holding 20-30 students.
• Maintained a disciplined, productive environment in the classroom to ensure everyone learned.
• Guided them on how to manage their time to get results efficiently.