At Enablers, in my role as a Machine Learning Engineer Intern, I am at the forefront of harnessing the power of AI, focusing on enhancing the performance and efficiency of YOLO architecture models. My journey here has been marked by significant contributions and continuous learning:- **Pioneering a Closed-Loop Training Pipeline:** I have developed an innovative closed-loop training system for YOLO architecture models. This initiative has notably improved model accuracy and automation by integrating continuous feedback into our training processes, creating a dynamic and responsive development environment for our machine learning endeavours.- **Optimizing ML Models for Edge Computing:** A key project has been optimizing machine learning models for deployment on NVIDIA Jetson devices using ONNX Runtime. This work has been essential in enhancing runtime performance and ensuring efficient resource utilization, significantly reducing inference times from 1000ms to 600ms, which is crucial for our applications in edge computing environments.- **Advancing Data Engineering and Visualization Efforts:** I am actively involved in engineering optimized data tables and crafting insightful visualizations. These efforts serve to elevate our data interpretability, leading to more informed decision-making and enhancing our data-driven strategy.My tenure at Enablers is characterized by a profound commitment to leveraging AI for solving real-world challenges, underscored by a passion for continual growth and innovation within the field of machine learning.**Key Skills and Technologies:**- AI and Machine Learning Development- YOLO Architecture Models- Deployment on NVIDIA Jetson Devices- ONNX Runtime Optimization- Data Engineering and Visualization- Proficiencies in Python, PyTorch

Working as a master's thesis student for the Department of Safety Vehicle Automation (SVA), I worked on developing an automatic fault detection solution based on a hybrid Autoencoder/CNN architecture. I undertook the following task in duration of project : - Performing Exploratory Data Analysis by utilizing dimensionality reduction techniques such as PCA, t-SNE and UMAP.- Proposing machine learning solutions based on state-of-the-art research and the goals of the stakeholders.-Constructing multiple test scenarios to test different capabilities of the proposed method.Our proposed solution had 94% accuracy on the fault detection task and 100% accuracy on the fault diagnosis task.

Contributed to development efforts in a high-impact SaaS project, focusing on modernizing both frontend and backend systems:- Spearheaded the development of a new, responsive frontend using React.js, significantly enhancing user experience and system performance.- Engineered a robust authentication service leveraging FastAPI, improving security protocols and streamlining user access.- Collaborated in an agile environment, participating in two-week sprints and utilizing Jira for efficient project management and tracking.- Created compelling data visualizations using Kibana, translating complex usage logs into actionable insights that demonstrated clear adoption trends of the new service.- Contributed to the project's success, which gained significant traction with management, resulting in securing additional support for further development and expansion.This experience showcased my ability to drive full-stack development in a SaaS environment, effectively collaborate in agile teams, and deliver measurable results that align with business objectives.

As a student worker, I was part of a team that developed an automated segmentation model to augment the company's software. We used CT images In this project, I performed the following as part of the team:- I was part of the team tasked with the development of a Fully convolutional network for automatic vertebrae segmentation. We developed a solution by creating a pipeline that connects 3 U-Net models. - I took part in the integration step of the created pipeline with the native software ensuring that reformatting of the images from DICOM to NIFTY and vice versa did not cause data corruption.- Created analytic test scenarios to check the performance of the developed pipeline to check fringe cases and ensure data safety.

As a research assistant, I was part of several scientific projects in neuroscience where I: - Worked with neuroscience PhD students to design clinical trials using the psychopy package. - Our team participated in Iran's National Brain Mapping Lab contest to predict what image the patient had recognised based on the EEG metrics collected during the trial. Our team's LSTM model achieved third place in the competition.-Performed methodical paper review.

Co-founded the first data science digital academy in Iran. As the chief operating officer, I had 3 objectives in mind: 1- Negotiate terms with venues that host our monthly events to get favourable prices. 2- Arrange logistics ranging from infrastructure for digital assets to procurement of necessary goods for each event. 3- Predict the requirements of the organisation in terms of resources.Through the efforts of our team, we achieved several milestones such as :- Our startup was selected as the top idea in Samsung-AUT's 10th acceleration cycle. - We partnered with famous educational and industrial organisations within Iran, such as Snapp, Digikala, Kharazmi University and Shahid Beheshti University.

As a Fullstack developer, I worked with the company's tech lead to create a comprehensive webpage for the E-learning platform to replace the WordPress website that was used before. With this goal and wanting to maximize our search engine visibility, I performed the following tasks:- Used Nuxtjs for development of frontend which also allowed server-side rendering that helped with website SEO.- Used Apolo client to communicate with GraphQL-based backend.

As a react native developer, I was responsible for the creation of a shipment tracking application. In this role, I performed the following:- created a react-native application with redux as a state manager.- Completed the project and exceeded the expectations which resulted in receiving a letter of excellence from the management.

I was part of a team that created a RESTful API middleware based on Nodejs's express framework to communicate with web services and a newly created application. In this role, I performed the following: - Created the API endpoints required for communication with the application. - Created an online payment endpoint connected to the bank payment service.

Worked on a GPS Application designed to communicate with GPS devices installed on cars the product was fully developed and was introduced on the 12th of March 2018.