EMAD (NEMATOLLAH) SAEIDI

Content-based Medical Image Retrieval Using Graph Neural Networks Graph neural networks, Foundation models, Histopathology image analysis, Generative models

Collaborated with cross-functional teams to troubleshoot and optimize the performance of 10+ deployed Al services Designed and executed performance evaluations to assess model accuracy, speed, and reliability Drafted RFPs and developed business plans to support initiatives within the AI open innovation ecosystem Authored technical articles and research briefs for the FANAP Research Team, promoting knowledge sharing and innovation

Medical image analysis and the implementation of a medical image search engine Medical image retrieval, image classification, medical images, attention-based adversarial variational graph autoencoder, pre-trained models, approximate nearest neighbors search algorithm Contour Drawing for a Robot Motion Planning System Contour drawing using image processing techniques to apply in a drawing robot Implemented an object detection app with REST API Object detection and segmentation frameworks, few-shot models, transfer learning Automatic Number Plate Recognition System Vehicle registration, vehicle data search, and display of top records based on license plates Implemented a video surveillance-based attendance and registration app with REST API Implemented a visual search app with REST API Object detection and recognition, color extraction, image web crawler, transfer learning, approximate nearest neighbor search Implemented a value creation and a clustering library SaaS Metrics and KPIs, customer analysis and segmentation, cluster ensembles, numeric and categorical clustering for the grocery retail industry Worked on clustering and extracting customer behavior patterns Credit card transactions for fraud detection (money laundering, tax evasion) Implemented a recommendation system Developed a sequence-to-sequence model for ranking Developed association rules, hybrid, content, and collaborative filtering, clustering customers, as well as feature engineering for candidate generation Worked on marketing Analysis and product prediction Provided strategic direction to the company on different datasets (using CatBoost, XGBoost, lightGBM, ensemble methods, MLP) Worked in an agile environment With daily standups, sprint retrospectives, backlog groomings, and continuous integrations built within two-week sprints

Thesis: Content-based Medical Image Retrieval Using Graph Neural Networks

Thesis: Learning Multi-Objective Binary Features for Image Representation and Recognition

Thesis: Intelligent Agent-based Social Simulation Model using Reinforcement Learning