Sepehr Eslami Moghadam
Persian with proud, and a self-taught maker who builds and breaks boundaries in computer science, with the spirit of an experimental engineer who is passionate about the practical side of bringing AI to the real world. From theory to deployment. Currently obsessed with deep neural networks, medical computer vision, and machine learning reinforcement systems.
Achievements
See all →3rd Place Laureate & Scholarship - RIT Dubai AI Competition
Awarded a 10,000 AED academic scholarship at the 14th Annual Engineering Competition organized by RIT Dubai. Served as the sole technical architect and developer behind the AI-driven task prioritization system.
Future Catalyst Award 2024 - STEM Best Practice Innovation Exhibition
Automating gastrointestinal tract segmentation in MRI scans to reduce radiation therapy planning time from over an hour to just 15 minutes.
Top Robotics Researcher - Mashhad Research Center
Awarded 1st place robotics researcher and invented an active Smart Mask featured on IRIB National TV and presented directly to the Iranian Minister of Education during the COVID-19 pandemic.
Projects
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Breast Cancer : Multi-Modal Fusion Dataset
A comprehensive data curation project addressing the fragmentation of the TCGA-BRCA program. This dataset provides a strictly patient-aligned fusion of radiology (MRI), computational pathology (WSI patches), RNA-seq, Copy Number Variations (CNV), somatic mutations, and longitudinal clinical records for breast cancer research.
OncoGemma: Multi-Modal Oncology Agent
An autonomous virtual tumor board — fine-tuned MedGemma-4B with multi-modal fusion of MRI, whole slide images, and genomic profiles, featuring a dual-agent zero-hallucination inference engine for precision breast cancer treatment planning.
Medical Image Segmentation: Brain Tumor
A systematic deep learning benchmark for automated brain tumor segmentation on BraTS20 MRI scans — comparing custom U-Net, pretrained encoder U-Nets, U-Net++, DeepLabV3+, and TransUNet across multiple loss functions and hyperparameter configurations.