Summary
Jahandar Jahanipour is a Senior Solutions Architect at NVIDIA with nine years of experience designing and deploying AI-driven solutions across healthcare and biomedical imaging domains. He holds a PhD in Electrical and Electronics Engineering and has a strong track record building and optimizing deep learning models for segmentation, detection, and generative tasks at institutions like Mayo Clinic and the NIH. Jahandar combines research rigor with production know-how—deploying models on GCP with containerization and accelerating inference for edge devices. He is an active AI practitioner and contributor to educational ML tooling, authoring TensorFlow tutorial notebooks and CNN/autoencoder examples to lower the barrier to entry for practitioners. Skilled in LLMs (RAG, PEFT/LoRA, prompt engineering) and GenAI (GANs, VAEs, diffusion), he adapts foundation models to domain-specific needs and large-scale datasets. Based in the United States, he blends deep technical expertise with practical deployment experience to move cutting-edge models from prototype to production.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (PhD) Electrical and Electronics Engineering, Doctor of Philosophy (PhD) Electrical and Electronics Engineering at University of Houston
Amirkabir University of Technology
Master of Science (M.Sc.) Electrical, Master of Science (M.Sc.) Electrical at Isfahan University of Technology
English, Persian