CV
CV of Mohammad Asadi, PhD student in Electrical Engineering at Stanford University: education, experience, awards, fellowships, and patents.
Education
- PhD, Electrical Engineering, Stanford University (2023-present) Ashley Lab and STAI Lab. Advised by Prof. Euan Ashley; co-advised by Prof. Fei-Fei Li and Prof. Ehsan Adeli.
- MS, Electrical Engineering, Stanford University (2023-2025)
- BSc, Electrical Engineering, Sharif University of Technology (2018-2023) GPA 4.0/4.0; ranked 2nd among 175 students.
Experience
- Research Assistant, Stanford University (Sep 2024 - present). Ashley Lab and STAI Lab.
- AI Research Intern, Samsung Semiconductor (Jun - Sep 2024). Multimedia Team.
- Research Assistant, Stanford University (Sep - Dec 2023). Computational Imaging Lab, with Prof. Gordon Wetzstein.
- Research Intern, EPFL (Jun - Oct 2022). ML4ED Lab, with Prof. Tanja Käser and Prof. Mirko Marras.
- Research Intern, EPFL (Dec 2021 - May 2022). VITA Lab, with Prof. Alexandre Alahi.
Awards & Fellowships
- Amazon AI PhD Fellowship, AY 2025-26 and AY 2026-27. One of 10 Stanford students selected for the inaugural cohort; listed at Stanford Data Science.
- Stanford HAI Graduate Fellowship, 2025-26. Stanford Institute for Human-Centered AI.
- 1st Place, “Smartest AI Agent” Prize, TreeHacks 2024 (project: Healthiator).
- Qualcomm Distinguished Poster Award, Stanford SCIEN Affiliates Conference, 2023.
- Summer@EPFL, 2022. Selected in the top 2% of more than 4,500 applicants.
- Highest Award of Academic Achievement, Department of Electrical Engineering, Sharif University of Technology, 2019-2020.
Service
- Peer review. Reviewer for MICCAI, Medical Image Analysis, and IEEE Transactions on Medical Imaging.
- Speaker, Stanford AI4ALL, 2026.
- Poster Session Committee, Market Design in the Age of AI, Stanford University, 2026.
- Head Teaching Assistant, Foundations of Data Science, Sharif University of Technology.
Patents
- System and Method for End-to-End Pipeline for Photo-Realistic 3D Motion Generation. U.S. Patent Application US20260080600A1 (Samsung Electronics).
- MARCUS: An Agentic, Multimodal Vision-Language Model for Cardiac Diagnosis and Management. U.S. patent application, in preparation.
Datasets
- EchoGraph-annotated ECHO-NOTE2NUM examples (v1.0.0, 2025). PhysioNet, DOI 10.13026/hb5q-9532.
Selected Publications
This is a selected list. See the publications page for the complete list.
- Align-RAG: Alignment Is All You Need for TSFM In-Context Learning, first author, 2026. Collaboration with Amazon. arXiv · Code
- MIRAGE: The Illusion of Visual Understanding, first author, 2026. arXiv · Stanford GSB working paper
- MARCUS: An Agentic, Multimodal Vision-Language Model for Cardiac Diagnosis and Management, co-first author (equal contribution), 2026. arXiv
- Deterministic Hallucination Detection in Medical VQA via Confidence-Evidence Bayesian Gain, first author. Accepted to MICCAI 2026. arXiv