Mohsen Ghafoorian


I am a Senior Staff Machine Learning Research Scientist, technical team lead and manager at Qualcomm AI research, where I focus on developing efficient video diffusion models.
Previously, I led Qualcomm’s Extended Reality team in Amsterdam, developing on-device efficient 3D scene reconstruction and understanding features. From 2017 to 2021, I worked at TomTom as a senior deep leaning R&D engineer, technical team-lead and line-manager, where I developed deep-learning-based methods for generating high-definition maps for autonomous driving.
I earned my Ph.D in machine learning from Radboud University, the Netherlands, focusing on machine learning algorithms for detection and characterization of neuro-degenerative diseases (Oct. 2013 - June 2017). I received my Master's degree in Artifical Intelligence from Sharif University of Technology in 2012, with a thesis on hierarchical reinforcement learning.

Reseach Interests

    • Machine Learning/computer vision
              • Video Diffusion Models
              • 3D Reconstruction
              • 3D Scene Perception
              • Nerfs and Guassian Splatting
              • Reinforcement learning
    • Application areas
              • Augmented/Virtual reality
              • Autonomous driving
              • Medical image analysis


Short Biography

Ph.D. in Machine Learning for Medical Image Analysis at Radboud University, 2013-2017.
M.Sc. in Artificial Intelligence at Computer Engineering Department of Sharif University of Technology, 2010-2012.
B.Sc. in Software Engineering at ECE Department of University of Tehran, 2005-2010.
Born in Tehran, Iran, 1987.
















































News:

• May 2025: I am excited to join Qualcomm AI Research, leading an excellent team on efficient video diffusion models.

• Feb. 2025: Our paper AnyMap is accepted at CVPR25.

• Dec. 2024: I was honored to receive the AIXR award for the XR company of the year on behalf of Qualcomm! An image is available here.

• July 2024: Our paper FastCAD is accepted at ECCV24.

• July 2024: Our paper Interrogate is accepted at BMVC24.

• Dec. 2023: I got promoted to Senior Staff Engineer at Qualcomm.

• July 2023: Two papers (DG-Recon, 3DDistillation ) accepted at ICCV23.

• July 2021: I joined Qualcomm as a staff engineer to work on extended reality.

• May 2021: Our research paper on weakly-supervised semantic segmentation stemming from the AI master's thesis of my former student, Erik Stammes, won the best paper award at ICDIP 2021.

• Dec. 2020: I gave a guest lecture at Dr. Pascal Mettes' "Appliced Machine Learning" course at UvA covering our research on adversarial training methods for map making.

• Sept. 2020: I started as the TomTom-side director and coordinator of the TomTom-UvA Atlas lab, with 5 PhD students doing research on AD-related topics. Prof. Theo Gevers and Prof. Cees Snoek are the lab directors from the UvA side.

• Dec. 2019: I represented TomTom by giving a talk on "AI for Mapmaking: Gambling Nets for Structured Semantic Segmetnation", at NCCV 2019 in Wageningen. A video of part of my presentation is available here.

• July 2019: My former student Laurens Samson successfully defended his AI Master's thesis. The resulting study, "I Bet You Are Wrong: Gambling Adversarial Networks for Structured Semantic Segmentation" was published and presented at ICCV 2019 Computer Vision for Road Scene Understanding and Autonomous Driving at Seoul, South Korea.

• Dec. 2018: I was pleased to give an invited talk on "AI for Map Making" at the Nijmegen Deep Learning Meetup.

• Aug. 2018: our paper titled "EL-GAN: Embedding Loss Driven Generative Adversarial Networks for Lane Detection", was accepted to ECCV 18 Computer Vision for Road Scene Understanding and Autonomous Driving.

• March 8, 2018: I publically defended my Ph.D. thesis entitled: "Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers". See some images here.

• Feb. 2018: Our paper "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR" is presented at SPIE Medical Imaging.

• July 1, 2017: I started as an R&D engineer for autonomous driving at TomTom. Learn more about our team here.

• May 2017: Our paper, "Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation" is accepted at MICCAI 2017.

• From Nov. 2016 to Apr. 2017, I had a six months research visit to the Surgical Planning Laboratory at Harvard Medical School, under the supervision of Prof. William Wells III.