Azade Farshad
Assistant Professor, Aalto University · Principal Investigator, ELLIS Institute Finland
About
I am an Assistant Professor at the Department of Computer Science, Aalto University, and a Principal Investigator at the ELLIS Institute Finland. Before moving to Finland in 2025, I was a postdoctoral research associate at the Technical University of Munich (TUM), where I also completed my PhD summa cum laude in 2023 with a thesis on learning neural representations with limited data and supervision — recognized with the BVM 2025 Best Dissertation Award.
My research develops deep generative models — with a focus on diffusion models and structured representations such as scene graphs — to understand, generate, and manipulate images and videos, with a central goal of bringing these methods into the operating room. I continue to co-advise doctoral researchers at TUM with Prof. Nassir Navab.
Positions
- 2025–nowAssistant Professor, Aalto University, Finland
- 2025–nowPrincipal Investigator, ELLIS Institute Finland
- 2022–2025Postdoctoral Research Associate, TU Munich, Germany
- 2018–2022Research Associate, TU Munich, Germany
Education
- 2018–2023PhD, TU Munich — summa cum laude. Thesis: “Learning to Learn Neural Representations with Limited Data and Supervision”
- 2015–2018MSc in Computer Science, TU Munich
- 2009–2014BSc in Computer Engineering, Amirkabir University of Technology, Iran
Awards
- 2025Best Paper Award, CREATE Workshop @ MICCAI 2025 — MoViS
- 2025Best Dissertation Award, BVM 2025
- 2024Best Paper Award, GRAIL Workshop @ MICCAI 2024 — SANGRIA
- 2024Best Paper Award, EARTH Workshop @ MICCAI 2024 — VISAGE
- 2023Best Paper Award, SG2RL Workshop @ ICCV 2023 — SceneGenie
Service & Community
- 2025Area Chair, MICCAI
- 2023–nowBoard Member, Women in MICCAI
- 2022–nowExecutive Committee Member, British Machine Vision Association (BMVA)
- 2022–nowLead Member, Women in AI and Robotics (WAIR)
- 2023–2026Organizer — MELEX @ ECCV 2026 & ECCV 2024, SG2RL @ ICCV 2023 & CVPR 2024, WiCV @ CVPR 2024
- 2022–2023Executive Assistant Program Chair, IPMI 2023
- 2018–nowReviewer — CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, TMI, MedIA
Teaching
- TUMMachine Learning for Medical Imaging (practical course), Deep Learning for Medical Applications (seminar), Computer-Aided Medical Procedures II, Deep Learning for Human Modelling (practical course), Deep Generative Models