Yunjoung Cho
EPFL ENAC IA LIPID
LE 1 114 (Bâtiment LE)
Station 18
1015 Lausanne
+41 21 693 02 42
Office: LE 1 114
EPFL › ENAC › IA › LIPID
Website: https://lipid.epfl.ch
+41 21 693 02 42
EPFL › ENAC › ENAC-SAR › SAR-ENS
Education
Ph.D.
| Civil and Environmental Engineering2025 – 2025 EPFL (École polytechnique fédérale de Lausanne)
B.A.
| Cognitive Neuroscience2021 – 2021 Brown University
B.A.
| Urban Studies2021 – 2021 Brown University
B.F.A.
| Interior Architecture2021 – 2021 RISD (Rhode Island School of Design)
Awards
BRIDGE Proof of Concept
Innosuisse & Swiss National Science Foundation
2025
Artist-in-Residence Award for Victor Horta Museum
Reseau Art Nouveau Network
2024
PhD Mobility Award
EDCE
2024
Sasso Art Residency Award
Casa Sasso
2023
SciFilmIt Public Prize
SciFilmIt Geneva
2021
Research
Dynamic Therapeutic Environments
Dynamism in Views-Out
Teaching & PhD
AR-442 Comfort and Architecture
Role: Teaching Assistant (lectures, labs for software, project critique)
Structured course content and semester projects and led lab sessions focused on geometrical modelling and evaluating daylight and thermal performance in built structures using advanced digital software.
AR-464 Daylighting Design Seminar
Role: Co-Instructor (with Prof. M. Andersen, Dr. S. Wasilewski)
Co-designed and taught a seminar for master's students on integratingdaylighting concepts into studio projects and exploring daylight's perceptual qualities in architecture.
MSc Master Thesis Supervision
Discipline: Computer science (30 credits)
Role: Project Supervisor (with Prof. M. Andersen, Prof. J.P. Thiran)
Mentored a master's student in developing machine learning and deep-learning algorithms to analyze and predict visual attention to movement in window using real-time eye-tracking measurements (ETMs).
MsC Master Semester Project Supervision
Discipline: Computer science (12 credits)
Role: Project Supervisor (with Prof. M. Andersen, Prof. P. Fua)
Guided a master's student in designing computer vision algorithms to analyze and quantify temporal changes in brightness and luminosity for sky dynamics.
MSc Master Internship Supervision
Discipline: Computer science
Role: Project Supervisor (with Dr. DH. Kim, Prof. M. Andersen)
Supervised a master's-level researcher developing a novel image processing methodology for analyzing sky dynamics in architectural views, comparing the results to CIE sky classifications and daylighting standards.
MA Master Semester Project Supervision
Discipline: Architecture (4 credits)
Role: Project Supervisor (with Prof. M. Andersen, Dr. S.A. Moreno)
Mentored three master's students in designing and simulating window systems to optimize daylight performance and ensure visual comfort for a new construction project in Lausanne.
CS-433 Machine Learning
Role: Project Supervisor (with Prof. N. Flammarion, Prof. M. Jaggi)
Supervised two teams of master's students in developing machine learning algorithms for view-out impression analysis and high dynamic range (HDR) signal recovery from low-dynamic range (LDR) images.