Welcome to the DeLTA Lab“DeLTA”: Designing Deep Learning in Principle: From Theory to Applications
PI: Wuyang Chen, Assistant Professor (wuyang at sfu dot ca) The School of Computing Science, Simon Fraser University Research Overview1. We make scientific machine learning (SciML) useful in practice. For example, we develop neural operators (1) for 3D reconstruction of real-world fluids (2). 2. We develop principled deep learning methods (3, 4, 5, 6) inspired by deep learning theory. 3. We are broadly interested in LLM (7, 8, 9), computer vision (10, 11), model efficiency (12, 13), self-supervised learning (14, 15), automated machine learning (AutoML) (16), etc. We actively look for self-motivated and proactive students to join us. You are welcome to email the PI (Wuyang Chen) with your resume and a short description of your research plans/interests. For Ph.D. applicants, please apply to the CS @ SFU and mention the PI's name (Wuyang Chen) in your application. News[12/2025]
[11/2024]
[10/2024] Invited talk at Challenges & opportunities in Foundation Models: accelerating scientific discovery, explainability, efficiency and security, University of Geneva [9/2024] 1 paper accepted in NeurIPS’2024 [7/2024] Our NeurIPS 2024 workshop proposal, “Foundation Models for Science: Progress, Opportunities, and Challenges,” is accepted. Please consider submitting your great work to our workshop (OpenReview)! [6/2024]
[5/2024] Dr. Chen is grateful to receive the Google GCP Credit Award (Gemma Academic Program) [4/2024]
[3/2024]
[2/2024] 1 paper accepted in CVPR’2024 [1/2024] 2 papers accepted in ICLR’2024 |