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PhD Candidate at EPFL @lpdi-epfl
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EPFL
Data Scientist
June 29, 2026 – Present
TianZhuAI4S.github.io
August 15, 2025 – Present
TianZhuAI4S.github.io — GitHub repository
View ProjectGGFlow
August 12, 2025 – August 12, 2025
GGFlow: A Graph Flow Matching Method with Efficient Optimal Transport (TMLR 2025)
View ProjectAbX
September 23, 2024 – June 30, 2025
Official open-source of Antibody Design Using a Score-based Diffusion Model Guided by Evolutionary, Physical, and Geometric Constraints
View Projectimmunefold
September 9, 2024 – March 19, 2025
Official open-source of Accurate structure prediction of immune proteins using parameter-efficient transfer learning
View ProjectDiffAffinity
August 7, 2023 – December 11, 2023
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model (NeurIPS 2023 Poster)
View ProjectCultural Fit Analysis
The candidate's projects are heavily focused on academic research and open-source contributions in specialized scientific domains (e.g., protein design, immunology). While demonstrating strong technical depth, the diversity of project types and exposure to broader industry applications is limited. The single listed professional experience as a Data Scientist at EPFL aligns with a research-oriented environment. This profile suggests a strong fit for roles requiring deep research and development in specific AI/ML areas, but potentially less exposure to diverse business contexts or cross-functional team dynamics typical in broader industry settings.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are technical but do not provide insight into collaboration, problem-solving approaches, or communication style.