Name:David Nader Palacio

Bio:

Applied Scientist at Microsoft MAIDAP Team. PhD in Computer Science (W&M, US), MS in Computer Engineering (TUM, Germany & UNAL, Colombia), BS in Computer Engineering (UNAL, Colombia). David was part of the SEMERU Research Group under Professor Denys Poshyvanyk. His research focused on interpretable deep learning for code generation, with a particular emphasis on using causal inference to explain software generative models. Professionally, he’s worked on projects involving refactoring automation, traceability link recovery using IR and DL, and security classification with pre-trained models. During internships at Cisco and Microsoft, David explored vector representations for software artifacts and developed interpretability methods for neural code models. He also brings several years of back-end software engineering experience.

Country:United States

Affiliation:Microsoft

Research interests:Deep Learning, Causal Inference, Information Theory