Summary
Peter E is a PhD candidate in Neural Information Processing at the University of Tübingen with 11 years of engineering experience bridging computational neuroscience and production-grade backend systems. He designs state-of-the-art Transformer-based video saliency models that substantially improve explainable information gain for temporal modules while experimentally probing predictive processing hypotheses. Previously he served as a backend architect and DevOps engineer, shipping infrastructure-as-code, containerized microservices, CI/CD pipelines and Lambda-based Alexa skills, and even implemented a Go reverse-proxy for Bitbucket-to-Jenkins integration. Comfortable across Python, Go, C++, Java and Objective-C, he brings together deep learning, computer vision and robust engineering practices to move research models toward reproducible, deployable systems. Based in Tübingen, he combines rigorous academic training from IMPRS and Concordia with practical production experience, making him fluent at turning neuroscience insights into scalable software.
11 years of coding experience
1 year of employment as a software developer
French Baccalaureate, French Baccalaureate at Lycee Franco Libanais
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Concordia University
Master of Science - MS, Neural Information Processing, Master of Science - MS, Neural Information Processing at International Max Planck Research School for Cognitive and Systems Neuroscience
Bachelor of Science (BS), Computer Science, Bachelor of Science (BS), Computer Science at Lebanese American University
Arabic, English, French