Ifigeneia Apostolopoulou is a Machine Learning PhD student and graduate researcher at Carnegie Mellon University with 11 years of research and teaching experience. She focuses on advancing ML methods through long-term academic work in CMU’s Machine Learning Department and has taught the Advanced Introduction to Machine Learning course. Her background spans international research roles including CERTH and early undergraduate projects, grounded in a B.Sc. in Computer Engineering from the University of Thessaly. Based in Pittsburgh, she combines rigorous theoretical training with hands-on experimentation and open-source engagement visible on her GitHub. Colleagues describe her as a persistent problem-solver who brings classroom clarity to complex research problems while mentoring the next generation of ML practitioners.
11 years of coding experience
High School Diploma, High School Diploma at 1st General Lyceum of Veria
Doctor of Philosophy (PhD), Machine Learning, Doctor of Philosophy (PhD), Machine Learning at Carnegie Mellon University
Bachelor of Science (B.Sc.), Computer Engineering, Computer Science, Bachelor of Science (B.Sc.), Computer Engineering, Computer Science at University of Thessaly
Author's implementation of the paper: "Deep Attentive Variational Inference", ICLR 2022.
Contributions:27 commits, 24 pushes, 1 branch in 1 month
pytorchiclrdeep-learninginferencevariational
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