About Me

I am a Research Scientist at Meta Reality Labs, where I develop and integrate state-of-the-art machine learning methods with wearable devices to interpret electromyography (EMG) signals. This work drives the creation of next-generation interfaces that bridge the gap between humans and digital technologies.

I earned my Ph.D. in Electrical and Computer Engineering, from the University of Texas at Austin, where I had the privilege to be advised by Prof. Aryan Mokhtari. Before that, I completed my undergraduate studies in the Department of Informatics and Telecommunications in Greece and obtained an MSc in Logic, Algorithms and Theory of Computation from the Department of Mathematics at the National and Kapodistrian University of Athens, under the supervision of Prof. Dimitris Fotakis.

I worked as an Applied Scientist Intern in the Alexa group at Amazon, focusing on scalable, semi-asynchronous federated learning algorithms to address challenges of system and data heterogeneity in distributed machine learning.

My research interests center on the theory and applications of optimization in large-scale machine learning problems. Specifically, I focus on various aspects of federated learning and decentralized optimization. Additionally, I am deeply interested in adaptive optimization, with my recent work aiming to bridge the gap between stochastic gradient descent (SGD) and adaptive methods across a broad range of regimes.