Anastasios Kyrillidis

Overview

Anastasios Kyrillidis (Tasos) is a Noah Harding Associate Professor in the Department of Computer Science at Rice University, part of the George R. Brown School of Engineering. His research focuses on optimization for machine learning, convex/non-convex algorithms, and large-scale systems, with recent ventures into quantum computing and bioinformatics applications. He has held postdoctoral positions at IBM T.J. Watson Research Center and the University of Texas at Austin, following his PhD in Computer Science from EPFL (Switzerland).

Education

• PhD, School of Computer and Communication Sciences, EPFL (2014)
• MSc, Electrical and Electronics Engineering, Technical University of Crete (2010)
• Diploma, Electrical and Electronics Engineering, Technical University of Crete (2008)

Research Interests

His work bridges optimization theory and practical machine learning systems. Key areas include:

• Designing efficient algorithms for high-dimensional problems
• Quantum computing applications in optimization
• Protein structure prediction via 3D Patterson maps (CrysFormer framework)
• Federated learning and distributed systems
• Neural network compression and acceleration

Awards & Funding

Recipient of NSF CAREER Award, Amazon Research Award, and Welch Foundation Grant. His research is supported by NSF, Amazon, Microsoft, and Intel collaborations. Notable recognitions include the Goldstine Fellowship (IBM) and Simons Foundation Postdoctoral Fellowship.

Teaching

Instructs advanced optimization courses (COMP 545, COMP 414) and Algorithmic Thinking (COMP 182). Focuses on connecting theory with real-world machine learning challenges.

Labs & Teams

Leads the OptimaLab at Rice, advancing research in optimization, quantum algorithms, and bioinformatics. Collaborates with interdisciplinary teams on projects like AI-OWLS and CrysFormer protein modeling.