Anastasios Kyrillidis
OptimaLab · Rice University · Est. 2018
Active
|
Alumni
Postdoctoral Researcher PostDoc
Jianqiang Li
PostDoc
Quantum computing and algorithms.
Co-advised with Tirthak Patel and Nai-Hui Chia
PhD Students PhD
PhD · Since 2021
Provable optimization methods in nonconvex objectives (neural networks).
PhD · Since 2022
Adversarial training, theory of non-convex smooth games, Byzantine attacks.
PhD · Since 2022
Quantum process tomography, distributed estimation of excited quantum states, variational methods.
PhD · Since 2024
Sequential learning, parameter efficient fine-tuning methods.
PhD · Since 2024
Quantum algorithms and optimization, theoretical computer science.
MSc Students MSc
Hamza Shili
MSc
Mixture of Experts systems.
Michael Menezes
MSc (previously undergraduate)
Pruning methods in AI, transfer learning, distributed optimization and learning.
Undergraduate Students Undergrad
Barbara Su
Undergraduate
Pruning methods in AI, distributed methods in learning, recursive neural network architectures for AI reasoning.
Xinze Fang
Undergraduate
Pruning methods in AI, distributed methods in learning.
Jack Shen
Undergraduate
Recursive neural network architectures for AI reasoning.
Aayan Ilyas
Undergraduate
Classical algorithms benchmarking against quantum algorithms for MIS instances.
Oneal Wang
Undergraduate
Classical algorithms benchmarking against quantum algorithms for MIS instances.
2025
PhD · 2021 – 2025
ML-based approach to protein structure determination and partial template completion.
Co-advised with George Phillips (Biosciences)
PhD · 2019 – 2025
From discrete to continuous methods for SAT.
Co-advised with Moshe Vardi
First position: JP Morgan · Now: Applied Scientist, Amazon
2024
PhD · 2019 – 2024
Quantum state tomography, game-theoretic optimization, acceleration, optimization in quantum computing.
First position: Quantum Computing Research Scientist, JPMorganChase
PhD · 2019 – 2024
Robustness in optimization for robotics.
Co-advised with Lydia Kavraki
First position: Research Scientist, Bookout Center (Houston)
2023
PhD · 2019 – 2023
Distributed learning of neural networks, federated learning, mixture of experts.
First position: Bytedance
PhD · 2020 – 2023
Theories and perspectives on practical deep learning.
First position: Director of AI, ReBuy · Now: Netflix
2021
MSc · 2019 – 2021
Efficient distributed techniques on lottery ticket hypothesis for neural networks.
First position: Microsoft