PhD - Math
Princeton University - 2004

ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery 2022 - Other

TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting 2022 - Conference Paper

Minimal Surfaces in Hyperbolic 3‐Manifolds 2021 - Journal Article

Topological Relational Learning on Graphs 2021 - Conference Paper

Minimal surfaces in ℍ2 × ℝ: Non-fillable curves 2021 - Journal Article

Embedded $H$-planes in hyperbolic $3$-space 2018 - Journal Article

Asymptotic plateau problem in $${\mathbb H}^2\times {\mathbb R}$$ H 2 × R 2018 - Journal Article

Non-properly embedded H-planes in $${\mathbb H}^2\times {\mathbb R}$$ H 2 × R 2018 - Journal Article

Distribution Network Resilience Enhancement with Topological Neural Networks

2022/12–2025/12 NSF-DMS-AMPS Research Grant (co-PI Jie Zhang)

Minimal Surfaces in Hyperbolic 3-Manifolds

2022/08–2025/07 NSF-DMS Geometric Analysis Research Grant

Innovative geometric deep learning models for onboard detection of anomalous events

2022/08–2024/02 NASA AIST Grant (co-I) (PIs: Y. Gel, Kyo Lee)

Minimal Surfaces in 3-manifolds

2018/08–2023/07 Simons Collaboration Grant

Math Approach May Make Drug Discovery More Effective, Efficient

Dr. Baris Coskunuzer, professor of mathematical sciences at UT Dallas, and his colleagues developed an approach based on topological data analysis to screen thousands of possible drug candidates virtually and narrow the compound candidates considerably to those that are most fit for laboratory and clinical testing.