Baris Coskunuzer

Baris Coskunuzer

Professor - Mathematical Sciences
FA 2.410
Personal webpage
Tags: Topological Data Analysis Geometric Topology

Professional Preparation

PhD - Math
Princeton University - 2004

Research Areas

Geometric Topology
Topological Data Analysis
Machine Learning


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

News Articles

Math Approach May Make Drug Discovery More Effective, Efficient
Computer Aided Drug Discovery 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.