Rui Wang
Simons Center Postdoctoral Fellow @ NYU
Office: Silver Building 1022I, 24 Waverly Place, New York, 10003
Contact: rw3594[at]nyu[dot]edu or wang.rui[at]nyu[dot]edu
I am currently a Postdoctoral Fellow at Simons Center for Computational Physical Chemistry (SCCPC) at New York University. Prior to this, I was a Visiting Assistant Professor in the Department of Mathematics at Michigan State University, working with Prof. Guowei Wei. I hold a Bachelor’s Degree from Xi’an Jiaotong University in Mathematics and Applied Mathematics, and an Applied Mathematics Ph.D. from Michigan State University.
My research focuses on developing innovative mathematical methods, particularly in topological and geometric data analysis (TDA/GDA), to understand various biological processes. Combined with machine learning (ML) models, this understanding enables rapid, data-driven responses to emerging diseases by providing predictive insights for identifying effective therapeutic candidates in early-stage drug discovery. My interests include computational topology and graphs, mathematical modeling of infectious diseases, mathematical virology, RNA motif design, protein-peptide docking prediction, and genomics analysis.
Research Interests
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Mathematics-aided Artificial Intelligence and Data Science
- Applied Topology and Topological Spectral Theory: Persistent Spectral Graph; Persistent Path Laplacian
- Artificial Intelligence: Topological Deep Learning; AutoEncoder; UMAP-assisted K-Means Clustering
- Data Science: Topological Data Analysis; Dimensionality Reduction
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Mathematical Modeling of Biosciences
- Biomolecules: Persistent Topological Laplacians of Biomolecules; Curvature-based Biomolecular Surfaces; Graph Theory-based Flexibility-Rigidity Index (FRI) for Proteins; Stochastic Prediction of Protein B-factor
- Bio-Complexes: Algebraic Topology-based Protein-Ligand/Protein Binding Free Energy (BFE) Prediction
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Artificial Intelligence for Life Science (AI4LifeScience)
- Infectious Disease: Early Prediction of Infectivity-enhanced and Vaccine-escaped Mutations
- RNA Motify Design: Clustering-based Top RNA-like Structure Prediction and Design
- Protein-peptide Docking: Enhancing Protein-peptide Complex Prediction by Topological Deep Learning Model
- Drug Discovery: Generative AI in Drug Design for Cocaine Addiction and Opioid Dependence
- Biomedical Imaging: Quantification of Transplanted Cell in Vivo Imaging Aided by CNN and U-NET
News
| 10/23/2024 | Organized a mini-symposium at 2024 SIAM Conference on Mathematics of Data Science (MDS24) |
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| 04/26/2024 | Attended NYC Metro Area Conference AI Meets Science (AIMS) @ New York University |
| 03/01/2024 | Attended New York Meetup of the Learning on Graphs Conference (LoG) |
| 12/18/2023 | Joined Simons Center for Computational Physical Chemistry (SCCPC) @ New York University as an Independent Postdoctoral Fellow |
| 10/23/2022 | Attended Women in Scientific Computing on Complex Physical and Biological System @ University of Florida |
| 09/24/2022 | Organized a mini-symposium at 2022 SIAM Great Lakes Section Annual Meeting (GLSIAM) |
| 07/07/2022 | Defended my Ph.D. Thesis |