Group

PhD student in Applied Mathematics & Statistics at Johns Hopkins. Research experience spans applied sciences, operations management, business analytics, renewable energy markets, and the pharmaceutical industry. Interested in applying mathematics and programming to real-world challenges in engineering, finance, and healthcare.

PhD student in Applied Mathematics & Statistics at Johns Hopkins. Works on geometry-aware learning for non-Euclidean data, scaling GNNs, and theory for transferability and generalization. Interested in connecting geometric deep learning with transformer/LLM architectures. Previously at University of São Paulo (BSc/MSc), where he received the Itaú Fellowship.

Mathematical researcher and Russian linguist at the Johns Hopkins University Applied Physics Laboratory and PhD student in AMS at JHU (advised by Luana Ruiz). Research interests include graph theory, graph neural networks (GNNs), and advanced cryptographic techniques. BA in Mathematics and Russian from Dartmouth College.

PhD student in Applied Mathematics & Statistics at Johns Hopkins. Interests: random matrices and graph theory, spectral graph theory, and applications to machine learning—especially graph signal processing. Focused on theoretical foundations of graph-based sampling algorithms and stochastic modeling. BS (Mathematics) from The Ohio State University; MS (Computational and Applied Mathematics) from the University of Chicago.