Building intelligent systems and data-driven solutions with modern technology
I'm a mathematician and researcher with expertise spanning pure mathematics, computer science, and quantitative finance. As Professor of Mathematics at Temple University and former Regius Professor at the University of St. Andrews, I bridge theoretical rigor with practical applications in technology and finance.
My academic work focuses on geometry, topology, and discrete mathematics, with highly cited research (3,300+ citations) including characterizing hyperbolic 3-dimensional polyhedra and advances in 3-manifold topology. I've held positions at prestigious institutions including the Institute for Advanced Study, Caltech, and Institut des Hautes Études Scientifiques.
In industry, I've served as Director of Advanced Development at Wolfram Research, developing the Mathematica kernel's compute and graphics engines, and as Chief Research Officer at Cryptos Fund. I co-created the Cryptocurrencies Index 30 (CCi30) and apply mathematical expertise to quantitative finance and algorithmic trading.
My current projects combine mathematical rigor with modern technology, from real-time sentiment analysis platforms to advanced dimension reduction algorithms. I'm passionate about translating complex mathematical concepts into practical tools that solve real-world problems.
GitHub template that creates Python packages which maintain themselves. Monthly CI workflow tests with latest dependencies, and when tests fail, Claude AI automatically diagnoses and fixes compatibility issues, then creates a PR. No more bitrot - your packages essentially maintain themselves for pennies per year. A "Djinn" that fixes your code while you sleep.
Revolutionary platform for human-AI design collaboration featuring reference image intelligence, auto-refinement with multimodal verification, and multi-provider ecosystem (OmniGen, FLUX, OpenAI, Stability AI). Proprietary verification engine ensures quality through iterative improvement and provides comprehensive analytics for continuous learning. Perfect for research, commercial applications, and technology licensing.
Revolutionary AI-powered system that automatically audits mathematical proofs in arXiv papers. Analyzed over 31,000 papers from math.DS and math.GT categories, identifying ~380 papers with critical errors or counterexamples. Features advanced search by author, verdict, journal tier, and provides detailed AI analysis with referee-style recommendations. 70% of wrong papers contain explicit counterexamples to their main claims.
Real-time sentiment analysis platform for stocks and politics. Features AI-powered sentiment scoring, interactive visualizations with EMA smoothing, and smart data downsampling for optimal performance. Built with modern web technologies and deployed on scalable cloud infrastructure.
Advanced dimension reduction software suite that improves upon UMAP with enhanced performance and accuracy. Provides state-of-the-art algorithms for high-dimensional data visualization and analysis, enabling researchers and data scientists to better understand complex datasets through intelligent dimensionality reduction.
Comprehensive graph embedding software that maps complex network structures into low-dimensional spaces while preserving essential topological properties. Features automated centrality detection to identify key nodes and relationships, making it invaluable for social network analysis, biological networks, and knowledge graphs.
Modernized Python library for solving hard counting problems (#SAT, vertex covers) using tensor network contractions. Originally by Kourtis & Meichanetzidis, we updated it with NetworkX/opt_einsum, added Jones polynomial computation for knot theory, and made it self-maintaining with Claude-powered auto-fixes. Physics meets CS.
Fast Jones polynomial computation and knot identification using tensor networks. Hybrid engine auto-selects between tl-tensor (Rust) for wide braids and classical algorithms for narrow ones. Includes knot database up to 12 crossings, notation converters, and CLI tools. Self-maintaining with Claude-powered auto-fixes.
Interested in collaboration, have a question about my work, or want to discuss opportunities?