Tristan Hodgson
Third year Oxford maths undergraduate, primarily interested in numerical analysis and numerical linear algebra.
Technical Projects
Performance Modelling of In-Database Sparse Matrix Multiplication
- Modelled performance trade-offs between in-database and client-side matrix multiplication under compute, sparsity, and bandwidth constraints
- Benchmarked performance to validate asymptotic runtime predictions across matrices of varying size and sparsity
- Derived and validated the sparsity threshold function where in-database outperforms client-side computation to inform system architecture decisions
Known Prefix Neural Cryptanalysis with seq2seq Models
- Implemented LSTM seq2seq models in PyTorch to perform neural cryptanalysis of Caesar and substitution ciphers on natural-language sequences
- Extended prior neural cryptanalysis work by introducing a known prefix, reducing character-level errors by 41%
- Benchmarked against a random baseline to validate that the model learned decryption structure
Real Estate Market Dashboard
- Constructed a data pipeline to ingest government statistics, transforming transaction data into time-series data
- Segmented the housing market using PCA and K-Means, revealing regional and socio-economic divides without relying on location-based data
- Visualized complex datasets, using interactive maps and graphs to enable exploratory analysis of price and returns
Presentation on Algorithmic Information Theory, Kolmogorov Complexity
- Independently studied literature on Kolmogorov complexity and compression-based similarity measures
- Implemented a simple illustrative example (Normalized Compression Distance) to support explanation
- Presented core theory, motivation, and limitations to a mixed undergraduate-faculty audience