Teaching

Second-year Engineering Science paper covering signals, systems, communications, and information processing.

First-year (Prelims) course, Michaelmas Term. Topics include systems of linear equations, vector spaces, linear maps and matrices, determinants, eigenvalues and diagonalisation, and matrix decompositions (LU, QR, SVD) — foundations used later in machine learning, graphics, and quantum computing.

First-year (Prelims) course, Michaelmas Term. Introduction to functional programming in Haskell, covering strong typing and pattern matching, recursive definitions and structural induction, higher-order list operations (map, filter, fold), lazy evaluation, and reasoning about program correctness.

First-year (Prelims) course, Hilary Term. Algorithm analysis with asymptotic notation; design strategies such as divide-and-conquer; fundamental data structures (arrays, lists, stacks, queues, trees, heaps, graphs); sorting and searching; graph algorithms (BFS, DFS); and introductions to dynamic programming and greedy methods.

Second-year (Part A) course, Hilary Term. Highly efficient algorithms and data structures for fundamental computational problems: amortised analysis, disjoint sets, balanced search trees, network flow, linear programming, NP-hardness, approximation algorithms, and fixed-parameter tractability.