Shuo Pang: Homepage

s.(last name)@bristol.ac.uk

Hi, I am a lecturer in computer science at the University of Bristol, UK.

I work in computational complexity and discrete mathematics, broadly on the limits of efficient computation.


My main focus is on proof complexity

... which studies what can/cannot be efficiently proved. Behind an algorithm there are proofs: the 'whys' behind each computation step, if formalized and chained, yield a proof that justifies the output. If moreover the computation is efficient, the proof is expected to be short.

An example question: given a graph \(G\) that is not 3-colourable, how hard is it to prove this fact? Is there always a proof in \(|G|^{10}\) steps in ZFC? Intuition may suggest that there can be some graph which is non-3-colourable but which avoids all 'easy evidences' like containment of 4-cliques, as sparse random graphs do, and for such graphs every proof has to brute force some exponential family of partial colourings*. A rigorous argument, however, remains beyond reach.

  1. *Interestingly, when the random graph is regular with degree ≥ 15, short proof exists in simple semi-algebraic proof systems via the Lovasz-theta function (Atserias–Ochremiak, Banks–Kleinberg–Moore). For sparser models, short proofs are unknown.

A more realistic goal is showing no short proof exists in restricted formal systems. Despite being restricted, many such systems (resolution, Gröbner bases, cutting planes, sum-of-squares, etc.) capture powerful methods in combinatorial optimisation and automated reasoning. Understanding their strength and limitations matters.

The techniques involved have a distinctive flavour, but they are well-connected to several branches in math and TCS. See more