Dr Yongchao Huang
Math (algebra and optimisation)
Stats (structured and data-driven)
Programming (agile software development)
I am a postdoc researcher in Computer Science at University of Oxford, working in the control & verification, computational biology and research software groups, on projects of learning smart building dynamics (e.g. GP, RL), Bayesian inference of ode systems, and MCMC numerical methods, considering data heterogeneity, uncertainty and sequential (e.g. temporal) nature. Intrinsically, I am curious about some fundamental aspects of science and logics, namely algebra, optimisation, probabilistic modelling, etc. My interests lie in maths and its applied spaces (e.g. numerical, signal processing, learning, control, etc) -- conceiving myself as a bit old school than being fascinated by the prevalents. While gradiently walking towards a theorist and generalist, I am keen to answer real world questions via evidence-based, agile, and ideally creative routines, typical fields include those concerning humans wellbeing and social good such as engineering (materials, structures), climate, energy, and data science related subjects, where, hopefully, computers could be automated to aid decision-making, boost efficiency and/or accuracy.
I did my DPhil in the Engineering Science department at University of Oxford and spent some 2.5 years in UK financial industry solving practical data science puzzles end-to-end before returning to academia in mid 2019.
Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI−NIDS
C Schroeder de Witt; Y Huang; P H.S. Torr; M Strohmeier
A Sequential Modelling Approach for Indoor Temperature Prediction and Heating Control in Smart Buildings
Y Huang; H Miles; P Zhang
In workshop on ML4Eng‚ NIPS. 2020.
Sensor Selection and Random Field Reconstruction for Robust and Cost−effective Heterogeneous Weather Sensor Networks for the Developing World
P Zhang; I Nevat; G Peters; W Fruehwirt; Y Huang; I Anders; M Osborne
In workshop on ML4D‚ NIPS. 2017.