Chloe So

• Analyse and evaluate alternative data sources for KPI-tracking of publicly traded companies • Research improvements to feature engineering and modelling processes • Scrape data from novel low-cost sources

• Contributed to Mindit, a mine water modelling application integrating temporal system networks and scenario-based simulations for traceable, collaborative planning • Established analysis workflows over Monte Carlo simulation outputs for model validation, scenario-level metric computation and system configuration benchmarking • Built data ingestion pipelines into a lakehouse architecture, served through an API bridge that orchestrates UI requests and backend operations

• Developed methodologies for implementing localised data cues in a prototype data sonification product

• Applied clustering to energy sensor time-series data for room-type classification, assessing the impact of transformation choices such as dynamic time warping

• Worked in a multidisciplinary team on a short consulting-style engagement to create a viable business plan for Wood to Work, a supported employment programme

• Completed a six-weekend workshop series on advanced machine learning methodologies

• Provided academic and pastoral support to members of the Junior Common Room

• Supervisor: Prof Axel Kuhn • Thesis title (provisional): Fabrication and characterisation of a high-finesse optical microcavity for quantum interfacing

• Supervisor: Prof C Stuart Adams • Thesis title: Zeeman-tunable modulation transfer spectroscopy

• Supervisor: Dr David Carty • Dissertation title: Quantum simulation of many-body physics with ultracold polar molecules in optical lattices

• Supervisor: Prof Kin Shing Chan • Project title: Water-driven dehalogenation for synthesis and remediation