About

Haotian (Tianyi) MA

Quantitative Researcher | Systems Modelling & Optimisation | Infrastructure & Energy Investments

About Me

I am a doctoral researcher in Systems Modelling and Optimisation at University College London. My work develops integrated modelling toolchains connecting electrochemical system dynamics, infrastructure performance constraints, and stochastic operating environments with decision-relevant sustainability metrics.

By combining physics-based system representation, statistical calibration, and scenario-based optimisation, I construct structured analytical frameworks for evaluating infrastructure transitions under deep uncertainty — spanning 10–20 year planning horizons with Monte Carlo simulation and global sensitivity analysis.

Core Competencies

Quantitative Modelling & Systems Analysis

Python (NumPy, Pandas, SciPy), C++, SQL, Linux; optimisation, system simulation, constraint modelling, reproducible research workflows

Risk, Uncertainty & Scenario Analytics

Monte Carlo, global sensitivity analysis, probabilistic branching, tail-risk quantification, stress testing, portfolio optimisation (convex), equity factor models

Infrastructure & Climate Investment

Multi-scenario DCF modelling, stochastic input simulation, NPV driver attribution, break-even corridor solving, levelised cost decomposition, policy stress modelling

Electrochemical Systems

PEM electrolyzer modelling, multiscale simulation, degradation mapping, lifecycle cost analysis, experimental validation and loss decomposition

Education

Ph.D. in Systems Modelling and Optimisation

University College London | 2023 – 2026

Integrated modelling toolchains for infrastructure transitions under deep uncertainty; Monte Carlo simulation and global sensitivity analysis across 10–20 year planning horizons.

M.Res. in Systems and Control — Distinction

University of Warwick | 2021 – 2023

GPA: 4.0/4.0 | Chancellor's International Award

M.Sc. in Sustainable Energy Engineering

University of Nottingham | 2019 – 2021

B.Eng. in Energy and Power Engineering

Southeast University | 2015 – 2019

Outstanding Graduate (Top 5%)

Professional Experience

Quantitative Researcher — Infrastructure & Energy Investments

Huawei European Research Institute, Munich | May 2023 – May 2025

Developed 20-year DCF valuation models for energy-intensive real assets (Tier III data centre, 12.895 MW baseline IT load). Implemented Monte Carlo frameworks for return distribution and tail exposure analysis. Structured capital allocation across hybrid infrastructure portfolios (PV, storage, hydrogen) under CAPEX-, total-cost-, and emissions-oriented objectives. Achieved 50% CO2 reduction through bounded valuation corridors.

Quantitative Analyst — Early-Stage Energy Infrastructure Screening

Global Energy Interconnection Research Institute, Berlin | Oct 2021 – Apr 2023

Defined techno-economic inflection thresholds for PEM infrastructure during rapid scale-up (CAGR 52%). Built calibrated multiscale modelling architecture (polarisation RMSE < 15 mV, lifetime drift ±3%). Quantified degradation uncertainty into P10/P50/P90 investment ranges via Monte Carlo ensembles (>300 runs per case).