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Jianqiao Mao is a PhD student at University of Birmingham, awarded with studentship from the HDRUK-Alan Turing PhD Programme supported by Wellcome Trust.
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University of Birmingham
Data Scientist
June 29, 2026 – Present
causal-sampler
October 13, 2025 – Present
causal-sampler is a python package that integrates multiple causal sampling techniques, e.g., causal bootstrapping and causally weighted Gaussian Mixture Models, offering standardized pipeline and interfaces.
View Projectmechanism-learn
October 23, 2024 – Present
Mechanism-learn is a simple method to deconfound observational data such that any appropriate machine learning model is forced to learn predictive relationships between effects and their causes, despite the potential presence of multiple unknown and unmeasured confounding. The library is compatible with most existing ML deployments.
View ProjectCausalBootstrapping
November 6, 2023 – Present
CausalBootstrapping is an easy-access implementation and extention of causal bootstrapping (CB) technique for causal analysis. With certain input of observational data, causal graph and variable distributions, CB resamples the data by adjusting the variable distributions which follow intended causal effects.
View ProjectPFFRA
June 17, 2023 – June 6, 2025
An Interpretable Machine Learning technique to analyse the contribution of features in the frequency domain. This method is inspired by permutation feature importance analysis but aims to quantify and analyse the time-series predictive model's mechanism from a global perspective.
View ProjectEnhancedXGBM
March 10, 2023 – March 26, 2023
A enhanced XGBM by considering a loss function with higher order.
View ProjectInterpretable-machine-learning-for-HVAC-predictive-control
January 23, 2023 – August 3, 2024
The open-access code of an interpretable machine learning-based method for room temperature prediction in a non-domestic building.
View ProjectNeoscholar-Machine_Learning_Basics
April 11, 2021 – March 20, 2022
Coding assignments materials
View ProjectUCL_AISOC_Tutorial_HandGestureRecognition
February 11, 2021 – February 16, 2021
This project aims to design a real-time vision-based hand gesture recognition system with machine learning techniques, which potentially makes deaf-and-mute people life easier.
View ProjectReal-time-Vision-based-Sign-Language-Recognition-System
October 4, 2020 – October 5, 2020
My undergraduate Final Year Project awarded as the Excellent Bachelor's Project. It develops a vision-based sign language recognition system with multiple machine-learning models, which currently can recognize 10 static and 2 dynamic gesutures in ASL with testing accuracy of 99.68%.
View ProjectMachine-Learning-Tutorials
October 11, 2019 – October 9, 2021
Materials for UCL Artificial Intelligence Society Machine Learning Tutorials Season 1 (2020/2021)
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in academic and research-oriented machine learning, with several projects stemming from university affiliations (UCL, Neoscholar). This suggests a fit for environments that value deep technical exploration and contribution to open-source or academic communities. However, the lack of diverse project types (all personal/academic) and limited professional experience (one current role with no details) makes it difficult to fully assess cultural fit for a corporate or product-focused environment. The projects show a strong alignment with the technical demands of a Data Scientist role, particularly in advanced ML research.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong technical drive and interest in complex problem-solving, but there is no information regarding collaboration, communication, or stress handling.