Machine learning
Statistical learning, probabilistic modelling, feature preparation, model comparison and careful interpretation of assumptions and limitations.
Sheffield, United Kingdom
Zhongjie Huang
Artificial Intelligence & Computer Science. I develop data-driven software and explore reliable approaches to machine learning, language technologies, computational modelling and responsible AI.
About
Research discipline with engineering delivery.
I am trained in artificial intelligence and computer science at the University of Sheffield. My interests span machine learning, natural language processing, data analysis, scalable computing and software development. I value clear problem definitions, transparent assumptions, reliable evaluation, reproducible implementation and technical communication that distinguishes evidence from interpretation.
AI + CSCross-disciplinary academic training
Build + testFrom requirements to evaluation
Explain limitsEvidence, uncertainty and responsible use
Core skills
See every moduleCapabilities grounded in coursework and completed work.
Language technology
Text preprocessing, corpus handling, quantitative analysis, representation methods and evaluation of contemporary NLP approaches.
Data science
Python-based analysis, data cleaning, statistical methods, method selection and reproducible interpretation of results.
Scalable computing
Parallelisation, GPU concepts, stochastic optimisation, large-scale processing, Spark and cluster-computing principles.
Software engineering
Java, web and mobile development, systems design, security, testing, documentation and maintainable modular architecture.
Research engineering
Literature synthesis, experimental design, validation planning, sensitivity to dataset bias and clear reporting of what results can and cannot support.
Selected projects
Completed systems and public case studies.
Only completed, non-confidential work is described. Claims are tied to supplied reports or demonstrable software features.
Visual emotion recognition
Completed BSc project combining a browser interface, Java/Tomcat services and a Python deep-learning pipeline for facial-expression classification.
Investment & financial management
A private full-stack application used here as evidence of data modelling, workflow design, access control and maintainable Java engineering.
This portfolio
A bilingual, accessible static application with searchable coursework, command navigation, theme support and a deployment-first security model.
Education
View BSc certificateAcademic background.
MSc Artificial Intelligence
University of Sheffield · 2025–2026 · in progress
Relevant areas: machine learning, natural language processing, data science, scalable computing, GPU computing, team-based development and professional issues.
BSc Artificial Intelligence and Computer Science
University of Sheffield · 2021–2025 · completed
Relevant areas: programming, algorithms, AI foundations, robotics, data-driven computing, security, distributed systems, computational modelling and applied project work.
Research interests
Explore research interestsFrom predictive performance to defensible evidence.
Mechanistic + data-driven models
Combining simulation, individual-based modelling and machine learning where structure and measurement constraints matter.
Validation under shift
Patient- or subject-separated evaluation, external datasets, calibration, sensitivity analysis and transparent failure modes.
Responsible decision support
Systems that communicate uncertainty, respect privacy and remain appropriately bounded by the evidence available.
Contact
Let’s discuss research, software or doctoral study.
For professional and academic communication, please use my University of Sheffield email address.