Zhang Tianhui

Zhang, Tianhui 张天慧

PhD in Computer Science

University of Liverpool, UK

About Me

I completed my PhD in Computer Science at the University of Liverpool, supervised by Prof. Danushka Bollegala and Dr. Bei Peng. I previously obtained an MSc in Data Science and Machine Learning with Distinction from University College London and a First-Class BSc in Artificial Intelligence from the University of Liverpool.

My research focuses on large language models, retrieval-augmented generation, synthetic data, trustworthy evaluation, and agentic AI. I study how generative models use evidence, adapt to new data, and can be evaluated through reproducible and human-grounded methods.

Natural Language Processing Large Language Models Retrieval-Augmented Generation Synthetic Data Trustworthy AI Agentic AI

Publications

ACL 2026

Synthetic Data Generation for Training Diversified Commonsense Reasoning Models

Tianhui Zhang, Bei Peng and Danushka Bollegala

Paper →
EACL 2026

Evaluating the Effect of Retrieval Augmentation on Social Biases

Tianhui Zhang, Yi Zhou and Danushka Bollegala

Paper →
ACL 2025

Evaluating the Evaluation of Diversity in Commonsense Generation

Tianhui Zhang, Bei Peng and Danushka Bollegala

Paper →
ACL 2025

BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages

Shamsuddeen Hassan Muhammad et al.

Paper →
EMNLP 2024

Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning

Tianhui Zhang, Bei Peng and Danushka Bollegala

Paper →
IJCNLP-AACL 2023

Learning to Predict Concept Ordering for Common Sense Generation

Tianhui Zhang, Danushka Bollegala and Bei Peng

Paper →

Projects

Apr 2026 – Present

Evaluation Platform for Agentic LLMs

  • Designed and implemented an end-to-end, multi-provider platform for auditing search-enabled and agentic LLMs
  • Integrated automated data collection, source and evidence enrichment, evaluation metrics, human review, dashboards, testing, and Linux deployment
  • Evaluated source selection, evidence use, provider differences, and repeated-run stability
2025 – 2026

CommonSyn: Synthetic Data for Diversified Reasoning

  • Developed a generation-and-selection pipeline for constructing diverse, high-quality commonsense training data
  • Fine-tuned 11 Llama, Qwen, and Gemma models using supervised fine-tuning with LoRA
  • Evaluated quality, diversity, transfer to unseen tasks, and retention of general reasoning capabilities
2024 – 2026

Retrieval-Augmented Generation and Social Bias

  • Evaluated how retrieved evidence changes social bias across 16 LLMs, three languages, and four bias categories
  • Separated the effects of document collections, retrievers, prompts, and generator models
  • Compared mitigation strategies including prompting, evidence summarisation, and Direct Preference Optimisation
2022

Companies Knowledge Graph Construction

  • Design the schema of the knowledge graph
  • Crawled the company information from websites
  • Develop algorithms to fetch the inference chains
2020 – 2022

Financial Open Information Extraction

  • Construct knowledge graph by designing a BERT open information extraction system
  • Create the dataset from Wikipedia and SEC filings
2020

Abstract Summarization

  • Applying 3 pre-trained models (BERT, MASS and MiniLM) on abstract summarization task and compared the performance on WikiHow dataset
2019

Negative Transfer of Word Meta-Embedding

  • Research on negative transfer of word embedding under supervision of Prof. D. Bollegala
  • Show great performance on tasks such as semantic similarity
2018

Search Filter

  • Developing a website that answers user's questions by crawled webpages
  • TextRank algorithm and cosine similarity to rank the paragraphs and webpages

Education

2022 – 2026

PhD in Computer Science

University of Liverpool, UK

2019 – 2020

MSc Data Science and Machine Learning

University College London, UK

Distinction Degree, 75% Average Score

2015 – 2019

BSc Artificial Intelligence

University of Liverpool, UK

First Class Degree

Experience

Service

Reviewer

2024 – Present

ACL, EMNLP, EACL, IJCNLP, COLING

Teaching

Teaching Assistant

2022 – 2023

University of Liverpool

  • COMP337/527 Data Mining and Visualization, 2023
  • COMP304 Knowledge Representation, 2022/2023
  • COMP518 Database and Information System, 2023

Internships

Knowledge Graph Developer

Jan 2022 – Sep 2022

IICT, Suzhou

  • Researched NLP algorithms and knowledge graph on hot news and company information
  • Constructed and maintained a finance knowledge graph
  • Tracked, studied, reproduced, and improved up-to-date machine learning methods

Webpage Developer

Aug 2019 – Jun 2021

Xi'an Jiaotong Liverpool University, Market Department

  • Implemented and maintained a market customer analysis website
  • Helped staff to analyze customer's preferences with their job, province and university

Software Engineer

Jun 2017 – Sep 2017

RISE English School

  • Developed a system to manage the students and classes
  • Helped teachers to easily track their students' courses, classes and tuition fee
  • Updated the information automatically in the database and generated weekly reports