Link
Home
Google Scholar
ResearchGate
USYD Research Project
Linkedin
Download my CV

Haohui LU

alt text  The University of Sydney, Australia
E-mail: haohui.lu[at]sydney.edu.au

About me

Haohui Lu holds a PhD in Data Science from the University of Sydney, where he specialised in AI for Healthcare. His academic journey includes a Master's in Project Management and a Bachelor's in Commerce, majoring in Operational Management and Decision Sciences. Haohui Lu has an impressive publication record, with over 20 peer-reviewed papers. His expertise extends beyond academia, with significant industry experience, including a role as a Data Analyst. As an academic at the University of Sydney, he has demonstrated excellence in teaching a variety of data science, business analytics and project management courses. Currently, Haohui Lu is an AI researcher at the University of Sydney, focusing on Generative AI and working on projects centered around large language models.

Research Interests

  • Generative AI: Foundation models and large language models

  • AI in Healthcare: Machine learning applications in health

  • Machine Learning on Graphs: Graph embedding, graph neural networks, knowledge graphs

Education

Doctor of Philosophy, The University of Sydney, 07.2020 - 12.2023, Conferral date: 18 March 2024

  • Thesis title: Chronic Disease Prediction using Graph Machine Learning

Graduate Certificate in Data Science, The University of Sydney, 11.2019

  • Distinction average

  • Main Courses: Data science, Statistics, Database Management Systems, Algorithms.

Master of Project Management, The University of Sydney, 11.2012

  • Distinction average

  • Main Courses: Project economic and scheduling control.

Bachelor of Commerce, The University of Sydney, 11.2011

  • Main Courses: Operations management, Business Analytics

Honours and Awards

  • Feedback for Teaching Student Survey Award 2024 - The University of Sydney
  • Paulette Isabel Jones Career Award 2023 - The University of Sydney
  • Postgraduate Research Support Scheme 2022 - The University of Sydney

Research experience

  1. Researcher, The University of Sydney, 07.2024 - Now

    • Managed the end-to-end development and training of AI models, driving operational efficiency and quality through comprehensive analysis of project data and business scenarios.

    • Led a faculty-funded project on child undernutrition, optimizing processes and enhancing collaboration with cross-functional international teams, including policymakers in Indonesia.

    • Integrated Large Language Models (LLMs) into web-based GUIs, improving data interaction and visualization.

  2. Research Assistant, The University of Sydney, 10.2022 - 07.2024

    • Supported multidisciplinary experts in National Health and Medical Research Council (NHMRC) Ideas Grant project

    • Spearheaded data preprocessing and analysis for Bilateral Investment Treaties (BITs) using Natural Language Processing (NLP), enhancing treaty analysis with a custom-built LLM featuring interactive querying capabilities.

    • Developed and maintained dashboards, utilizing advanced data visualization tools to ensure clear communication of complex data insights.

    • A tool is developed by me for this article with demo video.

  3. Doctoral Researcher, The University of Sydney, 07.2020 - 12.2023

    • Conducted research on chronic disease prediction using graph machine learning, achieving improved accuracy in identifying high-risk patients.

    • Managed large datasets using SQL and Python, employing machine learning techniques to derive actionable insights.

    • Created interactive dashboards with Tableau, PowerBI, and Python, facilitating data-driven decision-making.

Academic experience

  1. Casual Academic, The University of Sydney, 07.2020 - Present

    • Tutoring and marking:

      • 2024s2: PMGT6310 Business Operation Analysis, PMGT3340 Operation Management, QBUS2310 Management Science, PMGT3623 Scheduling
      • 2024s1: PMGT5873 Project Economics and Procurement, QBUS6820 Prescriptive Analytics: From Data To Decision, QBUS6840 Predictive Analytics
      • 2023s2: QBUS2310 Management Science, QBUS2810 Statistical Modelling for Business, QBUS6840 Predictive Analytics, PMGT5866 Quantitative Methods in Project Management (Course design)
      • 2023s1: QBUS2310 Management Science, QBUS6820 Prescriptive Analytics: From Data To Decision, QBUS6840 Predictive Analytics
      • 2022s2: QBUS6820 Business Risk Management, QBUS6840 Predictive Analytics
      • 2020s2 - 2022s2: PMGT6867 Quantitative Methods in Project Management

Recent Publications

2024

  1. H Lu, U Naseen, "Can Large Language Models Enhance Predictions of Disease Progression? Investigating Through Disease Network Link Prediction", Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, (2024) 17703–17715 [link]

  2. H Lu, S Uddin, "A parameterised model for link prediction using node centrality and similarity measure based on graph embedding", Neurocomputing, (2024) 127820. [link]

  3. H Lu, S Uddin, "Unsupervised machine learning for disease prediction: a comparative performance analysis using multiple datasets", Health and Technology, (2024): 14 (1), 141 - 154. [link]

  4. S Uddin, H Lu, A Rahman, J Gao, "A novel approach for assessing fairness in deployed machine learning algorithms", Scientific Reports, (2024), 14 (1), 17753. [link]

  5. S Uddin, H Lu, W Alschner, D Patay, N Frank, FS Gomes, AM Thow, "An NLP-based novel approach for assessing national influence in clause dissemination across bilateral investment treaties", Plos One, (2024): 19(3), e0298380. [link]

  6. S Uddin, H Lu, "Confirming the statistically significant superiority of tree-based machine learning algorithms over their counterparts for tabular data", Plos One, (2024): 19(4), e0301541. [link]

  7. S Uddin, S Yan, H Lu, "Machine learning and deep learning in project analytics: methods, applications and research trends", Production Planning & Control, (2024): 1-20. [link]

  8. S Uddin, H Lu, "Dataset meta-level and statistical features affect machine learning performance", Scientific Reports, (2024): 14 (1), 1670. [link]

  9. S Uddin, A Khan, H Lu, F Zhou, S Karim, F Hajati, MA Moni, "Road networks and socio-demographic factors to explore COVID-19 infection during its different waves", Scientific Reports, (2024): 14 (1), 1551. [link]

2023

  1. H Lu, S Uddin, "KNN-Based Patient Network and Ensemble Machine Learning for Disease Prediction", International Conference on Health Information Science, 2023. [link]

  2. H Lu, S Uddin, "Disease Prediction Using Graph Machine Learning Based on Electronic Health Data: A Review of Approaches and Trends", Healthcare 11 (7), 1031, 2023. [link]

  3. H Lu, S Uddin, "Embedding-based link predictions to explore latent comorbidity of chronic diseases", Health Information Science and Systems 11(2), 2023. [link]

  4. H Lu, S Uddin, "Explainable Stacking-Based Model for Predicting Hospital Readmission for Diabetic Patients", Information 13(9), 436. [link]

  5. S Uddin, A Kan, H Lu, "Impact of COVID-19 on Journal Impact Factor", Journal of Informetrics, (2023): 17(4), 101458. [link]

  6. S Uddin, S Ong, H Lu, P Matous, "Integrating machine learning and network analytics to model project cost, time and quality performance", Production Planning & Control 11 (7), 1031, 2023. [link]

2022

  1. H Lu, S Uddin, "Predictive risk modelling in mental health issues using machine learning on graphs", ACSW 2022: Australasian Computer Science Week 2022, (2022). [link]

  2. H Lu, S Uddin, "A disease network-based recommender system framework for predictive risk modelling of chronic diseases and their comorbidities", Applied Intelligence, (2022): 1-11. [link]

  3. H Lu, S Uddin, F Hajati, MA Moni, M Khushi, "A patient network-based machine learning model for disease prediction: The case of type 2 diabetes mellitus", Applied Intelligence, (2022): 1-12. [link]

  4. S Uddin, S Ong, H Lu, "Machine learning in project analytics: a data-driven framework and case study", Scientific Reports 12.1 (2022): 1-13. [link]

  5. S Uddin, S Wang, H Lu, A Khan, F Hajati, M Khushi, "Comorbidity and multimorbidity prediction of major chronic diseases using machine learning and network analytics", Expert Systems with Applications, (2022): 117761 (205). [link]

  6. S Wang, H Lu, A Khan, F Hajati, M Khushi, S Uddin, "A machine learning software tool for multiclass classification", Software Impacts, (2022): 100383 (13). [link]

  7. S Uddin, H Lu, A Khan, S Karim, F Zhou, "Comparing the Impact of Road Networks on COVID-19 Severity between Delta and Omicron Variants: A Study Based on Greater Sydney (Australia) Suburbs", International Journal of Environmental Research and Public Health, (2022): 19 (11), 9551. [link]

  8. S Uddin, I Haque, H Lu, M Moni, E Gide, "Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction", Scientific Reports, (2022): 1-12. [link]

  9. S Uddin, S Wang, A Khan, H Lu, "Comorbidity progression patterns of major chronic diseases: The impact of age, gender and time-window", Chronic Illness, (2022). [link]

  10. S Uddin, A Khan, H Lu, F Zhou, S Karim, "Suburban Road Networks to Explore COVID-19 Vulnerability and Severity", International Journal of Environmental Research and Public Health, (2022): 19 (4), 2039. [link]

2021

  1. H Lu, S Uddin, "A weighted patient network-based framework for predicting chronic diseases using graph neural networks", Scientific Reports, (2021): 1-12. [link]

Full list of publications in Google Scholar.

Conferences and paper presentations

Invited to serve as a session chair @ Sunbelt 2022. Session 93-1. Migration and social networks in the COVID-19 context. Full details here.

My poster is accepted in Digital Health Week 2022.

Academic service

Reviewer

  • Advanced Engineering Informatics

  • BMC Health Services Research

  • BMC Medical Informatics and Decision Making

  • BMC Public Health

  • Cardiovascular Diabetology

  • Cluster Computing

  • Complexity

  • Computers in Biology and Medicine

  • Computing

  • Health and Technology

  • Health Data Science

  • iScience

  • Journal of Computational Social Science

  • Journal of Medical Systems

  • Machine Learning with Applications

  • Scientific Reports

  • Signal, Image and Video Processing

Professional experience

  1. Peer Support Advisor/Senior Peer Supper Advisor, 06.2021 - 06.2023

    • Assist students with a range of enquiries, ranging from what support services the university offers to what social activities a student can join

  2. Personal Banker, ANZ bank, 06.2016 - 04.2020

    • Provide a full range of professional sales advice to help customers achieve their financial needs and goals. Explain lending products’ fees, interest, and current campaigns to the customer, ensuring that the products meet customers’ needs.

    • Tier 2 Personal Advice, Personal lending, and small business accreditation.

  3. Project Administrator/Business Analyst, Dynamic Payment Pty Ltd, 08.2012 - 07.2016

    • Led initiatives to detect and mitigate fraudulent activities, resulting in enhanced security and business growth during peak periods.

    • Analyzed sales data to develop predictive models and interactive dashboards, significantly improving business transparency and decision-making processes.

    • Provided essential administrative support to technical teams, including scheduling, minute-taking, and training coordination, contributing to project success.


Update on: Nov 2024.