Our Staff

Research Interests

Machine Learning, Statistical Computing, Data Mining, Time series modelling, Operations Research

Selected Publications

• Carlin C.F. Chu, Raymond So, Ernest K.L. Kwong and Andy Chan, “Multiword Target-Independent Transformer-Based Model for Financial Sentiment Analysis in Colloquial Cantonese” (Accepted for publication).
• Carlin C.F. Chu and David P.K. Chan, “Prediction of local extrema in financial time series with Multiple Timeframe Extreme Gradient Boosting method“, 18th International Conference on Computational and Financial Econometrics (CFE-CMStatistics), London, UK, 14-16 December 2024.
• J. Lian, F. Huang, X. Huang, Kitty Y.Y. Lau, K.S. Ng, Carlin C.F. Chu, Simon C. Lam, M. Koohli-Moghadam, and Varut Vardhanabhuti. “Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset.” BMC Infectious Diseases 24, no. 1 (2024): 1-11.
• Carlin C.F. Chu, Jonathan H.Y. Leung, Raymond So and Andy Chan, “Automatic verbalizer for extracting fine-grained customer opinions from non-English social media comments“. HCII 2024. Communications in Computer and Information Science, vol 2119. Springer, Cham. 16th International Conf. on Social Computing and Social Media, Washington DC, 29 Jun-4 Jul 2024.
• Carlin C.F. Chu, Charlotte H.N. Choy and Sarah Y.N. Kam, “Recent Developments and Applications of Social Media AI Cyberbullying Detection Technology in the Education Field“.  The Asian Conference on Education & International Development (ACEID2024), Tokyo, 25-29 Mar 2024.
• Carlin C.F. Chu and Simon S.W. Li, “A multiobjective optimization approach for threshold determination in extreme value analysis for financial time series“.  Computational Management Science, Vol. 21, Article 7 (2024).
• Carlin C.F. Chu, Raymond So, Ernest K.L. Kwong and Andy Chan, “Leveraging rule-based model and machine learning transformer for mining aspect-based financial opinions in colloquial language“. Proc. of 7th International Conference on Software and e-Business, Dec 2023, p71–78.
• Carlin C.F. Chu and David P.K. Chan, “Simulation of high-fidelity limit order book data with machine learning model for Asia exchange markets“.  International Conference on Econometrics and Statistics (EcoSta), Tokyo, 1-3 Aug 2023.
• Carlin C.F. Chu, Raymond So, Simon S.W. Li, Ernest K.L. Kwong and C.H. Chiu, “A framework for early detection of cyberbullying in Chinese-English code-mixed social media text using natural language processing and machine learning“.  In 2023 5th International Conference on Natural Language Processing (ICNLP), pp. 298-302. IEEE, 2023. 
• K.H. Ho, Y. Hou, Carlin C.F. Chu, C.K. Chan, H. Pan, T.T. Chan. “Work in Progress: An AI-Assisted Metaverse for Computer Science Education.” In 2023 IEEE World Engineering Education Conference (EDUNINE), pp. 1-4. IEEE, 2023.
• Raymond So, Carlin C.F. Chu, Jessie C.W. Lee. “Extract Aspect-based Financial Opinion Using Natural Language Inference.” In Proceedings of the 2022 International Conference on E-business and Mobile Commerce, pp. 83-87. 2022.
• W.H. Chiu, C.F. Chu, K.H. Ho, C.M. Liu and Y.W. Ho. “A Survey of Innovative Tools for Teaching Secondary School STEAM Coding in Hong Kong”. International Conference on Learning and Teaching (ICLT), Hong Kong, 8-10 December 2021.
• Kevin Hung, Ho-Yuen Cheung, Nathan Wan, Eva Lee, Chi-Nang Lai, Kun Pan, Rongle Liang, Carlin Chu, Sheung-On Choy, Douglas Ng and Daniel H.K. Chow, “Design, Development, and Evaluation of Upper and Lower Limb Orthoses with Intelligent Control for Rehabilitation”, IET Science, Measurement & Technology, Vol. 15, Iss. 9, pp. 738-748, Nov 2021.
• Carlin CF Chu, Simon SW Li, Indy MK Ho, FH Tang and Douglas KS Ng, “Statistical conformity index for improving the evaluation of Intensity-Modulated Radiation Therapy (IMRT) plan for neck and head cancer”, Royal Statistical Society (RSS) Conference 2021, 6-9 Sep 2021, Manchester and Online.
• Carlin CF Chu and PK Chan. “Feature selection using approximated high-order interaction components of the Shapley value for boosted tree classifier”, IEEE Access, Vol. 8: 112742-112750 (2020).
• Simon SW Li, Carlin CF Chu and Daniel HK Chow. “EMG-based lumbosacral joint compression force prediction using a support vector machine”, Medical Engineering and Physics, Vol. 74: 115–120 (2019).
• TH Cheng, KL Li, CL Wong, SY Lau, CL Ng and Carlin CF Chu. “Identification of pairs trading opportunities using copula-based conditional probabilities and machine learning models”, 3rd Int Conf on Econometrics and Statistics (EcoSta2019), 25-27 June 2019.
• Carlin CF Chu and PK Chan. “Decomposition of high frequency Forex signals for Copula based pairs trading strategy with Support Vector Regression”, 12th Int Conf on Computational and Financial Econometrics, 14-16 Dec 2018.
• Carlin CF Chu and PK Chan. “Mining profitable high frequency pairs trading Forex signal using copula and deep neural network”, Proc. of 19 IEEE/ACIS Int. Conf. on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), pp. 312-316, Busan, Korea, 27-29 Jun 2018.
• Carlin CF Chu, SC Yuen and YK Wong. “Deep neural network for marine water quality classification with the consideration of coastal current circulation effect”, Proc. of IEEE Int. Conf. on Intelligent Sustainable Systems (ICISS), pp. 389-394, Palladam, India, 7-8 Dec 2017.
• Carlin CF Chu and SC Yuen, “Prediction of Chlorophyll-a concentration using Artificial Neural Network and Long Short-Term Memory network”, Int Conf on Engineering and Applied Sciences, 4-6 Jul 2017.
• Carlin CF Chu. “On deep machine learning & time series models: A case study with the use of Keras”, 1st Intl Conf on Econometrics and Statistics (EcoSta2017), 15-17 Jun 2017.
• Carlin CF Chu. “Does information from cross-listed markets help modeling stock volatility? An empirical study on companies listed on Hong Kong, Shanghai and NYSE”, Quantitative Methods in Finance (QMF) Conf, Sydney 15-18 Dec 2015.
• James Caldwell, Carlin Chu and Douglas Ng. “Numerical Solution of Stefan Problems by Variable Space Grid Method”, 8th Int Congress on Industrial & Applied Mathematics, Beijing, 10-14 Aug 2015.

Selected Professional Services

• Reviewer for several international journals including IET software, IEEE Access, Applied Economics, Econometrics and Statistics, and Journal of International Financial Markets, Institutions & Money, etc. Technical committee members for 10+ international conferences.
• Invited speaker, “Big Data and Machine Learning Models in Quantitative Finance”, 17th Asia-Pacific Conference on Global Business, Economics, Finance & Social Sciences, 19-20 Jan 2018.

Research Grant

• PI, “Early Detection of Cyberbullying Incidents in Chinese-English Code-Mixed Language with Targeted Emotional Colloquial Slang Phrases: A Transfer Learning Approach”, Research Grant Committee, Faculty Development scheme, Project No: UGC/FDS14/E02/22, Jan 2023 – Jun 2025
• PI, “Electronic & Algo Trading with Machine Learning & Artificial Intelligence”, Research Grant Committee, Research Matching Grant Scheme, Jul 2022 – Jun 2024
• PI, “Investigation and Evaluation of the Effectiveness of Artificial Intelligence Models in Financial Investment Portfolio Selection Models”, Research Grant Committee, Research Matching Grant Scheme, Jun 2021 – May 2024
• Co-I, “Improved Indoor Air Quality (IAQ) management through Scientific IAQ monitoring and App Survey with an indication of energy demand reduction”, Research Grant Committee, Project No: UGC/FDS16/P01/20, Sep 2020 – Aug 2022
• Co-I, “New Development of Rapid and Easy Authentication Method of Single Drug Concentrated Chinese Medicine Granules using Fourier-Transform Infrared Spectroscopy (FTIR) coupled with Chemometrics”, Research Grant Committee, Project No: UGC/FDS16/M08/20, Sep 2020 – Aug 2022
• Co-I, “Recent Developments in Business Analytics and New Research Directions”, Research Grant Committee, Project No: UGC/IIDS14/P01/17, Sep 2017 – Aug 2018
• PI, “Investigation of Algal Bloom Prediction Models on Hong Kong Marine Zones Using Unevenly-spaced Data”, Katie Shu Sui Pui Charitable Trust Research and Publication Fund, Project No: KS2016/2.1, Sep 2017 – Aug 2019
• Co-I, “Development of an Exergaming System with Haptic Feedback for the Investigation of Energy Expenditure and Muscle Activities during Sports Training”, Research Grant Committee, Project No: UGC/FDS16/M02/14, Sep 2016 – Dec 2018
• Co-I, “Development of an Android-based Smart-Tablet-Aided Diagnosis / Evaluation Programme for Intensity-Modulated Radiotherapy Treatment Planning”, OUHK research and development grant, Project No: 2015/1.12, Feb 2016 – Sep 2017

Student services

• Best presenter award, ICSeB, 2023
• Supervisor of the student team, Greater Bay Area STEM Excellence Award, 2022
• Advisor of the Champion student team, HSUHK x SCMP Entrepreneurship Day, 2021
• Outstanding supervisor award, CUMCM contest, 2017
• Outstanding supervisor award, IBM Programming contest, 2012
• The most student-caring teacher award, 2003