Dr LING, Man Ho Alpha    凌萬豪 博士
Acting Head and Associate Professor
Department of Mathematics and Information Technology
Contact
ORCiD
0000-0002-9954-8302
Phone
(852) 2948 7815
Email
amhling@eduhk.hk
Address
10 Lo Ping Road, Tai Po, New Territories, Hong Kong
Scopus ID
26423822200
Research Interests
  • Lifetime data analysis in reliability & survival studies
  • Degradation data analysis
  • Statistical inference under censoring
  • Statistical computing
External Appointments
  1. Membership Secretary, The Hong Kong Statistical Society (HKSS), since 2017
  2. Editorial Board Member, Communications in Statistics - Theory and Methods, since 2017
  3. Editorial Board Member, Communications in Statistics - Simulation and Computation, since 2017
  4. Editorial Board Member, Communications in Statistics - Case Studies, Data Analysis and Applications, since 2017
  5. Editorial Board Member, International Journal of Applied & Experimental Mathematics, since 2016
  6. Organizing Committee Member, Mathematics Project Competition for Secondary Schools, 2015-2019
  7. Organizing Committee Member, The Hong Kong Mathematics Olympiad, 2015-2019


Personal Profile

Education

  • Ph.D., McMaster University

Thesis Title: Inference for One-Shot Device Testing Data (Advisor: Prof. N. Balakrishnan)

  • M.Phil., Hong Kong Baptist University

Thesis Title: Full Friendly Index Sets of Cartesian Product of Two Cycles (Advisors: Prof. W.C. Shiu and Prof. M.L. Tang)

  • B.Sc. in Mathematics & Statistics, Hong Kong Baptist University
  • PGDE (Major: Mathematics), The Chinese University of Hong Kong

Employment

  • Associate Professor, Department of Mathematics and Information Technology, The Education University of Hong Kong, since Jul 2020
  • Assistant Professor, Department of Mathematics and Information Technology, The Education University of Hong Kong, Jul 2015 - Jun 2020
  • Lecturer, Department of Mathematics and Information Technology, The Education University of Hong Kong, Aug 2013 - Jun 2015
  • Research Fellow, Department of Systems Engineering and Engineering Management, The City University of Hong Kong, Apr 2013 – July 2013
  • Post Doctoral Fellow, Department of Systems Engineering and Engineering Management, The City University of Hong Kong, Aug 2012 – Mar 2013


Research Interests

  • Lifetime data analysis in reliability & survival studies
  • Degradation data analysis
  • Statistical inference under censoring
  • Statistical computing
External Appointments

  1. Membership Secretary, The Hong Kong Statistical Society (HKSS), since 2017
  2. Editorial Board Member, Communications in Statistics - Theory and Methods, since 2017
  3. Editorial Board Member, Communications in Statistics - Simulation and Computation, since 2017
  4. Editorial Board Member, Communications in Statistics - Case Studies, Data Analysis and Applications, since 2017
  5. Editorial Board Member, International Journal of Applied & Experimental Mathematics, since 2016
  6. Organizing Committee Member, Mathematics Project Competition for Secondary Schools, 2015-2019
  7. Organizing Committee Member, The Hong Kong Mathematics Olympiad, 2015-2019


Research Outputs

Scholarly Books, Monographs and Chapters
Research book or monograph (author)
Balakrishnan, N., Ling, M.H., So, H.Y. (2021). Accelerated Life Testing of One-shot Devices: Data Collection and Analysis. Hoboken, New Jersey: John Wiley & Sons.
Chapter in an edited book (author)
Ling, M.H. (2024). On analysis of one-shot devices with multiple components. In Mangey Ram (Ed.), Developments in Reliability Engineering, 1st ed. (1-24). Elsevier.
Ling, M.H., Balakrishnan, N. (2023). Recent developments in accelerated life testing data analyses for one-shot devices. In Pham, Hoang (Ed.), Springer Handbook of Engineering Statistics, 2nd ed. (1039-1057). London: Springer London.
Ling, M.H., Hu X.W. (2022). A Bayesian approach for step-stress accelerated life-tests for one-shot devices under exponential distributions. In Lio, Yuhlong, Chen, Ding-Geng, Ng, Hon Keung Tony, Tsai, Tzong-Ru (Eds.), Bayesian Inference and Computation in Reliability and Survival Analysis (3-16). Cham: Springer International Publishing.
Ling, M.H., So, H.Y., Balakrishnan, N. (2022). A Bayesian approach for the analysis of tumorigenicity data from sacrificial experiments under Weibull lifetimes. In Lio, Yuhlong, Chen, Ding-Geng, Ng, Hon Keung Tony, Tsai, Tzong-Ru (Eds.), Bayesian Inference and Computation in Reliability and Survival Analysis (215-237). Cham: Springer International Publishing.
Ling, M.H., Ng, H.K.T., Tsui, K.L. (2017). Inference on remaining useful life under gamma degradation models with random effects. In Chen, Ding-Geng, Lio, Yuhlong, Ng, Hon Keung Tony, Tsai, Tzong-Ru (Eds.), Statistical Modeling for Degradation Data (253-266). Singapore: Springer, Singapore.
Poon, L. K. M., Kong, S. C., Yau, T. S. H., Wong, M., & Ling, M. H. (2017). Learning analytics for monitoring students’ participation online: Visualizing navigational patterns on learning management system. In S. K. Cheung, L.-F. Kwok, W. W. Ma, L.-K. Lee, & H. Yang (Eds.), Blended Learning. New Challenges and Innovative Practices. ICBL 2017. LNCS, vol 10309 (pp. 166-176). Cham: Springer.
Balakrishnan, N., Ling, M.H., So, H.Y. (2016). Constant-stress accelerated life-test models and data analysis for one-shot devices. In Fiondella, L., Puliafito, A. (Eds.), Principles of Performance and Reliability Modeling and Evaluation (77-108). Switzerland: Springer, Cham.

Journal Publications
Publication in refereed journal
Ling, M.H., Ng, H.K.T., Shang, X.W., Bae, S.J. (2024). Efficient Bayesian inference for a defect rate based on completely censored data. Applied Mathematical Modelling, 128, 123-136. https://doi.org/10.1016/j.apm.2024.01.022
Ling, M.H., Bae, S.J. (2024). A random-effect gamma process model with random initial degradation for accelerated destructive degradation testing data. Quality and Reliability Engineering International, 40, 374-387.
Deepak, P., Ling, M.H., Chan, P.S., Kundu, D. (2023). Misspecification of copula for one-shot devices under constant stress accelerated life-tests. Proceedings of the Institution of Mechanical Engineer Part O: Journal of Risk and Reliability, 237, 725-740. https://doi.org/10.1177/1748006X221108850
Lin, C.T., Wu, Y.N., Balakrishnan, N., Ling, M.H. (2023). OTL: Outliers testing for lifetime data online. Communications in Statistics – Simulation and Computation, accepted, 1-22. https://doi.org/10.1080/03610918.2022.2116748
Shang, X.W., Ng, H.K.T., Ling, M.H. (2023). On reliability analysis of one-shot device testing data with defects. Quality Engineering, 35, 79-94. https://doi.org/10.1080/08982112.2022.2089855
Lin, C.P., Dorigatti, I., Tsui, K.L., Xie, M., Ling, M.H., Yuan, H.Y. (2022). Impact of early phase COVID-19 precautionary behaviours on seasonal influenza in Hong Kong: a time-series modelling approach. Frontiers in Public Health, 10, 3850. https://doi.org/10.3389/fpubh.2022.992697
Lin, C.T., Balakrishnan, N., Ling, M.H. (2022). Exact tests for outliers in Laplace samples. Communications in Statistics – Simulation and Computation, 51, 5794-5815.
Hsu, M.H.K., Ye, Q., Ling, M.H. (2022). Career preferences among nursing students: A cross-sessional study. SAGE Open Nursing, 8, 1-11. https://doi.org/10.1177/23779608221094538
Ling, M.H. (2022). Optimal constant-stress accelerated life test plans for one-shot devices with components having exponential lifetimes under gamma frailty models. Mathematics, 10, 840.
Balakrishnan, N., Castilla, E., Ling, M.H. (2022). Optimal designs of constant-stress accelerated life-tests for one-shot devices with model misspecification analysis. Quality and Reliability Engineering International, 38, 989-1012.
Ling, M.H., Balakrishnan, N., Yu, C.X., So, H.Y. (2021). Inference for one-shot devices with dependent k-out-of-M structured components under gamma frailty. Mathematics, 9, 3032.
Lin, C.P., Ling, M.H., Cabrera, J., Yang, F.F., Yu, Y.W., Tsui, K.L. (2021). Prognostics for lithium-ion batteries using a two-stage gamma degradation process model. Reliability Engineering and System Safety, 214, 107797.
Ling, M.H., Chan, P.S., Ng, H.K.T., Balakrishnan, N. (2021). Copula models for one-shot device testing data with correlated failure modes. Communications in Statistics – Theory and Methods, 50, 3875-3888.
Lin, C.P., Cabrera, J., Yang, F.F., Ling, M.H., Tsui, K.L., Bae, S.J. (2020). Battery state of health modeling and remaining useful life prediction through time series model. Applied Energy, 275, 115338.
Ling, M.H., Hu, X.W. (2020). Optimal design of simple step-stress accelerated life test for one-shot devices under Weibull distributions. Reliability Engineering & System Safety, 193, 106630.
Hsu, M.H.K., Ling, M.H (2019). Nursing students' attitudes towards older people and future career choices in Macao - A Pilot Study. Journal of Nursing Education and Practice, 9, 10-19.
Ling, M.H., Ng, H.K.T., Tsui, K.L. (2019). Bayesian and likelihood inferences on remaining useful life in two-phase degradation models under gamma process. Reliability Engineering & System Safety, 184, 77-85.
Hsu, M.H.K., Ling, M.H., Lui, T.L. (2019). Relationship between gerontological nursing education and attitudes toward older people.. Nurse Education Today, 74, 85-90.
Ling, M.H. (2019). Optimal design of simple step-stress accelerated life test for one-shot devices under exponential distributions. Probability in the Engineering and Informational Sciences, 33, 121-135.
Ng, H.K.T., Ling, M.H., Chan, P.S. (2018). A gamma process modeling approach for comparison of dissolution profiles. Drug Development and Industrial Pharmacy, 44, 553-562.
Ling, M.H., Balakrishnan, N. (2017). Model mis-specification analyses of Weibull and gamma models for one-shot device testing data. IEEE Transactions on Reliability, 66, 641-650.
Ling, M.H., Wong, S.Y., Tsui, K.L. (2017). Efficient heterogeneous sampling for stochastic simulation with an illustration in healthcare applications. Communications in Statistics – Simulation and Computation, 46, 631-639.
Shen, X.B., Wong, S.Y., Ling, M.H., Goldsman, D., Tsui, K.L. (2016). Comparison of algorithms to simulate disease transmission. Journal of Simulation, 11, 285-294.
Balakrishnan, N., So, H.Y., Ling, M.H. (2016). A Bayesian approach for one-shot device testing with exponential lifetimes under competing risks. IEEE Transactions on Reliability, 65, 469-485.
Ling, M.H., Ng, H.K.T., Chan, P.S., Balakrishnan, N. (2016). Autopsy data analysis for a series system with active redundancy under a load-sharing model. IEEE Transactions on Reliability, 65, 957-968.
Ling, M.H., So, H.Y., Balakrishnan, N. (2016). Likelihood inference under proportional hazards model for one-shot device testing. IEEE Transactions on Reliability, 65, 446-458.
Balakrishnan, N., So, H.Y., Ling, M.H. (2016). EM algorithm for one-shot device testing with competing risks under Weibull distribution. IEEE Transactions on Reliability, 65, 973-991.
Ling, M.H., Tsui, K.L., Balakrishnan, N. (2015). Accelerated degradation analysis for the quality of a system based on the gamma process. IEEE Transactions on Reliability, 64, 463-472.
Balakrishnan, N., So, H.Y., Ling, M.H. (2015). EM algorithm for one-shot device testing with competing risks under exponential distribution. Reliability Engineering & System Safety, 137, 129-140.
Balakrishnan, N., Ling, M.H. (2014). Best constant-stress accelerated life-test plans with multiple stress factors for one-shot device testing under Weibull distribution. IEEE Transactions on Reliability, 63, 944-952.
Hui Yang; Kundakcioglu, E. ; Jing Li ; Wu, T. ; Mitchell, J.R. ; Hara, A.K. ; Pavlicek, W. ; Hu, L.S. ; Silva, A.C. ; Zwart, C.M. ; Tunc, S. ; Alagoz, O. ; Burnside, E. ; Chaovalitwongse, W.A. ; Presnyakov, G. ; Cao, Y. ; Sujitnapitsatham, S. ; Daehan Won ; Madhyastha, T. ; Weaver, K.E. ; Borghesani, P.R. ; Grabowski, T.J. ; Lianjie Shu ; Man Ho Ling ; Shui-Yee Wong ; Kwok-Leung Tsui (2014). Healthcare intelligence: turning data into knowledge. IEEE Intelligent Systems, 29(3), 54-68.
Balakrishnan, N., Ling, M.H. (2014). Gamma lifetimes and one-shot device testing analysis. Reliability Engineering and System Safety, 126, 54-64.
Balakrishnan, N., Ling, M.H. (2013). Expectation maximization algorithm for one shot device accelerated life testing with Weibull lifetimes, and variable parameters over stress. IEEE Transactions on Reliability, 62, 537-551.
Balakrishnan, N., Ling, M.H. (2012). Multiple-stress model for one-shot device testing data under exponential distribution. IEEE Transactions on Reliability, 61, 809-821.
Balakrishnan, N., Ling, M.H. (2012). EM algorithm for one-shot devices testing under the exponential distribution. Computational Statistics & Data Analysis, 56, 502-509.
Shiu, W.C., Ling, M.H. (2010). Full friendly index sets of Cartesian products of two cycles. Acta Mathematica Sinica-English Series, 26, 1233-1244.
Tang, M.L., Ling, M.H., Ling, L., Tian, G.L. (2010). Confidence intervals for a difference between proportions based on paired data. Statistics in Medicine, 29, 86-96.
Tang, M.L., Ling, M.H., Tian, G.L. (2009). Exact and approximate unconditional confidence intervals for proportion difference in the presence of incomplete data. Statistics in Medicine, 28, 625-641.
Shiu, W.C., Ling, M.H., Low, R.M. (2008). The edge-graceful spectra of connected bicyclic graphs without pendant. Journal of Combinatorial Mathematics and Combinatorial Computing, 66, 171-185.


Projects

On Reliability Analysis of Return-Spring Data
In this study, I am going to explore the data of return-springs and develop inferences for the return-springs. Accelerated degradation models with random effect are possible for fitting the data.
Project Start Year: 2023, Principal Investigator(s): LING, Man Ho, Alpha
 
Bayesian Inference for Defect Rate of One-Shot Devices
This study aims to develop Bayesian inference for the defect rate of one-shot devices that can be tested only once.
Project Start Year: 2022, Principal Investigator(s): LING, Man Ho, Alpha
 
An interactive avatar toolkit: Enhancing students’ online learning engagement in higher education
The project aims to develop and implement an interactive avatar (iAvatar) toolkit aligned with: (1) a framework of five dimensions of meaningful learning with technology, (2) the iAvatar toolkit design model, and (3) engagement to create a virtual interactive learning community.
Project Start Year: 2021, Principal Investigator(s): SONG, Yanjie (LING, Man Ho, Alpha as Co-Investigator)
 
Advanced Statistical Models in Data Analysis for Reliability and Safety Assessment
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Project Start Year: 2021, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
EdU Online Class Platform (EOCP) with Community of Practice (CoP)
This project aims at strengthening the EdU Online Classes Platform, and developing quality multi-media teaching materials to support the teaching of primary and secondary schools in Hong Kong.
Project Start Year: 2020, Principal Investigator(s): TSANG, Po Keung Eric 曾寶強 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Investigating Pupils’ English Vocabulary Learning Engagement Supported by Virtual Location-based Task Tool in COVID-19
Vocabulary learning for English as a second language (ESL) learners is a boring experience in school education because learners have few opportunities to review and apply the vocabulary learned in class to real-life settings. In the COVID-19, learners have to stay at home most of the time, the opportunities for consolidating the vocabulary in authentic learning environments are even rare. In the light of it, this study aims to develop and implement a virtual location-based task tool (refer to Figure 1) to engage learners in game-based learning activities to perform location-based tasks in a virtual world, especially in COVID-19.
Project Start Year: 2020, Principal Investigator(s): SONG, Yanjie 宋燕捷 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Healthy Ageing and Well-Being among Older People and Health Study Students' Attitudes toward Older People in Macao
The overall purpose is to explore the status, relationship, and related factors between healthy ageing and wellbeing among older people in Macao.
Project Start Year: 2020, Principal Investigator(s): Dr. Hsu, Mei Hua Kerry (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Establishing a Research Cluster for Promoting Artificial Intelligence in Technology-Enhanced Language Learning (AI-TELL) Research
This project aims to propose and establish a research cluster to promote artificial intelligence in technology-enhanced language learning (hereafter, AI-TELL) research in Hong Kong. The ultimate goal of the proposed AI-TELL research cluster is to identify and bridge the gap between AI techniques and TELL towards developing pedagogical innovations to enhance language learning.
Project Start Year: 2020, Principal Investigator(s): CHENG, Kwok Shing 鄭國城 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Facilitating Artificial Intelligence and Big Data Analytics Research in Education
This project aims to develop AI in education and big data analytics in education as the departmental strategic areas. It is also planned to facilitate the development of the two areas through various related research activities, which include organizing research seminars, undertaking collaborative research, and inviting world-leading scholars for discussion and consultation
Project Start Year: 2020, Principal Investigator(s): CHENG, Kwok Shing 鄭國城 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Infuse STEM/STEAM Elements into Mathematics and Information Technology Courses
This project aims to infuse STEM/STEAM elements into our subject-based courses in Mathematics and Information Technology courses. For each learning area of the subject-based courses, a relevant exemplar will be established to integrate STEM/STEAM elements into the teaching and learning of the subject. Instructional materials for each exemplar will be designed and implemented by a team of developers in consultation with the project’s supervisors. The materials will be freely available online to the teaching staff. Students can truly integrate the rich and supportive STEM/STEAM elements in their projects.
Project Start Year: 2019, Principal Investigator(s): SO, Wing Wah, Simon (LING, Man Ho, Alpha as Co-Investigator)
 
Investigation on Estimation Methods for Weibull Distributions with a Threshold Parameter Based on One-Shot Device Testing Data
In reliability studies, as it is reasonable to assume that there is a nonzero origin below which no event can occur, Weibull distribution with an unknown location (threshold) parameter is suitable for data analysis. To the best of our knowledge, no published study has examined estimation methods for the three-parameter Weibull distributions based on binary data arising from one-shot devices collected from accelerated life tests. In this project, we will investigate three-parameter Weibull distribution with a threshold parameter and develop estimation methods for one-shot device testing data.
Project Start Year: 2019, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Enhancing Pupils’ English Vocabulary Learning in a Seamless Learning Environment Supported by an Augmented Reality App
This Departmental Collaborative Research Fund project aims to develop an AR app to help learners learn vocabulary in an immersive and seamless learning environment, allow them to generate their own vocabulary learning content, increase their interaction with real objects without time and place constraints, provide opportunities for retention of the target vocabulary with the combination of picture and text media, and document their learning trails for pedagogical decision making via learning analytics.
Project Start Year: 2019, Principal Investigator(s): SONG, Yanjie 宋燕捷 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Enhancing Students’ Mathematics Learning through Instructional STEM Activities with Mathematical Modeling
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Project Start Year: 2019, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Developing Item Response Models with Copula Models for Data with Local Item Dependence
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Project Start Year: 2019, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Investigating the Essential Components of Mathematical Modeling as a Bridge to Cross Disciplinary STEM Integration in Mathematics Teachers' Education
We are inspired by the research report of Cai, et al (2014) on calling for research on learning and teaching of mathematical modeling in the three out of five perspectives, namely: mathematics, instructional, and teacher education. In this study, we measure how competent prospective, or fresh mathematics teachers are in certain areas of mathematics subject matter knowledge (SMK) and pedagogical content knowledge (PCK), which are decisive for quality teaching, while their knowledge of mathematical modeling will be our main focus. It is believed that effective teaching of mathematical modeling, requires at least the teachers’ capability of making real connection, using authentic approaches, applying appropriate metaphors, leading smooth transition of abstraction in delivery mathematical concepts and ideas, looking at elementary content from an advance standpoint, and skillful validation and verification of built models (Blum 2011). The knowledge of teaching of mathematical modeling is believed to be an essential component of effective teaching of mathematics in the STEM environment (Kertil & Gurel 2016).
Project Start Year: 2019, Principal Investigator(s): LEUNG KUI CHIU, ISSIC 梁鉅超 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Automatic Assessment Score Analysis
The project creates Automatic Assessment Score Analysis (AASA) software to analyze properly scores of test questions, essays, etc. AASA requires zero statistics/computer knowledge and uses teachers’ existing data on their students’ scores. AASA applies cutting-edge statistics to assess students accurately and produce an easy-to-understand report that (a) sorts students (lowest to highest learning outcomes), (b) sorts questions from easiest to hardest (poorly- to well-understood ideas), and (c) suggests removal of poor questions (easily guessed, misleading, etc.).
Project Start Year: 2019, Principal Investigator(s): CHIU, Ming Ming (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
On the Use of Copulas in One-Shot Device Testing Data with Multiple Failure Modes
Due to an increasing demand for appropriate probabilistic models for analyzing one-shot device data with multiple failure modes collected from accelerated life-tests, it is of great interest to develop copula models that can capture the association among the failure modes and provide more accurate reliability estimation under normal operating conditions.
Project Start Year: 2018, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Development of E-learning Package to Enhance Learning and Teaching Probability and Statistics
Innovative digital learning objects will be developed with a powerful statistical tool, R, and an appropriate curriculum will be designed in this project, to facilitate teaching and learning of probability distributions.
Project Start Year: 2018, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪, YEE, Tat Leung 余達良, CHEUNG, Ka Luen 張家麟
 
A Study of Online Evidence-based Assessment System to Promote Collaborative and Cooperative Learning in Group Activities
Many courses involve group projects and/or activities to let students to collaborate and work together to solve problems. However, it is not easy to ensure all students are actively contributed and collaborate with each other to complete the project. As teachers usually collect the final outcome and mark it as a whole, it is difficult to assess the group project fairly within a group if the workload is unevenly distributed. In this project, we proposed to use “An Online Evidence-based Assessment System” as a centralized platform for students to carry out group activities such as discussion, initiating activities, sharing resources, providing feedback and solution, etc. The proposed system will keep track of the progress of individuals within a group, and the best member and best group will be selected every week and showed on their main page as a compliment. Detailed reports will be generated for both students and teachers. Students will receive a regular report to show their current progress, such as the number of posts, replies, completed tasks, interaction degree with other members, etc., to promote active engagement and collaborative learning. Whereas teachers will receive activity log of all students in the class, which could be used to set assessment criteria and identify free-riders. We have invited six teachers to deliver group projects and/or activities with our pilot platform. To study the effect of this online evidence-based assessment approach on students and teachers in higher education, quantitative data will be analyzed by data mining modeling techniques to discover interesting learning patterns.
Project Start Year: 2018, Principal Investigator(s): LAM, Wai Man Winnie 林惠民 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Investment Pattern and Performance of Mandatory Provident Fund Scheme Members: A Historical Administrative Record Analysis
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Project Start Year: 2016, Principal Investigator(s): CHOU, Kee Lee 周基利 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems
The project aims to extend the advantage of Hong Kong by establishing it as a center of expertise in the safety, reliability, and efficient management of complex networking systems.
Project Start Year: 2016, Principal Investigator(s): TSUI, Kwok Leung (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Good Teaching Practice – Incorporation of Development of Generic Skills into Course Teaching at Higher Education Context
The present project is related to Community of Practice (CoP). It aims to promote good teaching practice with the focus of incorporating the generic intended learning outcomes (GILOs) in course teaching and develop a peer sharing atmosphere on campus. It engages our colleagues in sharing and exchanging their teaching experience through an online platform.
Project Start Year: 2015, Principal Investigator(s): CHENG, May Hung May 鄭美紅 (LING, Man Ho Alpha 凌萬豪 as Team Member)
 
Advanced Statistical Models for Accelerated Life Testing Data of One-Shot Devices
The objective of this research is to accurately demonstrate the reliability characteristics of one-shot devices from data collected from accelerated life testing.
Project Start Year: 2015, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
故障预测和系统健康管理的贝叶斯推断 (Bayesian Inference for Prognostics and System Health Management)
This project is concerned with some fundamental issues of statistical analysis for remaining useful life estimation for prognostics and system health management (PHM). Due to sophisticated modeling of high reliable components and systems, classical approach may fail or become difficult for making inference on remaining useful life. The main objective of this project is to make Bayesian inference for complicated models in PHM that classical approach is difficult for implementation.
Project Start Year: 2015, Principal Investigator(s): TSUI, Kwok Leung (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Developing and Evaluating a Learning Analytics Platform to Support University Teachers for Pedagogical Decision-making in Fostering Reflective Engagement of Students
The project aims to develop a learning analytics platform conducive to data-oriented decision-making; to evaluate the impact of a learning analytics platform on facilitating reflective engagement of students in the learning process; and to evaluate the impact of a learning analytics platform on teachers’ pedagogical decision making. The expected outcomes include a deliverable learning analytics platform, which can help teachers gain a better understanding of students’ learning process, and identify learning issues to predict learning patterns and make corresponding pedagogical decision-making; a higher quality learning-teaching process, which will provide flexible teaching and learning environments where students can control their own learning; the platform will also segregate the learning objects into appropriate segments so as to address the needs of students with different learning styles; a higher degree of engagement in learning with reflection, which will enable students to engage in learning with reflective thinking associated with personal experience and social issues and interact with peers and teachers anytime, anywhere; and a transformation of teachers’ traditional pedagogical practices of summative assessment into formative assessment, which will enable teachers to give students assessment that corresponds to their learning performance (i.e. through statistical report on students’ responses on online quizzes) throughout the learning process. With various tasks and discussions throughout a course, apart from being able to give quality feedback to students, teachers will also have a clear understanding of what students know and do not know during the learning process instead of at the end of a unit of instruction. A deliverable learning analytics platform, pilot test reports, the establishment of a community of practice, analysis of evaluation data and guidelines on the use of the platform are the expected key deliverables of the project. The project dissemination activities include three teacher professional development programs for reporting the design and implementation of the learning analytics platform in the proposed project, two presentations for reporting the development and implementation status of the learning analytics platform and two conference presentations for disseminating the effects of a learning analytics platform on supporting university teachers for pedagogical decision-making in fostering reflective engagement of students.
Project Start Year: 2014, Principal Investigator(s): KONG, Siu Cheung 江紹祥, SONG, Yanjie 宋燕捷, POON, Kin Man 潘建文 (LING, Man Ho Alpha 凌萬豪 as Co-Investigator)
 
Statistical inference on system reliability with redundancy
This project is to develop statistical methods to estimate the reliability of system with redundancy
Project Start Year: 2014, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Semi-parametric inference for one-shot device testing data
The main purpose of this research is to develop semi-parametric models that help engineers and scientists to analyze one-shot device testing data collected from accelerated life testing.
Project Start Year: 2014, Principal Investigator(s): LING, Man Ho Alpha 凌萬豪
 
Prizes and awards

VocabGo app: "Gold Medal" (2021)

Date of receipt: /8/2021, Conferred by: The International Invention Innovation Competition in Canada (iCAN) 2021
 
Impact Case Study Prize

Date of receipt: 2/8/2021, Conferred by: The Education University of Hong Kong
 
VocabGo app: "Gold Medal"

Date of receipt: 16/11/2020, Conferred by: International Innovation and Invention Competition (IIIC) Taiwan 2020
 
Silver Medal
In iCAN 2019, EdUHK showcased four edtech innovations and the GMoodle system for assessment automation has been awarded with two prizes: silver medal and special award. The GMoodle system is developed for assessment of collaborative learning. The whole process of collaboration is recorded by the system to provide an objective measure and fair evaluation to reflect the actual contribution of each student in a group project.
Date of receipt: 24/8/2019, Conferred by: The International Invention Innovation Competition in Canada (iCAN) 2019
 
Special Inventor Award
In iCAN 2019, EdUHK showcased four edtech innovations and the GMoodle system for assessment automation has been awarded with two prizes: silver medal and special award. The GMoodle system is developed for assessment of collaborative learning. The whole process of collaboration is recorded by the system to provide an objective measure and fair evaluation to reflect the actual contribution of each student in a group project.
Date of receipt: 24/8/2019, Conferred by: The International Invention Innovation Competition in Canada (iCAN) 2019
 
Research Output Prize

Date of receipt: 14/3/2017, Conferred by: The Education University of Hong Kong