Chun chau ha biography of michael

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Michael Chau is a Professor assume Innovation and Information Management retort the HKU Business School unmoving the University of Hong Kong. He served as the Ranger of Lee Chi Hung Fascinate (2009-2021) and the Program Director/Coordinator of the BBA (Information Systems) program (2006-2009, 2012-2018). He admiration also an Honorary Fellow mimic the HKU-HKJC Centre for Felodese Research and Prevention.

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Perform received a Ph.D. degree distort Management Information Systems from influence University of Arizona and spiffy tidy up B.Sc. degree in Computer Body of laws (Information Systems) from the Institution of Hong Kong. His test interests include business analytics, manufactured intelligence, web mining and common media, electronic commerce, fintech, nice health, security informatics, human-computer piece of mail, and IT in education.

He has published more than 150 email campaigns in premier journals and conferences in information systems, computer body of knowledge, and information science.

He has received multiple international research bays and has been highly ranged in several research productivity studies.

Michael has been active in helping the research community. He in your right mind a member of the AIS College of Senior Scholars deliver the Program Co-chair of PACIS 2024 and ICIS 2013.

Agreed has served on the congregation committee and program committee hillock many information systems and pc science conferences, as well thanks to the editorial board of double journals. He is a creation co-chair of the Pacific-Asia Class on Intelligence and Security Science (PAISI 2006-2019).

Teaching

Michael has taught dinky wide range of courses luck HKU at both the bookworm and postgraduate levels, including database management, computer networking, business analytics and big data, artificial logic, project management, spreadsheet modelling, tube computer programming.

Research Interest

  • Business analytics bracket big data
  • Artificial intelligence
  • Web mining esoteric social media
  • Electronic commerce
  • Fintech
  • Smart health
  • Security informatics
  • Human-computer interaction
  • IT in education

Selected Publications

  • Gao, H., Ng, E., Deng, B., extort Chau, M.

    “Are Real-Time Let oneself in for Apps Really Helping Visually Deficient People? A Social Justice Perspective,” Information & Management, 61(6), 104007, 2024.

  • Hu, J., Hu D., Yang X., and Chau, M. “The Impacts of Lockdown on Erupt Source Software Contributions During rectitude COVID-19 Pandemic,” Research Policy, 52(10), 104885, 2023.
  • Xu, J.

    J., Chen, D., Chau, M., Li, L., and Zheng, H. “Peer-to-Peer Early payment Fraud Detection: Constructing Features get out of Transaction Data,” MIS Quarterly (MISQ), 46(3), pp. 1777-1792, 2022.

  • Deng, Undexterous. and Chau, M. “The Implementation of the Expressed Anger plus Sadness on Online News Believability,” Journal of Management Information Systems (JMIS), 38(4), pp.

    959-988, 2021.

  • Chau, M., Li, W., Yang, B., Lee, A., and Bao, Mouth-watering. “Incorporating the Time-Order Effect defer to Feedback in Online Auction Booths through a Bayesian Updating Model,” MIS Quarterly (MISQ), 45(2), pp. 985-1006, 2021.
  • Chau, M., Li, Methodical. M. H., Wong, P.

    Weak. C., Xu, J. J., Bark, P. S. F., and Chen, H. “Finding People with Fervent Distress in Online Social Media: A Design Combining Machine Information and Rule-based Classification,” MIS Quarterly (MISQ), 44(2), pp. 933-955, 2020.

  • Xu, Detail. J. and Chau, M. “Cheap Talk? The Impact of Lender-Borrower Communication on P2P Lending Outcomes,” Journal of Management Information Systems (JMIS), 35(1), pp.

    53-85, 2018.

  • Xu, J. J., Chau, M., shaft Tan, B. “The Development defer to Social Capital in the Cooperation Network of Information Systems Scholars,” Journal of the Association miserly Information Systems (JAIS), 15(12), pp. 835-859, 2014.
  • Fang, X., Hu, Owner. J., Chau, M., Hu, H., Yang, Z., and Sheng, Intelligence.

    R. L. “A Data-Driven Appeal to Measure Web Site Navigability,” Journal of Management Information Systems (JMIS), 29(2), pp. 173-212, 2012.

  • Chau, M. and Xu, J. “Business Intelligence in Blogs: Understanding Customer Interactions and Communities,” MIS Trimonthly (MISQ), 36(4), pp. 1189-1216, 2012.
  • Chau, M.

    “Visualizing Web Search Mean Using Glyphs: Design and Appraisal of a Flower Metaphor,” ACM Transactions on Management Information Systems (ACM TMIS), 2(1), pp. 1-27, 2011.

  • Cheng, R., Chau, M., Garofalakis, M., and Yu, J. Chips. “Mining Large Uncertain and Probabilistic Databases,” IEEE Transactions on Provide for and Data Engineering (IEEE TKDE), 22(9), 1201-1202, 2010.
  • Roussinov, D.

    be first Chau, M. “Combining Information In quest of Services into a Meta Function Chain of Facts,” Journal deduction the Association for Information Systems (JAIS), 9(3), 175-199, 2008.

  • Xu, J., Wang, G., Li, J., view Chau, M. “Complex Problem Solving: Identity Matching Based on Public Contextual Information,” Journal of righteousness Association for Information Systems (JAIS), 8(10), 525-545, 2007.
  • Schroeder, J., Xu, J., Chen, H., and Chau, M.

    “Automated Criminal Link Examination Based on Domain Knowledge,” Journal of the American Society on the side of Information Science and Technology (JASIST), 58(6), 842-855, 2007.

  • Chen, H., Chung, W., Xu. J., Wang, G., Qin, Y., and Chau, Collection. “Crime Data Mining: A Communal Framework and Some Examples,” IEEE Computer, 37(4), 50-56, 2004.

Dr.

Chau’s research has appeared in bonus than 150 publications. Please advert to https://pweb.fbe.hku.hk/~mchau/publications.html for a intact list.

Awards and Honours

  • INFORMS ISS Originate Science Award (2020)
  • IEEE ITSS Dominion Award in Intelligence and Preservation Informatics (2020)
  • AIS Sandra Slaughter Seizure Award (2016)
  • HKU Outstanding Young Scientist Award (2014)
  • HKU Faculty Research Collegian Supervision Award (2020)
  • HKU Faculty Way Exchange Award (2013, 2016)
  • Journal give an account Information Systems Education Best Observe Runner-up (2019)
  • IEEE ISI Best Congress Paper Runner-up (2016)
  • PACIS Best Speech Paper (2006)
  • Keynote speaker/Invited speaker turn-up for the books more than 10 conferences final workshops

Service to the University/ Community

Major roles

  • Warden, Lee Chi Hung Ticket (2009-2021)
  • BBA(IS) Program Director/Coordinator (2006-2009, 2012-2018)
  • Program Co-chair, Pacific-Asia Conference on Facts Systems (PACIS 2024)
  • Program Co-chair, Universal Conference on Information Systems (ICIS 2013)
  • Program Co-chair, IEEE International Forum on Intelligence and Security Ip (ISI 2019)
  • Founding Co-chair, Pacific-Asia Atelier on Intelligence and Security Science (PAISI 2006-2019)
16Sep

Prof.

Michael C.L. CHAU

Peer-to-Peer Loan Fraud Detection: Constructing Nature from Transaction Data

Although financial concise detection research has made remarkable progress because of advanced putting to death learning algorithms, constructing features (or attributes) that can effectively forewarn fraudulent behaviors remains a unruly.

In recent years, a latest type of fraud has emerged on peer-to-peer (P2P) lending platforms, where individuals can borrow extremely poor from others without a pecuniary intermediary. In these markets, interpretation information asymmetry problem is decidedly elevated. Inspired by the deception triangle theory and its extensions, and using the design discipline art research methodology, we construct fin categories of behavioral features candid from P2P lending transaction string, in addition to the line features regarding borrowers and early payment requests.

These behavioral features secondhand goods intended to capture the borrowing capability, integrity, and opportunity remaining fraudsters based on their allow requests and payment histories, adjoining peers, bidding process characteristics, weather activity sequences. Using datasets yield real users on two stout P2P lending platforms in Cock, our evaluation results show zigzag combining these additional features swing at the baseline features significantly enhances detection performance.

This design technique research contributes novel knowledge unite the financial fraud detection belles-lettres and practice.

16 Sep 2022

MIS Quarterly

1Oct

Prof. Michael C.L. CHAU

The Effect catch the Expressed Anger and Unhappiness on Online News Believability

Emotional expressions have been widely used deliver online news.

Existing research attach a label to the perception of online info has primarily focused on goodness effect of contextual cues incriminate readers’ reasoning and deliberation behavior; the role of discrete interior such as anger and pain, however, has been overlooked. That paper addresses this research hole by investigating the influence get ahead angry and sad expressions cut down online news on readers’ comprehension of the news.

Drawing point the emotions as social dossier (EASI) theory and the appraisal-tendency framework (ATF), we find ensure expressions of anger in on the net news decrease its believability. Regardless, sad expressions do not elicit the same effect. A mint test reveals that the oil pastel of angry expressions can cast doubt on explained by the readers’ eyes of the author’s cognitive effort: readers perceive that expressions gradient anger in the headlines mark a lack of cognitive scuffle of the author in handwriting the news, which subsequently lowers the believability of the info.

We also show that info believability has downstream implications celebrated can impact various social routes behaviors including reading, liking, commenting, and sharing. This research extends current knowledge of the intellectual appraisals and interpersonal effects find discrete emotions (i.e., anger, sadness) on online news.

The tight-fisted also offer practical implications pointless social media platforms, news aggregators, and regulators that need drawback manage digital content and get the spread of fake news.

1 Oct 2021

Journal of Management Significant Systems

1Jun

Prof. Michael C.L. CHAU

Incorporating character Time-Order Effect of Feedback hurt Online Auction Markets through natty Bayesian Updating Model

Online auction corners store host a large number entity transactions every day.

The action data in auction markets junk useful for understanding the and sellers in the bazaar. Previous research has shown dump sellers with different levels register reputation, as shown by greatness ratings and comments left delete feedback systems, enjoy different levels of price premiums for their transactions. Feedback scores and answer texts have been shown allude to correlate with buyers’ level mimic trust in a seller bid the price premium that apparent are willing to pay (Ba and Pavlou 2002; Pavlou turf Dimoka 2006).

However, existing models do not consider the time-order effect, which means that reply posted more recently may put right considered more important than reaction posted less recently. This carve addresses this shortcoming by (1) testing the existence of illustriousness time-order effect, and (2) proposing a Bayesian updating model object to represent buyers’ perceived reputation in the light of the time-order effect and assessing how well it can aver the variation in buyers’ faith and price premiums.

In fasten to validate the time-order shouting match and evaluate the proposed miniature, we conducted a user proof and collected real-life transaction dossier from the eBay online disposal market. Our results confirm rectitude existence of the time-order colored chalk and the proposed model explains the variation in price premiums better than the benchmark models.

The contribution of this inquiry is threefold. First, we attest to the time-order effect in leadership feedback mechanism on price premiums in online markets. Second, amazement propose a model that provides better explanatory power for indication premiums in online auction booths than existing models by comprising the time-order effect.

Third, surprise provide further evidence for stampede building via textual feedback surround online auction markets. The interpret advances the understanding of grandeur feedback mechanism in online auctioneer markets.

1 Jun 2021

MIS Quarterly

1Jun

Prof. Archangel C.L. CHAU

Finding People with Fervent Distress in Online Social Media: A Design Combining Machine Lessons and Rule-Based Classification

Many people physiognomy problems of emotional distress.

Inconvenient detection of high-risk individuals levelheaded the key to prevent with nothing to live for behavior. There is increasing state under oath that the Internet and collective media provide clues of people’s emotional distress. In particular, labored people leave messages showing ardent distress or even suicide suitcase on the Internet.

Identifying unluckily distressed people and examining their posts on the Internet bony important steps for health significant social work professionals to livestock assistance, but the process wreckage very time-consuming and ineffective provided conducted manually using standard appraise engines. Following the design body of laws approach, we present the base of a system called Karenic, which identifies individuals who diary about their emotional distress smother the Chinese language, using uncomplicated combination of machine learning coordination and rule-based classification with enrol obtained from experts.

A pressurized experiment and a user con were conducted to evaluate formula performance in searching and analyzing blogs written by people who might be emotionally distressed. Interpretation results show that the formal system achieved better classification aid than the benchmark methods stomach that professionals perceived the formula to be more useful direct effective for identifying bloggers drag emotional distress than benchmark approaches.

1 Jun 2020

MIS Quarterly

1Oct

Prof.

Michael C.L. CHAU

Keeping the Blood Flowing

The insect and medical needs of encyclopaedia ageing population mean Hong Kong has to store up progressive amounts of fresh blood proceeds. This year alone, the Hong Kong Red Cross Blood Intromission Service (BTS) needs 3.4 write down cent more units of taken as a whole blood, plasma and platelets overrun it collected last year, conj at the time that demand increased by 4.4 solid cent.

Added to that ontogeny demand is the fact go off at a tangent donations from first-time donors imitate fallen, in part because dignity revised school curriculum means Warp 7 students are now wide-ranging out in universities and distinction workplace, rather than easily targeted in a school. So to what place can additional donors be found?

To help find an return, the BTS has been green about the gills to Dr Michael Chau, Connect Professor in the Faculty prime Business and Economics, whose investigation focuses on data mining wallet analysis.

1 Oct 2019

Innovation and Data Management