Assoc Prof Dr. Harco Leslie Hendric Spits Warnars

Harco Leslie Hendric Spits Warnars is Head of Concentration of Information Systems at Doctor of Computer Science (DCS) Bina Nusantara University ( and supervisor some Ph.D. students in Computer Science. He did Bachelor's degree in Computer Science in the Information Systems field from STMIK Budi Luhur (, Jakarta Selatan, Indonesia with title S.Kom (Sarjana Komputer) between 1991-1995 with a bachelor thesis topic about information systems using Budi Luhur scholarship. Between 2004-2006 he continued his Master's degree in Computer Science with major field Information Technology in University Indonesia, with degree title M.T.I. (Magister Teknologi Informasi) ( with master thesis topic about Datawarehouse which was funded by Budi Luhur university. His Ph.D. Computer Science was done at The Manchester Metropolitan University, Manchester, United Kingdom (, with a Ph.D. Thesis topic about Data Mining between 2008-2012.

He had been awarded some research grants such as Program of research incentive of national innovation system (SINAS) from the Ministry of Research, Technology and Higher Education of the Republic of Indonesia and Incentives article in the International Journal from the directorate of research and community service, Ministry of Research, Technology and Higher Education of the Republic of Indonesia. He is a member of some professional membership such as IEEE (Institute of Electrical and Electronics Engineers) since 2011, member number: 92305834, (, SDIWC ( The Society of Digital Information and Wireless Communication) member ID:3518 since March 2014, (, IAENG (International Association of Engineers) member number: 140849 since April 2014, (, IACSIT (International Association of Computer Science and Information Technology) senior member since Jan 2014, (, INSTICC (the Institute for Systems and Technologies of Information, Control and Communication) member number 5279 since June 2014, ( He is active as a reviewer/program committee for some International journals or conferences and active as general chair, program chair, the general committee for some international conferences, active as the advisory and editorial board for 6 journals. His review activities can be seen at He had success running as general chair for 2 international conferences such as 2017 cyberneticsCOM ( ), 2018 Indonesian Association for Pattern Recognition International (INAPR) conference ( ). Technical Program Chairs for 2019 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) (

Title: Towards Human-Centered AI through Unstructured Data Text Representation
Date: 13 Sept 2021.
Time: 9.00am to 10.30am (MYT GMT +8)

Descriptions: Humans when interacting with computers will use the User Interface (UI) as a communication medium. At the end of the day, this communication will use data in the form of structured and unstructured data, both as input and output. The use of unstructured data text in Human-Computer Interaction (HCI) can be divided into two, namely the interaction between humans and computers, and interactions between humans when using computers or applications. Interactions between humans and computers that produce unstructured data text are carried out using feedback or reviews where humans can provide feedback or review on a product or service. Meanwhile, interactions between humans while using computers or applications produce unstructured data text which is carried out using forums or discussion.

To enhance the element of HCI the unstructured data text is processed using Artificial Intelligence (AI). For example, the use of other unstructured data types such as voice will further enhance human-centered AI where voice to text and/or text to voice Application Programming Interface (API) can easily be implemented to transfer unstructured data voice to unstructured data text. Another example, the AI technology will be applied with certain algorithms either using datasets from forum/discussion or feedback/review. Through human-centered AI, the systems with unstructured data text can understand human language, emotion, and behavior using AI technology such as recommender system, sentiment analysis, topic classification/analysis, and dialogue system/conversational agent/chatbot.

This workshop is expected to provide a broad and in-depth understanding of the implementation of AI technology using unstructured text data. It is hoped that the application of AI technology that uses unstructured text data is expected to increase the benefits of human-centered AI. This workshop is perfect for academics, industry practitioners, and students who are interested in understanding human-centered AI implementation using unstructured text data. In addition, this workshop will be of benefit to masters or Ph.D. students who are looking for a research topic and interested in the topic of human-centered AI where AI is applied to improve interactions between humans and computers.