Wern Han Lim (Ian) has been teaching computer science with the School of Information Technology since 2015; achieving teaching recognition from student association, school, faculty and campus such as: - 2020 PVC Awards for Excellence in Education: Outstanding Educator - 2019 Faculty of Information Technology Teaching Award: Teaching Excellence - 2018 Monash Student Association (MSA) Teaching Awards - Faculty Teaching Excellence Award: Information Technology. - 2017 Faculty of Information Technology Teaching Award 2017: Citation for Outstanding Contribution to Student Learning. His teaching experience includes: - FIT1008 Introduction to Computer Science - FIT2004 Algorithms and Data Structures - FIT2014 Theory of Computation - FIT3140 Advanced Programming - FIT3152 Data Science - FIT3155 Advanced Data Structures and Algorithms Ian is also the student experience coordinator for the school. He often initiate, coordinates and act as the advisor for student enhancement programs -- having mentored student teams successfully in various local, regional and international events particularly hackathons and datathons. Besides that, he also contributes to community outreach programs such as the Campus Community Engagement (CCE) as one of the academic advisors. On the research front, Ian’s area of interest and expertise includes (not limited to): - Information Retrieval (IR) and Knowledge Discovery particularly on User-Generated Content (UGC) platforms. His work in this area also includes Natural Language Processing (NLP), Data Science (DS) and Machine Learning (ML). - Graph Algorithms for a wide range of use cases such as knowledge graph, social engineering and flow optimization with capacity constraint. To date, he has been involved in a number of research projects in these research areas including postgraduate supervision, industry collaborations and industry consultancy.

Ian has a strong research interest to bring order to the World Wide Web (WWW) today – estimating the reliability and information quality of User-Generated Content (UGC). He aims to enhance the information retrieval (IR) experience on the WWW, leveraging the Wisdom of the Crowd (WotC). To do so, he utilizes various data science techniques in conjunction with machine learning (ML) to produce powerful models such as:

• Classification of WWW resources using user annotations/ tags.
• Identifying experts on community question-answering (CQA) platforms and reliable product reviewers for improved recommender systems.
• Prediction of best answer in a CQA environment.
• Identifying high quality comments on Reddit and filtering out unwanted comments/ fake news.
• Identifying malicious users/ spammers on various UGC platforms including fake news.
• Extraction of tacit knowledge from UGC platforms, towards enhancing existing knowledge graphs.

Besides that, he also work on other areas such as:

• Analytics and design of novel flow networks (humans and vehicles) for route optimization with capacity constraints and a wide range of use cases.

• FIT1008 Introduction to Computer Science
• FIT2004 Algorithms and Data Structures
• FIT2014 Theory of Computations
• FIT3152 Data Science
• FIT3155 Advanced Data Structures and Algorithms

As a student experience coordinator, Ian as been a part of various community services involving SoIT students such as:

• The Campus Community Engagement (CCE) program with NGOs such as Tzu Chi.
• Deloitte-Monash KidsEdu initiative to provide computing devices for children education.

He also contribute his expertise as for the research into the primary care for the elderly with the Institute of Health System Research (IHSR) of the Malaysia National Institute of Health (NIH).

Ian has provided his services both paid and unpaid to the following:

• MIMOS Berhad, the Malaysia National Applied R&D Centre.
• Institute for Health System Research (IHSR), for the Malaysia National Institute of Health (NIH).