Home > Events > CLIP Colloquium: Ashad Kabir (Charles Sturt U)

CLIP Colloquium: Ashad Kabir (Charles Sturt U)

Time: 
Wednesday, November 13, 2019 - 11:00 AM to 12:00 PM
Location: 
5105 Brendan Iribe Center

 

Smart Mobile Apps for Wellbeing: Challenges and Opportunities

Abstract: In this talk, potential research challenges and opportunities in developing smart mobile applications, and a novel framework to address some of those challenges will be presented. The framework includes an approach to model, represent, reason about, and manage different types of social context, and a platform for acquiring, storing, provisioning and managing social context information to aid the development of socially-aware mobile applications. A few other current research projects will also be discussed to explore potential research collaborations and joint research funding applications.

Ashad Kabir is the Deputy Leader of Data Mining Research Group and a Lecturer in Computer Science at Charles Sturt University, Australia. He received his PhD in Software Engineering from Swinburne University of Technology, Australia. He has more than 15 years of teaching and research experience in a number of universities including Nanyang Technological University (Singapore), Deakin University (Australia), Swinburne University (Australia), University of Nantes (France), Pusan National University (South Korea), University of Chittagong (Bangladesh) and Chittagong University of Engineering and Technology (Bangladesh). Over the years, Dr Kabir has been involved in a number of projects from different industries/institutions, including Rolls-Royce (Singapore), Samsung (South Korea), Computer Associate (Australia), AutoCRC (Australia) and INRIA (France). Dr Kabir has been invited to visit the University of Toronto, Canada, Texas A&M University, USA, Auckland University of Technology, New Zealand, King Abdul Aziz University, KSA and Chandigarh University, India as a guest speaker. His research interests include mobile data mining, social context awareness, data/software behavior mining, smart mobile applications, user-centric privacy and human computer interaction.