January 11, 2016: Invited Speaker Seminar: Recommender Systems in Future Intelligence

Kaveh Bakhtiyari

Monday, January 11 at 4:00 p.m.
Room EV003.309

Abstract

Recommender Systems (RS or RecSys) seek to produce a list of recommendations by predicting the rating and/or the preference of an item given by a specific user or group. They initially became popular in online shopping websites, and they have been rapidly expanded into many various applications from entertainment industries to business. Recommender Systems is a new research area which is coined in 1995, and it attracted many researchers and scientists which resulted in the growth of nearly 4 times in research papers only in the last 10 years. This seminar talks about the current status of RS in different categories: 1) The well-known methodologies and algorithms which are being used in RS, 2) The potential challenges (research potentials) which are being investigated, 3) Novel methodologies and discussions (e.g. integration with Affective Computing), and 4) The future of RS..

Biography

Kaveh Bakhtiyari obtained his bachelor degree in Computer Engineering in 2009, and Master of IT - Artificial Intelligence from The National University of Malaysia in 2012. He is currently doing two PhDs in System Engineering and Computer Cognitive Science at University of Duisburg-Essen (Germany) and The National University of Malaysia. He has published many research papers with international collaboration in more than 6 countries. His main research areas are Recommender Systems, Human Interruptability Measurements and Affective Computing. He founded MUSINGWAY Ltd. in 2005 as the high-tech intelligent service provider. He has been awarded the DAAD International Doctoral Scholarship in 2015 in Germany, Samsung Gear Challenge in 2014 in South Korea, UKM Research Fellowship in 2013, and top researcher student in 4 sequential years during his bachelor education.