Mr Syed Irteza Hussain Jafri

Lecturer (P.hD.)

Mr Syed Irteza Hussain Jafri

Lecturer (P.hD.)

Research Area: AI, Machine Learning, Deep Learning, Automation, IOT
About Me

PhD Scholar at UTHM, Malaysia

Degree Major University Start Date End Date
P.hD. Computer Science UTHM, Malaysia October 2020 November 2024
MS Software Engineering Bahria University Islamabad January 2009 January 2011
BS (Computer Science) Computer Science University of Azad Jammu & Kashmir, Muzaffarabad January 2002 January 2006
Designation Organization Duration
Lecturer The University of Poonch, Rawalakot March 2014 - November -0001
Sr. S/W Eng. EVS (E-Vision) Software Islamabad February 2009 - August 2010
PHP Web-Developer Artologics Software Islamabad September 2007 - February 2009
Project Manager, Team Leader CyberVision, International Islamabad March 2007 - March 2014
Title Description Sponsoring Agency Amount Year
Designation Department Organization From Date To Date
Ph.D. Scholar Faculty of Computer Science and Information Technology UTHM, Malaysia October, 2020
Lecturer Computer Science and Information Technology University of Poonch, Rawalakot March, 2014
Description Year Journal Name Impact Factor
Irfan Javid, Irteza Syed, Rozaida Ghazali Municipal Solid Waste Generation Forecast using an ARIMA and XGBoost Model Municipal Solid Waste Generation Forecast using an ARIMA and XGBoost Model - ICICCT 2023 2023
Syed Irteza Hussain Jafri, Rozaida Ghazali, Irfan Javid Deep transfer learning with multimodal embedding to tackle cold-start and sparsity issues in recommendation system Deep transfer learning with multimodal embedding to tackle cold-start and sparsity issues in recommendation system 2022
Irfan Javid, Irteza Syed, Rozaida Ghazali Developing Novel T-Swish Activation Function in Deep Learning Conference: 2022 International Conference on IT and Industrial Technologies (ICIT) · Oct 15, 2022 2022
Irfan Javid, Irteza Syed, Rozaida Ghazali Study on the Pakistan stock market using a new stock crisis prediction method Study on the Pakistan stock market using a new stock crisis prediction method - PLOS ONE · Oct 20, 2022 2022