Foto del docente

Ghulam Mustafa

PhD Student

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems

Curriculum vitae

Download Curriculum Vitae (.pdf 97KB )

EDUCATION

University of Bologna, ItalyPhD in Computer Science and Engineering
November 2024 – Present
Advisor: Prof. Dr. Claudio Sartori

Sun Moon University, South KoreaM.S. in Computer and Electronics Convergence Engineering
March 2022 – December 2023
Advisor: Prof. Dr. Youngsup Hwang
Thesis: Bus Travel Time Prediction in Cheonan City Using Deep Learning with DTG Data

Karabük University, TurkeyDepartment of Computer Engineering (Exchange Program)
February 2020 – July 2020

Quaid-e-Awam University of Engineering, Science & Technology, PakistanB.S. in Computer Science
January 2017 – January 2021
Thesis: Application of Drone Surveillance for Advanced Agriculture Monitoring Using CNN


EXPERIENCE


Lecturer, Department of Artificial Intelligence and Multimedia Gaming
Aror University of Art, Architecture, Design & Heritage, Sindh, Pakistan
August 2024 – Present

Teaching Assistant, Computer Science
Institute of Science and Technology, Nawabshah, Sindh, Pakistan
January 2021 – January 2022


RESEARCH PROJECTS


1: Prediction of Bus Travel Time in Cheonan City Using Deep Learning with DTG Data
Sun Moon University & Dankook University, South Korea
March 2022 – December 2023
Developed a bus travel time prediction algorithm using digital tachograph data (DTG) in Cheonan, South Korea.

Hybrid ConvLSTM with Attention for Precise Driver Behavior Classification
Sun Moon University & Dankook University, South Korea
March 2022 – December 2023
Designed the HCLA-DBC model combining CNN, LSTM, and Attention layers to classify driver behavior.

TrafficNet: A Hybrid CNN-FNN Model for Traffic Accident Analysis in Seoul
Sun Moon University & Dankook University, South Korea
March 2022 – December 2023
Analyzed traffic accidents in Seoul using deep learning techniques.

Application of Drone Surveillance for Advanced Agriculture Monitoring Using CNN
Quaid-e-Awam University of Engineering, Science and Technology, Pakistan
January 2019 – December 2019
Used drone surveillance and deep learning for the detection of plant diseases.

TECHNICAL AND DIGITAL SKILLS

  1. Languages: Python, C++, C, Java, JavaScript
  2. Database: MySQL, SQLite, Firebase
  3. Software and Tools: Google Earth Pro, PyCity, NetworkX, SUMO (Simulation of Urban Mobility), Jupyter Notebook

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