Shaik Salman, Industrial Doctoral Student

E-mail:
shaik.salman@se.abb.com
Division:
Division of Networked and Embedded Systems
Research group:
Complex Real-Time Embedded Systems


My research includes: (1) Methods, tools and mechanisms for development of real-time applications capable of running in a fog environment, and (2) resource efficient execution of industrial robotics applications on parallel and heterogenous computing resources.

[Show all publications]

Latest publications:

Deep Neural Network for Indoor Positioning Based on Channel Impulse Response (Sep 2022)
Van-Lan Dao, Shaik Salman
International Conference on Emerging Technologies and Factory (ETFA'2022)

Multi-Processor Scheduling of Elastic Applications in Compositional Real-Time Systems   (Dec 2021)
Shaik Salman, Alessandro Papadopoulos, Saad Mubeen, Thomas Nolte
Journal of Systems Architecture, 2021 (JSA)

Scheduling Elastic Applications in Compositional Real-Time Systems (Sep 2021)
Shaik Salman, Alessandro Papadopoulos, Filip Markovic, Saad Mubeen, Thomas Nolte
26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021)

A Systematic Methodology to Migrate Complex Real-Time Software Systems to Multi-Core Platforms   (Aug 2021)
Shaik Salman, Alessandro Papadopoulos, Saad Mubeen, Thomas Nolte
Journal of Systems Architecture, 2021 (JSA)

Enabling Fog-based Industrial Robotics Systems (Sep 2020)
Shaik Salman, Václav Struhár, Van-Lan Dao, Nitin Desai, Zeinab Bakhshi Valojerdi
The 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2020)

Real-time Fog-based Industrial Robotic System: Applications and Challenges (Sep 2020)
Shaik Salman, Václav Struhár, Zeinab Bakhshi , Van-Lan Dao, Nitin Desai, Alessandro Papadopoulos, Thomas Nolte, Vasileios Karagiannis , Stefan Schulte , Alexandre Venito , Gerhard Fohler
The 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2020)