Muhammad Sajid received a B.Eng. degree from the National University of Sciences and Technology (NUST), a Master’s degree from the École Nationale Supérieure d’Arts et Métiers (ENSAM) Paris Tech, France, and a PhD degree from the University of Cergy Pontoise, France, in 2010. He completed postdoctoral research at Texas A&M University, Qatar. He is currently an Associate Professor with the National University of Sciences and Technology (NUST), Pakistan where he is the Principal Investigator of Artificial Intelligence for Mechanical Systems (AIMS) laboratory. He has authored over 50 peer reviewed publications and his current focus of research is towards integration of Machine Learning and Artificial Intelligence with mechanical engineering problems by exploiting cloud-based infrastructure for high performance computing, leading to applications in external aerodynamics, heat exchanger design, as well as time series problems in estimation of solar energy potential and urban water management for smart cities. Additionally, he has also worked with Internet of Things (IoT) based sensor arrays for real time data analytics in Heating Ventilation and Air-conditioning (HVAC) and indoor air quality monitoring. In short, his research integrates the three transformative technologies of AI, IoT and Could Computing with Fluid Mechanics problems for disruptive innovations.
Research Keywords & Expertise
Fluid Mechanics
Multiphase Flow
Thermal Management
CFD
Renewable and Sustaina...
Fingerprints
20%
CFD
5%
Thermal Management
5%
Fluid Mechanics
Short Biography
Muhammad Sajid received a B.Eng. degree from the National University of Sciences and Technology (NUST), a Master’s degree from the École Nationale Supérieure d’Arts et Métiers (ENSAM) Paris Tech, France, and a PhD degree from the University of Cergy Pontoise, France, in 2010. He completed postdoctoral research at Texas A&M University, Qatar. He is currently an Associate Professor with the National University of Sciences and Technology (NUST), Pakistan where he is the Principal Investigator of Artificial Intelligence for Mechanical Systems (AIMS) laboratory. He has authored over 50 peer reviewed publications and his current focus of research is towards integration of Machine Learning and Artificial Intelligence with mechanical engineering problems by exploiting cloud-based infrastructure for high performance computing, leading to applications in external aerodynamics, heat exchanger design, as well as time series problems in estimation of solar energy potential and urban water management for smart cities. Additionally, he has also worked with Internet of Things (IoT) based sensor arrays for real time data analytics in Heating Ventilation and Air-conditioning (HVAC) and indoor air quality monitoring. In short, his research integrates the three transformative technologies of AI, IoT and Could Computing with Fluid Mechanics problems for disruptive innovations.