Please welcome to the forum Dr. Zaid Al-Ars from TU Delft!
Dr. Al-Ars will be using the PI System as part of an applied research programme which aims to put the latest Machine Learning and data analytics tools into the hands of engineers close to the operations. This research is being conducted with participation from existing OSIsoft commercial customers, including Shell and DSM. The analytical platform being developed will enable engineers and operators to make predictions about plant processes and equipment in an intuitive and guided way, greatly expanding the real-world impact of data science techniques.
About Dr. Zaid Al-Ars:
Zaid Al-Ars is an associate professor at the Computer Engineering Lab of the Delft University of Technology, where he leads the research and education activities of the big data architectures research theme of the lab. His work focuses on addressing the bottlenecks in big data application scalability on multicore architectures and proposing optimized solution alternatives for system performance, memory, power, reliability, etc. The research interests of Dr. Al-Ars include:
- Analysis and development of multicore systems to accelerate big data applications such as bioinformatics
- Methods for application domain analysis and mapping to appropriate multicore architectures (CPU, GPU, FPGA)
- Design and optimization of interconnect solutions to improve system performance and relieve data transfer bottlenecks
- Design, characterization and test process improvement for multicore systems using the abundant computational resources available in these systems
Dr. Al-Ars is also a co-founder of Bluebee, a high-tech startup active in the intersection between the fields of cloud computing, high-performance computing and genomics applications. Prior to joining the TUDelft, Dr. Al-Ars spent a number of years in the Product Engineering Group of Infineon Technologies and Siemens Semiconductors in Munich, Germany, where he was responsible for constructing new test methodologies to reduce the overall cost of the memory production test flow.